WO2005043628A2

WO2005043628A2 - Diagnosis and monitoring of the cardiovascular system

Info

Publication number: WO2005043628A2
Application number: PCT/DE2004/002434
Authority: WO
Inventors: Horst Prehn; Rainer Sus; Marco Rohrbach; Uwe Schuster
Original assignee: W.O.M. World Of Medicine Ag
Priority date: 2003-10-31
Filing date: 2004-10-29
Publication date: 2005-05-12
Also published as: WO2005043628A3; DE112004002649D2; DE10351728A1

Abstract

The invention relates to a method and a system for diagnosing and/or monitoring the cardiovascular system of a living being, comprising at least one measuring means (2, 3), for the automatic measurement of at least one cardiac and/or circulatory system-specific parameter (20, 30), at least one determination means (6a), for the automatic determination of at least one time-resolved baroreflex of the living being from the measured cardiac and/or circulatory system-specific parameters (20, 30), at least one extraction means (6b), for the automatic extraction of at least one chronological series from the determined time-resolved baroreflexes, at least one evaluation means (6c), for evaluating the time behaviour of the at least one chronological series of the at least one measured baroreflex, at least one allocation means (6d), for automatically allocating the time behaviour of the at least one chronological series to physiological features and characteristics of the living being and at least one display means (8), for displaying the physiological features and characteristics of said living being.

Description

Method and system for the diagnosis and / or monitoring of the cardiovascular system of a living being

description

The invention relates to a method for diagnosing and / or monitoring the cardiovascular system of a living being according to the preamble of claim 1. The invention further relates to a system for performing this method according to the preamble of claim 21 and a system for diagnostics and / or Monitoring the cardiovascular system of a living being according to the preamble of claim 27.

To date, different methods have been used for diagnosing and / or monitoring the cardiovascular system of living beings. When monitoring or diagnosing cardiovascular systems in the clinical area, it is particularly important in the area of surgical medicine that the respective surgeon can use a monitoring device to recognize whether the patient is moving in an unstable state. Such an unstable condition can be triggered, for example, by blood loss (hypovolaemia) or by washing in distension media (hypervolemia).

The blood volume of a living being is an essential parameter that is of great importance in many physiological contexts. For example, in minimally invasive, endoscopic operations such as hysteroscopy or prostate resection, a fluid is usually fed into the corresponding body cavity as a distension medium. For example, physiological saline solutions or serve as a distension medium also electrolyte-free solutions, such as mannitol or sorbitol.

The distension medium can get into the bloodstream due to mechanical impairment of the tissue during the operation. In individual cases, more than 2000 ml of distension medium can enter the bloodstream, this hypervolemia being an undesirable strain on the heart. If a distension medium is used that has a different electrolyte content than that of the blood, TUR syndrome (trans-urethal resection syndrome) or hyponatrimia can occur.

It is known to monitor the resulting dangers by measuring the liquid flows. The disadvantage here is that the mass balances cannot be determined with the required precision, since the distension medium supplied does not completely pass into the bloodstream.

To date, monitoring of such dangers has included also used by an accounting method in which the inflow and outflow of the respective distension medium were measured. However, such accounting, volumetric methods are not very specific and are too slow to recognize a critical condition.

As a further detection method, the sodium concentration in the blood was measured, for example. A corresponding termination criterion can be derived from the sodium concentration, in which the operation must be stopped. However, such a measurement of blood on sodium is necessarily invasive. The object of the present invention is therefore to provide a fast and non-invasive method or a system for diagnosing and / or monitoring the cardiovascular system of a living being.

The invention is achieved by a method for diagnosing and / or monitoring the cardiovascular system of a living being with the features of claim 1.

For this purpose, measurement data of at least one cardiac and / or circulatory-specific parameter, in particular blood pressure and / or myocardial excitation, are first automatically, continuously and time-resolved. Thereupon, time-structured ensembles of measurement data are formed in order to generalize the measurement data determined and to reduce its complexity. These time-structured ensembles are formed with regard to the temporal procedural regulatory development of the cardiovascular system, in particular the heart rate variability and / or the pulse transit time. At least one time series to represent the temporal and regulatory development of the cardiovascular system is then determined on these time-structured ensembles. The temporal behavior of this time series is then analyzed. This temporal behavior of the time series is then assigned to empirically determined physiological properties and characteristics of the circulatory system. This assignment takes place in particular in relation to different parameterizable loads on the cardiovascular system, such as, for example, blood volume increase or decrease, physical loads and / or pharmacological interventions. The temporal behavior of the time series and / or the physiological properties and features is then displayed for the diagnosis monitoring of the cardiovascular system. The invention is based on the basic idea that the system behavior of the cardiovascular system contains all the information necessary for monitoring the cardiovascular system of a living being. The cardiovascular system has a number of effective and efficient regulatory mechanisms that act on the system in a self-stabilizing manner. For example, the Baro-Reflex controls the cardiovascular system based on pressure parameters based on the baro sensors.

For example, a blood or blood draw acts on the barosensor in such a way that the cardiovascular system is controlled in a stable state via the Baro-Reflex. This fast and adaptive regulatory behavior of the cardiovascular system thus forms the basis of various and highly efficient, body-specific protective mechanisms and therefore reacts directly to various types of exogenous or endogenous disorders. These reflex processes show further significant and covariant subsequent physiological reactions, which can also be demonstrated with non-invasive methods.

The method according to the invention makes use of this knowledge. The system behavior of the cardiovascular system is continuously and automatically measured over the course of time. The system behavior can be represented in different parameters or different measurement data ensembles, which are given, for example, by the heart rate variability and / or pulse transit time. From the complex measurement signal, for example one

Pulse curve, the complexity can be reduced by the ensemble formation, for example by assigning the ensemble a single value, such as the pulse transit time or the heart rate variability. The behavior of the cardiovascular system can then be viewed by forming time series and analyzing the time series. An empirically determined physiological phenomenon can then be assigned to the temporal behavior of the time series. The method is based on the knowledge that a cardiovascular system shows similar dynamic behavior under similar conditions. The respective underlying physiological phenomenon can therefore be inferred from this dynamic behavior.

To spatially resolve the dynamic behavior of the system, two cardiac and / or circulatory parameters are advantageously measured simultaneously. For example, the blood pressure can be measured simultaneously at two different distal locations in the body, or the myocardial excitation can be measured simultaneously with the blood pressure using an EKG.

The formation of time-structured ensembles can be achieved, for example, by forming windows of measurement data. The measurement data record is examined for significant positions within a specific measurement data window and one or more such values are then assigned to the window. Here, for example, the RR interval, an average blood pressure from two pulses or the pulse transit time can be measured within a time window when two measured values are correlated with one another.

In particular, the measurement data in the windows can be analyzed with regard to periodic components, in particular the time interval between two heartbeats. These analyzed values are then used as the time-structured ensembles. The time series can then be determined with these analyzed values of the windows. The analysis of the temporal behavior of the time series can advantageously be represented in a meta-representation by means of a reconstruction method. The time series can be represented in the form of Lorenz plots, phase spaces, parameter spaces, trajectory plots and / or Poincare plots. The time series can also be represented in the parameter space by means of a delay method or can be represented as a state vector in the parameter space.

From this representation of the time series, accumulation points, attractors and / or trajectories can now be determined. The temporal behavior of the accumulation points, attractors and / or trajectories can then be determined. From this temporal behavior of the accumulation points, attractors and / or trajectories, statements about the spatio-temporal relationship of the respective accumulation points, attractors and / or trajectories to one another can be derived in the parameter space. From the temporal behavior of the accumulation points, attractors and / or trajectories in the phase space, a measure for monitoring the course of the long-term development of the cardiac

Circulatory system.

For the empirical determination of the respective physiological properties corresponding to the temporal behavior of the time series, these can be carried out by simultaneous measurement of the respective physiological properties, in particular the heart rate, the mean blood pressure, the cardiac output and / or the stroke volume. This empirical determination is advantageously carried out when there is a defined load on the cardiovascular system, in particular by using physical, physiological and / or pharmacological means.

The assignment of the dynamic or temporal behavior of the body or system can be further improved in this way, that in addition to the temporal behavior of the time series, external and / or internal cardiac and / or circulatory-specific control parameters are included in the analysis of the temporal behavior of the time series and / or the assignment of the temporal behavior of the time series to empirically determined physiological properties.

This provides additional data that can be correlated with the time behavior of the time series. The external and / or internal cardiac and / or circulatory-specific control parameters are, for example, the heart rate, the mean blood pressure, the cardiac output, the stroke volume, defined volume flow rates, the volume inflow or outflow and / or ergometric work or Performance parameters.

The assignment of the temporal behavior of the time series to the empirically determined physiological properties and features is preferably carried out automatically.

The object is further achieved by a system for carrying out the method according to the preamble of claim 21.

Accordingly, the system has at least one measuring device for automatic and continuous measurement of at least one cardiac and / or circulatory-specific parameter of the living being, at least one recording device for automatic and time-resolved recording of the parameter measured with the measuring device and at least one evaluation device for evaluating the continuously and time-resolved parameter on .

The method described above can be carried out with such a system. It is advantageous if at least one cardiac and / or circulatory-specific parameter is blood pressure and / or myocardial excitation. A measuring device can be designed as a blood pressure measuring device and / or as an EKG. The measuring equipment used is advantageously non-invasive. The measuring means is also advantageously designed such that it is formed on a distal part of the body of the living being. It can be a pressure sensor.

The object is further achieved by a system for diagnosing and / or monitoring the cardiovascular system of a living being with the features of claim 27.

According to the invention, the system has at least one measuring device for automatically measuring at least one cardiac and / or circulatory-specific parameter, at least one determining device for automatically determining at least one time-resolved baro-reflex response of the living being from the measured cardiac and / or circulatory-specific parameters, at least one extracting device for automatic acquisition at least one time series from the determined time-resolved baro-reflex responses, at least one evaluation means for evaluating the time behavior of the at least one time series of the at least one measured baro-reflex response, at least one assignment means for automatically assigning the time behavior of the at least one time series to physiological ones Properties and characteristics of the living being and at least one display means for displaying the physiological properties and characteristics of the living being.

The system according to the invention takes advantage of the body's own regulatory regulatory processes in connection with the phasic baro-reflex. In the licensed In-house Baro-Reflex take into account all the essential current cardiovascular parameters. These include: the ejection performance of the heart, which depends on the contractile force, the stroke volume and the heart rate, the blood pressure curves depending on the respective distal location, the vasomotor regulation of peripheral resistance depending on the diameter and elasticity of the arteries.

Such a system represents a self-contained unit for the diagnosis and monitoring of the cardiovascular system of a living being.

It is advantageous if the pulse transit time, the heart rate, the blood pressure or the baro reflex sensitivity are used as the baro reflex response. The pulse transit time variability, the heart rate variability and / or the blood pressure variability can also be used as the baro reflex response.

A measuring device can be embodied in the system as an EKG device or as a blood pressure measuring device. The measuring means is preferably non-invasive.

The determination means, the extraction means, the evaluation means and / or the assignment means can be designed as software means.

The method described above can be carried out in the determination means, the extraction means, the evaluation means and / or the allocation means. In the allocation means, the temporal behavior of the time series can be set in relation to at least one stored, empirically determined behavior of a time series of the same baro-reflex response, this stored behavior being determined when the cardiovascular system of the same or another living being was stimulated. Here again the knowledge according to the invention is used that the system behavior of a cardiovascular system triggers similar reactions of the baro-reflex system in many living beings when this system is stimulated in a similar way.

The excitation of the cardiovascular system for the empirical determination of the comparison time series can be stimulated in particular by physical action, in particular infusion, blood sampling and / or physical stress and / or by pharmacological action.

In the assignment means, at least one control parameter can additionally serve to assign the temporal behavior of the at least one time series to physiological properties and characteristics of the living being. If this further control parameter is advantageously provided by at least one further measuring device or by the already existing measuring device. This control parameter can preferably be the mean heart rate, the mean blood pressure, the infusion volume, the blood withdrawal volume, the distension agent volume or the distension agent balance and / or an ergometer performance.

When monitoring a patient when the time behavior of the time series is assigned to a critical cardiovascular state, a warning is advantageously output on the display means. Such a system or such a method can be used in intensive care medicine, sports medicine, rehab medicine, anesthesiology, and for monitoring fitness equipment or for general cardiovascular diagnosis. In the area of general cardiovascular diagnostics, monitoring can also be carried out when carrying out a stress ECG, for example to prevent the patient from collapsing. The invention relates to a method and device for the evaluation, representation, analysis and for the representation and clinical evaluation of the properties and the course of the temporal development of complex dynamic states and for characterizing the dynamic quality of the autonomous physiological behavior of the human or animal heart. Circulatory system under multiple and changing endogenous or exogenous loads or in the manifestation of pathophysiological conditions in connection with the derivation and acquisition of objective and quantifiable functional parameters, parameters and criteria for clinical function diagnostics, monitoring and therapy control.

Under the highly generalized view, all previously known clinical procedures in connection with cardiovascular diagnostics are based on the one hand on certain morphological aspects of the specific organs themselves. A corresponding methodological approach is essentially achieved through the use of appropriate imaging methods. On the other hand, these morphological data are linked to the various cardiovascular functions and assessed under certain functional diagnostic aspects on the basis of their specific hemodynamic parameters in connection with further substance-specific laboratory values. A comprehensive assessment of the respective patient-specific The circulatory status therefore only emerges after the collection and evaluation of all the clinical data required for this from the imaging procedures, hemodynamic examinations and laboratory diagnostic analysis results using the appropriate expert knowledge. This type of diagnosis thus largely reflects the steady state of the circulatory system determined at the time of the examination.

In the particular clinical case of continuous monitoring and diagnostic evaluation of the dynamic development of certain physiological or pathophysiological circulatory conditions, the diagnostic question, however, essentially shifts to the procedural aspect of the circulatory functions. The clinical problem is primarily focused on the in vivo observation of sudden changes in acute cardiovascular conditions. The medical-technical requirements for a corresponding monitoring method are therefore essentially directed towards the early detection of certain unstable or critical conditions so that clinical action can take place as quickly as possible. Furthermore, there is a demand for the most immediate possible therapy control and a direct objective proof of effectiveness of the interventions initiated in each case.

The methodological approach of all known methods for in-vivo monitoring and circulatory monitoring has the basic disadvantage that no suitable detection and diagnostic method has yet existed which is capable of high complexity, diverse networking, dynamic adaptivity and To adequately record the plasticity of the surgically closed cardiovascular system, including its autonomous regulatory mechanisms and compensatory services, and to represent its process development accordingly in a significant way. So limit yourself The currently known methods essentially relate to the isolated detection of a few externally accessible hemodynamic parameters, vital signs and laboratory values, which are then subjected to a largely phenomenological assessment and are related to corresponding interindividually determined and statistically validated reference values (external reference methods ). Due to the considerable individual and inter-individual variability, only statistical information is available as a basis for the acquisition of clinical criteria, which must not take into account the individual patient-specific features.

Against this background, there is a demand for a corresponding in-vivo diagnostic method which, on the one hand, is able to complete the complex process quality and all highly networked functionalities of an individual's entire physiological system behavior despite the methodically limited physical observability capture. The task according to the invention accordingly consists, on the one hand, of representing these system states by corresponding mathematical structures or mathematical structures which correspond to the essential physiological system behavior and which are then accessible to a corresponding mathematical analysis.

On the other hand, the further metrological task is to determine suitable and easily accessible process data under in vivo conditions in such a way that it also adequately reflects the autonomous individual regulation and control of the physiological behavior of the cardiovascular system. These tasks are solved by the claimed method and device. It was based on the knowledge of the invention that the organic system behavior manifests itself in the form of dynamic quality in the course of changing qualitative and quantitative physiological or pathophysiological conditions. In this generalized form, this approach applies in principle to any type of dynamic quality with regard to the physiological system behavior under consideration. Of particular clinical relevance from the point of view of the claimed method is the fundamental distinction between the established (orthodynamic) system behavior and the correspondingly identified forms of dynamic anomalies.

In this aspect, e.g. Cardiac arrhythmias or bradycardias or tachycardias or other haemodynamically significant dynamic manifestations in many cases express missing or altered intrinsic pacemaker functions, control functions or coupling conditions.

The essential diagnostic potential of the claimed method thus lies in the dynamic analysis and monitoring of the course in connection with the corresponding manifestation of the dynamic determinants examined in each case of certain physiological or pathophysiological states and dynamic state changes.

In the foreground of a clinically usable monitoring process is the influence of special stabilizing or destabilizing factors with regard to the acute prevailing regulatory performance in connection with an in vivo detection of critical deregulatory or decompensatory conditions, as well as after objectification and quantification of sufficient stability - criteria or the acquisition of diagnostically and prognostically relevant process parameters.

To obtain suitable clinically relevant diagnostic parameters and characteristic values, the claimed analysis methods as well as structure and time-dispersive detection methods as well as special methods of signal processing and display methods are used.

The claimed method is based on the use of certain endogenous reflective regulatory processes of the cardiovascular system in medical technology in direct connection with the relevant autonomous, highly specific, sensitive and effective, sensory, adaptive and compensatory services and the access according to the invention to this system behavior through Conception, specification and development of suitable exogenous interfaces with regard to the selected autonomous circulatory reflex control mechanisms on the basis of system-theoretical or bio-cybernetic approaches in connection with the way in which they are implemented technically in the form of certain measurement strategies and sensor technologies for signal acquisition as well as selected ones Methods for signal processing and processing, as well as specified analysis methods for evaluating and obtaining certain process parameters, sys characteristic features and parameters, as well as suitable representation and presentation methods for monitoring the course and functional diagnosis of certain process information, as well as corresponding automated or semi-automated classification and recognition methods for suitable clinical evaluation and in vivo recognition or for suitability for objective operative and postoperative Monitoring of regulatory or compensatory developments Development regarding the occurrence of acute or impending critical circulatory conditions.

With the help of appropriate embodiments of the claimed method, numerous functional diagnostic questions and clinical monitoring tasks are thus solved. A particular advantage arises from the special possibility with regard to an objective self-referential in-vivo determination of diverse functional interdependencies and derivation of clinically meaningful criteria in direct connection with the currently prevailing individual circulatory regulation, as well as through the objective determination of the essential dynamic determinants associated with this complex regulatory events. It is also particularly advantageous that, in contrast to the usual and known clinical methods, the claimed method also does not require any invasive and multiple sampling, as well as complex sample preparation and laboratory analytical in-vitro determinations of substance quantities or substance conversions, which as a rule are only random can take place and are consequently subject to corresponding delays, as a result of which no continuous in vivo monitoring or rapid detection of acute critical conditions is possible under these circumstances.

The claimed method, on the other hand, only comes with a sensor system that is common in clinical routine and is also widespread and well known and can be applied extracorporeally in a simple manner (e.g. for EKG and

Pulse) in conjunction with a mathematical analysis of the complex regulation dynamics implemented in the method, which, as the at least necessary input signals, only requires two continuously and simultaneously derived signal channels. In addition, the method in principle characterized by a simple, secure and interference-insensitive data acquisition, whereby as a rule no particular problems regarding critical detection limits or artifacts that are difficult to control can occur. The fact that the basic hardware can be created inexpensively and with constant measurement value configuration at any time subsequent adjustments, extensions and diversifications of the analysis algorithms, display programs and monitor functions for a variety of other is advantageous for a wide range of clinical applications, as well as for industrial medical technology applicability future applications and specific diagnostic questions can take place.

The procedure can be carried out with the following steps:

Step 1: Identification, specification and extraction of the relevant and representative as well as metrologically accessible cardiac and / or circulatory physiological state variables and order parameters, which implicitly include, represent and represent the properties of the complex dynamics of the autonomic cardiovascular regulation processes clearly describe, in conjunction with corresponding system-specific control parameters, which represent at least one control variable for the dynamics of the myocardial excitation processes and / or the circulatory regulation processes with regard to pressure and / or volume regulation and / or central load-dependent regulatory processes of the organ circulations. and which fundamentally enable an objective characterization of the temporal structure formation in the course of the regulation, by assigning the specific procedural physiological properties, their dynamic quality, their dynamic development, and so on e of their sensory, adaptive and / or compensatory services corresponding theoretical models, simulation and analysis methods of non-linear dynamics (NLD) through the construction of appropriate mathematical structures that adequately represent these essential physiological properties, as well as through the specification and formation of an appropriate interface for process interaction on the basis of the relevant With the help of at least two sensors of selected process data obtained in vivo or the means used in this regard for intervention and / or provocation and / or stimulation of certain circulatory physiological effects.

Step 2: Time-synchronous preparation of the multiple measurement variables determined by step 1 and the state variables or control parameters derived therefrom with regard to their specific suitability for the application of the following methods by application of specific method steps: a. when evaluating corresponding particularly low-noise, low-artifact scalar time series with high time resolution and voltage resolution as well as low digitization noise, and b. in the further processing of the measured variables and time series with regard to their specific suitability for the correspondingly specified representation methods, provided that a successful reconstruction of certain substitute state space (phase space) representations from the relevant empirical time series, in particular under the condition that the topological properties, ie the neighborhood relationships between the respective empirically obtained substitute state space with the respective empirically inaccessible original

State space should largely correspond, and c. in the implementation of the downstream analysis methods to avoid impairment of the analysis result due to noise and artifacts. 3rd step: designation, specification, acquisition and signal representation of parallel and simultaneous time series from the previously prepared measurement data by certain process steps, in particular by appropriate timing processes to determine the occurrence times of certain signal components and / or to determine certain parameters and / or characteristic values and / or features with regard to their further use for the downstream analysis methods.

Step 4: Designation, specification and creation of appropriate representations of the state of space with the help of certain reconstruction methods, in particular by applying delay methods to the corresponding time series and by incorporating certain method steps and criteria for the optimal selection of the embedding window used ( D.τ) with regard to the requirements for a practically sufficient applicability of a simple and robust delay reconstruction in finite time series with a limited number of data points and measurement accuracy, and with a common or separate optimization for the respective embedded dimension D and for the delay time τ.

Step 5: Representation of the reconstructed trajectories, iterative sequences or attractors with regard to the chosen state space embedding dimension for a. Investigation of the properties of the flow defined by the respective dynamics and b. for assessing the quality of the reconstruction of the state space and the positional relationships of the Zu¬

Status vectors and / or the status space filling and / or attractor expansion according to certain static attractor-based and / or topological criteria and / or according to a certain dynamic-based course of the trajectory movement and c. the appropriate assessment and choice of Delay time τ and / or the embedding dimension D and d. to minimize errors such as redundancy or irrelevance errors, and e. To assess the necessity and the effects of further process steps downstream of the embedding and, in certain cases, necessary process steps to optimize the quality of the state space representation by means of corresponding coordinate transformations (such as, for example, main axis transformation of the correlation matrix, Karhunen-Loeve transformation, etc.).

6th step: Representation of higher-dimensional state spaces through dimension reduction for exploration of the attractor topology generated and identification and / or recognition of the states and / or course monitoring and in-vivo monitoring of the respectively examined circulation trajectory development by a. certain state projections of the relevant attractor onto a 2D or 3D manifold or through b. Isoshell projection of the relevant attractor or by c. Corresponding Poincare cuts or by e. corresponding recurrence pictures or f. other suitable mapping processes or mapping processes.

7th step: Analysis of the temporal dynamics and / or significant dynamic changes due to the properties of the rivers in the state space represented in each case, as well as by determining certain significant structural dynamic parameters and / or fluctuation measures and / or certain dynamic stability characteristics and / or Complexity measures for characterizing the current level of structuring, as well as the temporal development of the structure formation of circulatory and / or myocardial excitation processes, in particular by calculating the currently effective correlation dimension and / or the Lyapunov exponent or the Kolmogorow entropy and / or the localized Lyapunov exponents and / or the location vector course of the respective trajectory and / or the attractor location tiling area.

Step 8: Analysis of the temporal dynamics and / or significant dynamics change or mode change (phase transitions) through the properties of the time series correlating with one another with respect to the respectively determined tachometric, parametric and / or state time series, in particular by the determination of the mean squares of successive differences of the respective interval variabilities and / or by the determination of the corresponding successive algorithmic complexity with respect to the respectively predetermined time sequences and / or by determination of corresponding successive feature vectors with respect to the respectively determined regulatory episodes.

Step 9: Analysis of the influences of the different physiological control parameters with regard to the occurrence or change of certain dynamic modes of the cardiovascular system by determining the respective dependency of the state space representations determined in this regard and / or the corresponding attractor representations or projections and / or the derived parameters for identifying or identifying the respectively occurring modes, of certain values of the control parameters, in particular of the heart rate (HR) control parameters, various blood pressure values and / or the mean blood pressure, and / or the pressure-volume work , and / or different blood volumes or volume flow rates, and / or cardiac output, among others related energy or

Performance parameters, such as the heart rate dependency of the correlation dimension and / or the Lyapunov exponent and / or the blood volume dependency of the Lyapunov exponent or the location vector or the attractor position tiling area, among other things, for the purpose of characterization and specification of the dynamic properties and quality of the behavior of various autonomous cardiac, circulatory, central and / or local regulatory processes.

10th step: Assignment of the properties of the structural dynamic analysis results to physiologically or pathophysiologically relevant clinical findings, which represent at least one functionally diagnostically significant condition of the cardiovascular system or certain regulatory functionalities.

The method and the system are described below for two applications:

a. Closed circuit applications (isovolaemic conditions)

On the one hand, in the case of the closed circulatory system, those clinically relevant process parameters are determined which are involved in the reflex regulation and which also adequately characterize the respective functional dynamic system state on the theoretical basis of a non-linear dynamic analysis (complex system theory). These analysis results then enable systemic functional diagnosis and follow-up of the specific development of cardiovascular conditions in connection with the maintenance, adaptation or stabilization of regular cardiovascular functions or the identification and detection of the occurrence of critical deregulations. With the claimed

Methods can also be used to investigate the effects of various types of circulatory stresses and their effects on adaptive regulatory performance and dynamic modes under in vivo conditions. Here are the adaptive effects of regulatory benefits the circulatory functions both under certain specific, parameterizable and quantifiable stresses and physical or pharmacological interventions as well as under different, undefined, unspecific and / or unpredictable and changing exogenous or endogenous effects, as well as under special physical and physiological conditions or stresses and / or or detectable in certain pharmacological interventions.

b. Open circuit applications (hypo- or hypervolemic conditions)

Another special application of the claimed method relates to certain situations of an open circuit, such as if there is an acute decrease (hypovolaemia) or increase (hypervolemia) in the blood volume. On the one hand, this can take place under controllable and / or quantifiable conditions and with known or quantifiable volume inflow or outflow, e.g. in the case of an invasive opening of the vessels for the purpose of drawing blood or an infusion or perfusion.

On the other hand, however, fundamentally uncontrollable and / or unpredictable and unpredictable volumic stresses can occur, for example due to occult volume flows, such as a sudden loss of blood (outflow) in the case of various types of vascular lesions or perforations or in the course of hemorrhagic complications. Likewise, unpredictable acute hypervolemic flushing, e.g. in the form of a certain proportion of a rinsing solution in the bloodstream in connection with certain endoscopic interventions (inflow), which under the effect of a certain distension pressure can also occur in various ways, e.g. via the vascular and lymphatic systems Perforations as well as with intact endometrium or through speaking (delayed) absorption (eg peritoneum) can take place.

The claimed method is also suitable for the use of the cases described under a) and b) both for objective cardio-vascular functional diagnostics and for the quick in-vivo detection of regular or irregular, destabilized, decompensatory and critical conditions or changes in conditions as well as Obtaining objective and significant clinical diagnostic and prognostic criteria for circulatory monitoring.

The method is fundamentally based on the properties described below.

The acute dynamic self-behavior of the autonomously closed autonomous reflex control mechanisms, which are closed in a complex and adaptive manner in a complex and adaptive manner, in connection with the specific performance of the higher-level, central and local regulation of the cardiovascular system.

Systems manifests itself in the form of a few selected, both physiologically relevant and easily accessible, efferent output components of the various covariant and time-correlated autonomous reflex responses (e.g. Baro-Reflex) on different effector levels.

At the cardiac effector level, the reflexive regulatory behavior (e.g. with regard to the fast phasic component) essentially manifests itself in a special way through significant complex temporal patterns and specific variability in cardiac rhythm, as well as through its characteristic temporal development in the course of each individual stroke sequence (beat to-beat variability). Heart rate variability HRV and its dynamic development HRV (t) also has a direct regulative and co-variant connection with the reflex action on the vascular level, whereby correspondingly correlated form variabilities of the corresponding arterial pressure curve (pulse curve variability) develop (with characteristic variabilities of the pulse shape as well as the systolic, diastolic and dicrotic pressure amplitudes). In addition, these reflective efferences also correlate with the level of the vasomotor effector component with corresponding regulatory effects on the mechanoelastic and geometrical variability of the vessels, which means that with each heartbeat there is also a covariable variability in the pulse wave velocity or the pulse - Transit time (pulse transit time, PTT) is coming. Due to the time-synchronous and continuous derivation of the cardiac component, e.g. by derivation of the electrocardiogram EKG (t) in connection with the acquisition of arterial pulse curves p (t) from at least one lead location (e.g. A. radial and / or A. femoralis) as a vascular component This means that all metrological requirements are generally created in order to determine the suitable system parameters for the claimed process. Description of the individual steps of the procedure:

Brief overview:

1st step: Identification of the relevant and accessible status variables, order parameters and control parameters and selected process data as well as specification of the interface (sensor and process interaction) 2nd step: Preparation of the measured variables, status parameters and control parameters regarding Suitability for further process steps under best. conditions

Step 3: Identify various. Simultaneous time series with the help of timing procedures or parameter extraction or characteristic extraction Step 4: reconstruction of state space representations and optimization procedures

Step 5: Multiple representations of the reconstructed attractors for further investigation, attractor-related optimization and error minimization of the procedure

Step 6: Representation of higher-dimensional status rum representations by reducing dimensions for exploration Step 7: Analysis of the attractors with regard to the properties of the rivers in the state space and determination of structural dynamic parameters and fluctuation measures

Step 8: Analysis of the properties of correlating time series and determination of successive dynamic parameters and complexity measures. Step 9: Analysis of the dependence of dynamic modes on specified physiological control parameters to identify and identify the modes that occur. Step 10: Assignment of the analysis results to the nature and functionality of the cardiovascular system

Regarding step 1: is particularly characterized in that, in accordance with the task of the invention, certain relevant and representative physiological state variables and control parameters can be obtained, which are evaluated in a certain way from time-synchronous derivations of electrocardiograms and blood pressure curves, and which the adequately represent and clearly describe the complex dynamics of the autonomic cardiovascular processes, and for this either the ECG signals are continuously registered by at least one corresponding ECG lead, which is recorded with the blood pressure curves recorded simultaneously and corresponding to the respective cardiac action are in a time-synchronous relationship and which are recorded by at least one blood pressure sensor at a related arterial site, or alternatively, also a continuous and simultaneous one Detection of at least two blood pressure curves measured at different arterial sensors can be carried out with the aid of several blood pressure sensors, and that at least one related control parameter, for example in the form of the heart rate (HR), can be obtained from either the respective RR intervals or the respective pulse frequency, and that further control parameters regarding the pressure or Volume regulation can be obtained from the measured blood pressure curves or from additional volumetric measurements and that further control parameters with regard to the load-dependent regulation processes of the organ circuits are determined accordingly from additional ergometric measurement data.

The time-synchronous and continuous detection of ECG signals from at least one lead position according to one of the known lead methods (Frank, Einthoven, Wilson and others) can be advantageous in connection with the derivation of the arterial pulse curves corresponding to each heartbeat from at least one lead location ( For example, A. radialis, A. feminal, etc.) are carried out using appropriate methods for digital data acquisition and measurement data processing.

The specific assignment of the specific process properties of the cardiovascular system in terms of their dynamic quality to corresponding mathematical models, which adequately represent the essential physiological properties, is characterized in that corresponding models, simulation methods, representation methods and analysis methods of non-linear dynamics and / or the use of synergies, and in which the corresponding physiological state variables and / or control parameters are entered as certain observables (measured variables) and are calculated accordingly and, where the necessary interface for process interaction is characterized on the one hand by the designated sensors and on the other hand by appropriately trained means such as various applicators and / or actuators for intervention and / or provocation and / or simulation of the circulatory physiological effects to be achieved.

Description of the measured variables used in the preparation process according to step 2:

Due to the possibility of a serious impairment of the downstream representation and analysis processes due to certain artifacts and noise influences as well as the high sensitivity of some algorithms to numerical errors, the type and quality of the measurement parameters must meet special requirements. The preparation of the measurement data, for example by means of known noise-reducing methods, is therefore usually unsuitable, since the superposition principle no longer applies to the non-linear processes examined here. In particular, the customary low-pass filtering, which corresponds to a moving averaging, cannot be used in this case, since it can, for example, contribute to incorrectly increasing the attractor dimension. Because of the broadband nature of chaotic methods, filtering in the frequency domain is also not a suitable method for improving the signal / noise ratio. Thus, two different strategies and procedures are used to solve this problem. On the one hand, signal processing according to step 2 takes place initially in the signal space according to the optimal conditions determined by the invention and, on the other hand, if necessary, further methods for artifact or noise reduction are used in conjunction with the processing step of the state space reconstruction according to step 4 which was carried out later. Usually, the sig- nal processing sufficiently low artifact and low noise time series can be obtained. If that is not yet sufficient, an additional Karhunen-Loeve transformation can advantageously be carried out in the state space.

Regarding step 2: is characterized in that the measured variables registered with the preceding step synchronously and in parallel are processed in such a way that they sufficiently meet the requirements associated with the subsequent method steps, in particular,

- that in order to achieve the temporal resolution necessary for the evaluation, the sampling rate for both input signals EKG (t) and P (t) must be far above the usual regular sampling rate (e.g. according to the Shannon-Nyquist condition). In the embodiment used, the sampling rate is above 3000 Hz. The resolvable time steps should be less than 0.3 ms and

-that the signal acquisition and processing are appropriate

Has means for avoiding or reducing artifacts, in particular that time series which are as low-noise and low-artifact as possible with high time resolution and voltage resolution as well as low digitization noise are evaluated, and

-that further process steps are provided, whereby the efficiency and quality of the signal processing and its suitability for the successful representation of the state space can be assessed on the basis of the results obtained with the subsequent process steps, such as, for example, on the basis of certain topological or dynamic properties. the attractor reconstruction, and that certain smoothing algorithms, for example N-point smoothing, are used in the signal processing of the raw signals, further examination methods being used which enable the selection of the critical number of points N which is suitable and which is significant for the achievable measurement accuracy of the trigger time marks, and

-that appropriate timing procedures are provided which are used to obtain the appropriate time stamps for determining the occurrence times of the various ECG components (such as R wave, p wave, T wave, late potentials, etc.) and corresponding sections ( such as the respective slope maxima, ST sections, etc.) and the various pulse curve components (such as systolic maximum, diastolic minimum, maximum of the dicrotic wave), as well as corresponding sections (such as the slope maxima concerned, systolic, diastolic intervals and intervals) between systole and dicrotic wave) are suitable.

Description of the designated timing procedures according to steps 2 and 3:

The exact derivation of the time stamps is, among other things, a particularly critical condition for the successful applicability of the method, whereby the conventional trigger methods (such as according to the threshold value method) are used as the timing method due to the individually and inter-individually occurring pulse curve shape variability and due to the different ones Dynamics of ECG and pulse signals as well as various artifacts and baseline fluctuations or offset components are not suitable for use with regard to the claimed method, since on the one hand these can lead to an inadmissibly large time jitter and also to incorrect time marks , With the claimed timing process the problem of extensive independence from the pulse curve variability, various artifacts and baseline fluctuations was solved, which means that the true trigger marks are reliably derived with a time jitter below the time steps that can be resolved.

a. In one embodiment, instead of the usual threshold values in the form of predetermined signal amplitudes, corresponding predetermined slopes are selected and these are set as slope threshold values (ΔU (t) / Δt) = Si (i = l ... n). In the case of a rising signal edge, these Si serve as corresponding trigger criteria. In the course of the timing process, a predetermined constant time window (search window Δt) samples the respective signal with the time steps determined by the sampling frequency. The gradient that occurs acutely in the constant time interval is determined and compared with the predetermined gradient threshold value Si. When the slope threshold is exceeded, a trigger mark is set. In the case of the ECG signal, the slope threshold can be set so that triggering takes place, for example, at the time of the maximum slope of the R wave. If this is necessary, the corresponding time stamps and times of occurrence of the maximum gradients for the other ECG components can also be obtained individually or in combination. In the case of the pulse signal, the greatest systolic rise or the dicrotic rise can be triggered accordingly. The appropriate slope threshold values and the time window are selected by previous empirical studies. To rule out faulty multiple triggers within the same heart action, the process is blocked for a certain period of time after the threshold has been exceeded for the first time. b. In a further embodiment of the method, a timing method is used for the exact and, above all, unambiguous determination of the respective occurrence times for the corresponding extreme values (maxima or mini a) of the corresponding ECG and pulse signals, a determination of the respectively associated maxima or Minima of the blood pressure amplitude values (eg systolic, diastolic pressure and pressure amplitude of the dicrotic wave) take place. For this purpose, with the help of a windowed extreme value search method, a correspondingly predetermined time search window is set when the respectively derived trigger time mark occurs and the signal maximum or minimum occurring in this search window is detected. The freely selectable width of the respective optimal search window results from a previous empirical determination of the corresponding pulse widths for the corresponding signal components of the EKG or pulse signal. With the help of this windowed max. Or min. Detection, a clear and reliable determination of the occurrence times and amplitudes of all the desired signal components is thus given with the required temporal accuracy.

c. Because of the principally different signal shape occurring in both leads, for example the R wave of the EKG in relation to the systolic pulse curve, an exact detection of the time of occurrence for the systolic maximum, which is much broader in relation to the R wave, is generally associated with greater inaccuracy , However, in order to obtain an optimal PTT time measurement, in the case of the pulse curves corresponding to the EKG, the time stamps for the time of occurrence of the largest systolic increase (max. Gradient) are used. For this, in one embodiment according to the under a. Use the slope threshold as described. In another form of training after a corresponding signal smoothing, the pulse curve is differentiated and then on the differentiated pulse signal that under b. described method for determining the occurrence time used for the maximum. The occurrence time for the maximum slope of each component of the pulse curve can also be determined in this way.

d. When processing signals, the raw signals of the pulse curves in particular are subjected to a corresponding smoothing. The known smoothing algorithms used in each case are empirically optimized with a view to achieving the lowest possible time jitter. For this purpose, the time jitter that can be achieved is determined beforehand under the changing conditions of the signal processing. Appropriate optimization procedures are then carried out and validated on the basis of this data. This process step is necessary due to the multiple dependency of the time jitter that occurs and the related critical time measurement, among other things. of the specified pulse shape, the selected sampling rate and smoothing level in the claimed process. In one embodiment, e.g. using a sampling rate of 3 kHz for the determination of the time of occurrence of the systolic maximum, a point smoothing with a smoothing level of 20 to 24 points proved to be optimal. The maximum time deviation that occurred remained below 0.3 ms and thus below a single sampling time step.

e. With the following step, the corresponding process parameters, which characterize the cardiovascular system behavior and these with regard to their characteristic synchronous temporal development, are determined from the prepared ECG signals as well as the simultaneously recorded pulse curves and the respective time sequences of the designated trigger time marks by means of further further processed representation and analysis procedures.

Regarding step 3: is characterized in that certain simultaneous time series are identified and specified accordingly, which are derived from the measurement data previously prepared with the preceding steps using the designated a. Timing procedures for determining the specific times of occurrence with respect to certain signal components corresponding tachometric time series are created, in particular:

a. Tachometric time series with regard to the heart rate variability HRV (ti) or RR (ti) tachogram and / or further ECG-specific time interval tachograms such as e.g. PQ (ti), ST (ti) and / or further occurrence tachograms P (ti), R (ti), T (ti) within each ECG complex and / or with regard to the pulse transit time variability PTTV (ti) and / or further pulse curve-specific time interval or occurrence time tachograms with regard to the systolic, diastolic component and the dicrotic wave, etc.,

-that certain b. Parametric time series are created, the relevant parameters, parameters or characteristics being determined on the basis of certain parameter evaluation methods, in particular:

Parametric time series with respect to the blood pressure curves are created, with certain characteristic parameters being evaluated on the basis of the absolute or relative blood pressure values and / or on the basis of certain characteristics relating to the pulse shape, for example by the fact that certain excellent values of the systolic, diastolic blood pressure and the maximum Amplitudes of the dicrotic wave are used and offset in a certain way. be determined by determining the relevant pressure differences, pressure quotients and / or the integral values of a specific area segment and / or by forming certain differences or quotients therefrom and / or by using known downstream signal analysis methods (e.g. Fourier analysis, correlation analysis, wavelet -Analysis, among other things), certain one-dimensional or multi-dimensional pulse shape-specific features are obtained, which are summarized, for example, in the form of corresponding feature vectors and / or feature spaces, which, as certain parametric time series, reproduce the successive development of the pulse shape variability in a significant manner.

Description of the designated time series representation method according to step 3 (time series representations of the different variabilities):

a. Tachometric time series: characterize various time-dispersive variabilities and fluctuations with regard to certain specified time intervals with regard to the occurrence times of various excellent signal components. With regard to the large number of system-specific time intervals that can be determined using the method, there are multiple variants of different tachometric time series.

In particular, the respective time intervals are determined from the time series with regard to the appearance times of successive R waves.

The temporal development of the regulatory-related significant time differences of successive RR intervals that occur thereby characterizes the heart rate variability (HRV). By representing the time course of the currently occurring RR interval time for each because two consecutive heartbeats, the HRV (ti) for i = 1 ... N beats) is shown in the form of an HRV tachogram.

Correspondingly, the time difference between the occurrence time of the R wave, determined from the EKG signal, and the occurrence time of a certain excellent amplitude or respectively, which appears with a corresponding delay, Slope value e.g. Amplitude maxima of the systole or the dicrotic wave or their gradient maxima in the course of a pulse curve corresponding to the current heart excitation determines the corresponding pulse transit time (PTT) for the respectively selected position of the arterial blood pressure sensor. The continuous temporal development of the PTT, which varies significantly with each heart action, thus characterize the dynamics of vascular regulation events as PTT variability PTTV = PTT (ti) and can therefore be represented as a PTT time series in the form of a PTT tachogram.

In the case of a special embodiment of the method, the HRV (ti) and the PTTV (ti) are also determined on the basis of two arterial blood pressure curves registered at different derivation positions, for example the brachial artery and the femoral artery. Here, the HRV (ti) is determined on the basis of a selected and continuously registered blood pressure curve on the basis of the relevant time difference in each case of two successive pulse beats, the corresponding time intervals of the time stamps for the occurrence times of consecutive systolic gradient maxima being determined, for example. The PTTV (ti) result in a corresponding manner from the respective time difference with which the respective pulse wave first reaches the heart (proximal) and then the heart (distal) lead. The corresponding significantly varying time differences between the relevant performance times for the corresponding The amplitude or slope values drawn from the two pulse curves are then determined on the basis of the respective time marks.

The parallel and synchronous pulse-train representation of the temporal development of HRV (ti) and PTTV (ti) can again take the form of two tachograms. A corresponding procedure is also used when using further pulse recorders attached distally to different derivation positions, the corresponding PTT being determined for the relevant arterial vessel sections.

With regard to an exact chronological assignment of certain resulting regulatory cardiovascular status changes in connection with the initiation of special clinical interventions or in connection with the fixing of the times of corresponding sampling with accompanying in-vitro laboratory diagnostics and / or for the identification of certain excellent regulatory E - Pisodes can be marked accordingly in the relevant displays by means of externally triggered time stamps.

Furthermore, from the EKG signals, by using the described timing method, further time intervals characterizing the myocardial excitation processes, e.g. PQ intervals, QT intervals, ST routes and / or QRS groups and their related variabilities are determined and represented and displayed in different ways in the form of tachograms and / or different types of seif organization feature maps.

b. Parametric time series: characterize various parameter-dispersive variabilities and fluctuations on the one hand with regard to certain excellent blood pressure amplitude values or amplitude differences and / or amplitude ratios and on the other hand regarding certain significant changes in pulse shape with corresponding pulse signal components. (With regard to the acquisition of corresponding parametric time series, a wide range of variants is again possible.)

In addition to those under a. The tachometric time series described can be determined with the aid of the claimed method from the respective pulse curves in addition to the time-dispersive fluctuations and variabilities mentioned, as well as corresponding significant dynamic changes in the pulse shapes and fluctuations in blood pressure. With the continuous online recording of each individual pulse curve, corresponding clinically relevant characteristic values or process parameters can be obtained with the aid of corresponding known analysis methods and certain evaluation methods, which also go into the meta-representation and representation forms described in more detail above. Among other things, the following analyzes and evaluations are conceivable:

Determination of certain excellent but pressure values such as the systolic, diastolic and dicrotic pressure values and determination of their variabilities or fluctuations

Time series representation of the dynamic development of the pulse curves themselves or the development of the absolute or relative systolic, diastolic, and / or dicrotic blood pressure values and / or the corresponding pressure differences determined therefrom (eg Δ p = p (syst) -p (diast); or p (syst) -p (dikr) etc.) and / or the corresponding pressure ratios (e.g. pressure value quotient) - Determination of absolute or relative integral characteristic values as well as the related differences and / or quotients from the corresponding surface segments of the pulse curve and their variabilities and fluctuations

Determination of corresponding characteristic shape-specific parameters from the registered blood pressure curve profile based on the separate or combined application of known signal analysis methods (eg Fourier or spectral analysis, correlation analysis, wavelet analysis, etc.) and / or extraction of corresponding features and generation of multidimensional ones Characteristic vectors and determination of their variabilities and fluctuations (eg characteristic vectors in the form of spectral amplitudes at n predetermined frequencies (f1, f2, .., fn) or by means of the values determined from the pulse signal for a specific number k of the wavelet - coefficients (λl, λ2, ..., λk) etc.)

c. Pulse-train representations: characterize the chronological and time-correlated relationship of multiple tachometric and parametric simultaneous time series through their time-synchronous parallel summary and display. (Numerous variants are also possible here)

-The complex dynamics of the reflex regulatory events are largely represented in the temporal development of the HRV (ti) with regard to the cardiac events and are represented in the form of corresponding tachograms according to section a. shown. For this purpose, the variable RR intervals are shown as ordinate values for successive heartbeats on a time axis from the time marks derived in this regard. - The dynamics with regard to the myocardial excitation processes influenced by the influence of certain vegetative efferences is also represented in the temporal development of the corresponding time intervals which characterize the specific myocardial excitation. Correspondingly, for example, the PQ or QT intervals and / or ST sections and / or QRS groups are also determined by corresponding tachograms in accordance with section a. shown on further parallel time axes. The PQV (ti), QTV (ti), STV (ti), for example, result in a corresponding manner on the basis of the corresponding derived time stamps within a respective heart action.

The efferent influences on the vasomotor system and its dynamics are represented in the form of the variability of the acute pulse wave propagation speed, whereby the relevant vascular events are determined in the temporal development of the respective PTTV (ti) by the corresponding derivation position of the relevant pulse sensor. placed vessel section manifest. The PTTV (ti) assigned to the relevant vessel sections are again determined in accordance with section a. represented tachographically on a relevant time axis.

- Certain temporal variabilities with regard to the hemodynamic determinants, which also characterize the dynamics and specific characteristics of the respective blood pressure curve, are also affected by the temporal development of the corresponding time intervals (e.g. pulse width of the systolic and / or dicrotic wave and / or duration of the

Diastole and / or time interval between the time of occurrence of the systole and dicrotic wave, etc.) represents and in a corresponding manner according to section a. represented tachographically on a relevant time axis. - Certain pulse shape variabilities in the respective pronounced blood pressure curve are on the one hand by the in section b. Values specified in more detail for certain reported blood pressure amplitudes and represented by the corresponding shape-specific parameters and characteristic values in their chronological course as a relevant time trace.

In addition, all the signals recorded in this regard (ECG, blood pressure curves) can also be displayed on other time axes synchronously in connection with the respective tachograms and the parameters and parameters derived therefrom.

Appropriate simultaneous and multichannel pulse train displays of all tachometric and parametric time series available due to the method provide the user with a corresponding overview of the current variabilities and fluctuations of multiple parameters, parameters and signals as well as theirs by displaying the respectively selected variants temporal development, which characterize the cardiovascular system behavior.

Certain clinically significant covariances, correlations and / or trend trends relating to the cardiovascular events can be determined from the various time-synchronized multiple time series and signal courses shown in parallel, and with the related various clinical interventions or circulatory ones

Relate stresses and / or directly to other additionally determined vital parameters and / or laboratory diagnostic data. This form of representation may in principle be suitable for many clinical applications, the variability and stability of the cardiac Circuit systems to be assessed using largely phenomenologically oriented evaluation processes.

Description of the designated meta-representations and analysis method according to steps 4,5,6:

In addition, further suitable meta-representations are created for separate representation of the dynamic development of cardiovascular system behavior in connection with the additional process parameters recorded synchronously with it, e.g. in the form of Lorenz plots, phase spaces, parameter spaces, trajectory plots, Poincare plots, etc. Suitable mapping processes (seif organization feature maps) known from system theory and nonlinear dynamics, which characterize the respective structural dynamic development.

Meta representations: characterize various state-dispersive variabilities and fluctuations with regard to certain specified multidimensional meta-representations, a corresponding state vector being formed on the basis of a plurality of determined state variables in an n-dimensional state space and / or by means of corresponding reconstruction methods an n-dimensional phase space and / or corresponding soap-organizing feature maps. (Numerous different variants are also possible here)

The assessment of implicit autonomous, complex, structural-dynamic regulatory relationships, on the other hand, can only be promised if the relevant cardiovascular complex, dynamic order states are appropriately prepared from the available measurement data and thus also made available for explicit exploration and analysis. These states of order manifest Ren thus in the form of appropriate ordering parameters and also have a certain specific dependence on certain physiological control parameters. This is done with the help of the different forms of meta-representations described below through n-dimensional state spaces or phase spaces on the basis of the measured time series, a corresponding flow being defined by the currently underlying dynamics, the properties of which are then followed by a Analysis can be examined. Appropriate meta-representation methods are required for this, which include the reconstruction of the trajectories or iterative sequences or attractors in an N-dimensionally embedded state space (phase space) and, if necessary, further additional display methods for generating so-called state portraits and projection to a correspondingly lower-dimensional diversity for the exploration of higher-dimensional state spaces by means of suitable projections or images and / or certain seif organization feature maps.

The use of all these meta-representation methods according to the invention is justified by the fact that the overall behavior of a complex system is fundamentally easier to observe and characterize than one of its parts, ie from the limited observation of a single physiological phenomenon, for example a selected signal curve or one HRV (ti) tachogram series shows the system behavior impenetrably complex. The representation with respect to a larger totality becomes a corresponding ensemble of data through the simultaneously determined multiple circulatory physiological determinants and its certain form of the multidimensional MetaRepresentation on the one hand significantly reduce the complexity for the observer and on the other hand it leaves the applicability of mathematical analysis methods for the characterization of structural dynamic system states and modes.

For step 4 and 5: Reconstruction procedures and optimization procedures for the reconstruction of meta representations

a. Lorenz plot representations:

Another meta-representation which results from the interval times described above, e.g. the HRZ (ti) or PTTV (ti) tachogram can be created using the so-called Lorenz plot. With this representation method, n consecutive interval times, n = 2,3, ... k are combined to form an n-dimensional state vector and its temporal development is continuously recorded in the course of the investigation. In the case of a two- or three-dimensional representation of the Lorenz plot, these state vectors mark corresponding points in the surface or in space. In the course of the temporal development of the state vectors, a distinction is made in the coordinate space shown! The formation of characteristic distributions, trajectories or attractors serves to characterize and identify the dynamic modes that have been passed through, as well as, among other things. to classify the type of system-specific dynamics and stability as well as to differentiate between periodic, quasi-periodic, stochastic, deterministic or chaotic system behavior. In this way, the corresponding Lorenz plots can be created from the assigned tachogram data sets available on the basis of the method.

In order to identify certain examination phases or significant episodes or to assign them to certain interventions or burdens, the relevant points of the Lorenz plot can be marked graphically or in color. b. arameters-space representations:

Another meta-representation, which can be summarized from the above-mentioned simultaneously recorded tachometric and / or parametric time series (e.g. several excellent blood pressure values or pressure differences and / or selected pulse shape parameters and selected interval times) to form an n-dimensional parameter vector. The parameter spaces can either be based on the absolute values of the relevant state variables or on correspondingly standardized relative values.

c. State space (phase space) representations:

Certain analysis methods for evaluating complex dynamic states are based on the investigation of the behavior of certain reconstructed circuit attractors, which are embedded in corresponding reconstructed n-dimensional phase spaces. The advantage of this analysis method lies in the fact that all relevant influences, which have a regulatory connection with the current circulatory situation, are also part of the related attractor in the phase space.

Basically, a variety of variants of the phase space reconstruction are also conceivable here. First of all, those variants are favored which are regarded as essential and relevant MetaRepresentations for the circulatory regulation and which are to be reconstructed on the basis of easy-to-determine cardiovascular size, for example from the ECG and pulse signals. If determined system behavior of the circuit is based on determined processes, the time profile of a single state variable can already contain all the essential information about the overall dynamics of the system, which is represented in a significant way with the help of a phase space reconstruction.

In general, two different methods of phase space reconstruction are possible, each of which is applied to the signal curve of a selected state variable (e.g. from a continuously derived ECG or pulse curve signal curve or using a continuous tachographic or parametric signal curve).

In the first reconstruction method, an n-dimensional phase space is spanned in that a coordinate contains the signal detected in each case, each further coordinate k = 2, 3,..., N each containing the corresponding k-1-fold differentiated signal.

In the second reconstruction method, correspondingly delayed signal values can also form an n-dimensional state vector. To do this, a certain delay time (Delay = τ) must be specified.

Since in the described embodiments of the method the analog sensor signals are subjected to a corresponding AD conversion, this leads to additional problems in the case of the first reconstruction method, particularly in the case of higher-dimensional reconstructions. These arise as a result of the discontinuities associated with a discrete sampling and the limited temporal resolution in connection with the required numerical multiple differentiations.

For this reason, the delay reconstruction method is preferred in this case. Delay RekonstruktJons method

This method therefore represents a key technology for the reconstruction of the N-dimensional state vectors from the measured time series. Since the measurement of all state variables of the examined cardiovascular system is practically impossible, the problem is that it is unclear a priori which measurement variables or the state variables that can be derived from it essentially describe the dynamics of the system. This problem is solved by designating, specifying and extracting the relevant state-relevant and metrologically accessible state variables after step 1, according to which the corresponding delay reconstructions can be carried out using these state variables. For the successful application of the reconstruction method, the choice of the underlying embedding window is extremely important, so that the reconstruction of the dynamics is made easier. This embedding window is determined on the one hand by the chosen embedding dimension D and by the delay time τ to be specified in each case, the respective reconstruction being able to take place either with correspondingly predetermined constant values for D or τ or for a specific constant product D x τ. Because a successful reconstruction also sensitive to the delay times used, e.g. Given the specified embedding dimension, and thus also the practical applicability of the entire process, certain process steps according to step 4 and corresponding criteria are also specified for the purpose of optimization.

In the delay reconstruction, a delay time τ is chosen so that the dynamics of the system are correlated in an optimal way. A suitable delay time τ is selected on the basis of empirical preliminary examinations, with several reconstructions for different delays τi being carried out with respect to the selected signal curve, the selection criterion being the optimal spreading of the attractor in the phase space (optimization of the state space filling) without it overfolding (optimization of the attractor topology) occurs. In principle, however, the dynamics of the system are independent of the type of representation. Accordingly, although coordinate transformations or variations in scaling have no influence on the dynamic properties of the resulting attractor, care should be taken when determining the dynamic variables that their properties are brought into a sufficient correlation. This is done by choosing a suitable delay time.

To reconstruct an attractor in the n-dimensional phase space, the state variables involved are obtained according to the following scheme: xl (t) = x (tl), x (t2), ...., x (tn) x2 (t) = x (tl + τ), x (t2 + τ), ...., x (tn) x3 (t) = x (tl + 2τ), x (t2 + 2τ),, x (tn + 2τ)

xN (t) = x (tl + (N-l) τ, x (t2 + (N-l) τ,, x (tn + (N-l) τ)

The state vector X at a time ti is thus defined as

X (ti, τ) = (x (ti), x (ti + τ), x (ti + 2τ), ...., x (ti + (Nl) τ)) In order to fully describe an N-dimensional state and its temporal development, these must exist in an N-dimensional phase space, which is characterized by its embedding dimension D = N.

In particular, N-dimensional phase space reconstructions are now carried out for the cardiac component from the EKG signal and for the vascular component from the pulse signal.

Correspondingly, phase space reconstructions from the tachometric and / or parametric time series and / or for corresponding correlations such as e.g. B. between HRV (ti) and PTTV (ti) - perform tachograms.

Accordingly, e.g. a related tachometric phase space reconstruction after the described time offset embedding (delay reconstruction). In this way, n curve curves can be obtained from a single tachogram curve, which are shifted relative to one another with a delay (delay = τ). Accordingly, a state vector Xti, τ can be determined at a predetermined occurrence interval ti:

Xti, τ = (x (ti), x (ti + τ), x (ti + 2τ), K, x (ti + (n-l) τ))

Each corresponding vector thus defines a spatial point in a correspondingly dimensioned phase space.

If, in the case of the cardiovascular dynamics examined with the method, there is a complexly determined regulatory behavior, then the spatial points that are constituted in the course of the process do not fill the entire phase space (as in the case of purely stochastic behavior), but instead form corresponding sub-characteristics that characterize the dynamic structure. Manifolds that represent the currently prevailing structural dynamics. Using the analytical methods described in more detail in section 0, certain structural dynamic states and changes in state can be observed identified and assessed in terms of their relevance to the circulatory diagnosis.

In principle, any high-dimensional embedding dimensions can be selected with the help of the phase space reconstruction method described. As the knowledge of the invention shows, the practically cheapest selection of an embedding dimension that is particularly suitable in terms of the determination of structural features results from investigations of the correlation dimension analysis described under the analysis methods, or Lyapune exponents and their dependence on the embedding dimension used in each case. These investigations, which were carried out from N = 3 up to a 40-dimensional embedding, showed that significant changes in state were mostly recognizable with a chosen embedding dimension of more than 10.

With regard to the optimization of τ or D, the designated attractor-based optimization methods stand out so that when an attractor is embedded in the state space, its a. static properties (topology, geometry) are optimally represented.

The method for volume maximization evaluates the empirical observation that if the τ is too small, the reconstructed attractor collapses (eg in the form of an elongated hyperellipsoid), while if the τ is too large, the structure expands until it resembles a hypercube. In addition, other evaluation criteria can also be used advantageously, such as determining the fill factor or the reconstructed signal strength (RSS). The first maximum This evaluation function as a function of τ then corresponds to an optimal τ.

Methods for optimizing embedding that use the principle of topology preservation can also be used advantageously. In the ideal case of noise-free and arbitrarily long time series, the topology of the original attractor is retained, from which another topologically justified criterion can be derived. If the embedding is sufficient, the neighborhood relationships of the attractors remain unchanged (invariance) if the embedding dimension is increased. If the embedding is insufficient, the topology can change. Such topology changes can be detected in the sense of the method using the Wabern product or using the method of the wrong neighbors. Based on the attractor-based optimization process, optimal pairs for D, τ can be determined.

Furthermore, b. Dynamics-based optimization methods are advantageously used, whereby those dynamic properties are used which characterize the temporal course of the trajectory movement in the state space. The principle of this form of optimization uses the deterministic character of the dynamics on which an attribute is based. For this purpose, the order of magnitude of the Lyapunov exponent λ is used as a reliable criterion. This condition is met if the flows in the state space show only a small divergence, i.e. for not too large λ.

Step 6: Representation procedure and state projections

In order to arrive at a suitable graphical representation of higher dimensionally embedded (N greater than 3), which enables a direct inspection and exploration of the respective Appropriate methods for dimension reduction are used because the generated topology of the attractor or the temporal course of a specific current trajectory development and the formation of attractors are to be made possible.

These are described as:

a. State projections (state portrait) of higher-dimensional attractors on a 2D or 3D manifold. The points of the attractor are projected through a 2D surface, whereby the dot product of a point is formed with two unit vectors that span the plane. The two results of this product formation result in the coordinates in the plane by which the point in the state space is represented.

b. Isoshell projections: A 2D representation of the attractor can generally be generated with any pair of functionals defined on the state space. The special choice of such a function is the distance to a reference point on the trajectory. With such a choice, all points from a hyper-spherical shell around the reference point are assigned the same value (isoshell projection).

Poincare cuts: This relates to a further method for reducing the flows to be represented in the state space by temporal discretization. Scanning the flow as it penetrates a hypersurface in the state space leads to a dimension reduction by one dimension. The resulting cuts are called Poincare cuts

d. Recurrence mapping: This display procedure is suitable for checking the constancy of the control parameters in the time series. The starting point of this display method is the property of the attractors that a trajectory in the state space always gets into an ε environment of a reference point (recurrence) in the course of the temporal development. The prerequisite for this is that the reference point belongs to the attractor against which the dynamic converges. The method is to be used advantageously if it is to be used to assess periodic and non-stationary behavior, such as for identifying certain circulatory physiological conditions and changes in condition. A special feature can be obtained from the fact that, in the case of periodic regulation behavior, corresponding line structures are generated in the recurrence image, which are parallel to the diagonal. The current period can be easily determined using these equidistant lines. In the case of a transition to non-stationary behavior, there are significant densifications of these lines around the diagonal. By inspecting the changes that occur in this figure, mode changes (phase transitions) can be identified particularly easily.

In all under a. to d. In addition, suitable graphic or color coding methods can advantageously be used for the identification and marking of certain phases or episodes in the course of continuous circuit monitoring. , Other non-dynamic representation methods: In addition, the dynamic can be mentioned

Representations additionally advantageously use the known statistical methods with corresponding representation methods, such as, for example, analyzing the frequency distributions for the corresponding times of occurrence with regard to the derived time series using appropriate methods Histogram displays e.g. HRV (ti), TTV (ti) histogram and much more.

For steps 7 and 8: Analysis procedure:

This includes the analysis procedures for obtaining suitable significant and representative structural dynamic measures and fluctuation measures regarding changed attractor positional relationships for clinical use in circulatory diagnostics and monitoring.

Conceptual background of the claimed analytical methods

The previously known methods for in vivo diagnosis and monitoring of circulatory functions are essentially based on a phenomenological evaluation of explicitly accessible vital parameters in connection with corresponding statistical analysis methods such as e.g. from the normal ECG and blood pressure data. However, a systemic assessment of the implicitly complex autonomous regulatory processes and their adaptive and complexly networked physiological system relationships is not possible. In order to create the appropriate prerequisites for a method that is suitable with regard to the mapping and differentiation of current dynamic circulatory states, the relevant measurement data are appropriately prepared and represented. The analysis methods described below are therefore based on these corresponding and previously reconstructed representations or meta representations. Based on this high dimensional

State vectors and the temporal development of the respective trajectory courses and attractor orbitals are then used to obtain clinically relevant systemic structural dynamic features or characteristic values such as the current level of structuring and / or certain complexity measures and / or certain dynamic stability features and / or certain parameters or features for monitoring the course of certain attractiveness properties.

The particular advantage of all of these claimed analytical methods can be seen in the fact that empirically generalizable system-specific statements about the collective cooperative procedural system behavior can be obtained without knowledge of all the physiological subsystems involved and their interaction having to be assumed , The object of the analysis methods is therefore: the measurement of states of the circulatory regulation in the phase space to obtain statements about the spatiotemporal relationships of the attractor orbitals to one another, the analysis of metric relationships in the phase space to identify a measure derived therefrom for monitoring the long-term development of circulatory states , These include in particular: a. the determination of the correlation dimension, b. the determination of the Lyapunov exponent or the Kolmogorow entropy or the localized Lyapunov exponent c. the position vector course d. the attractor location - tiling area, which is determined either individually or in connection with the implementation of the analysis method, whereby - the determination of the correlation dimension is used as a significant characteristic value for assessing structurally dynamic order parameters depending on the respectively given (selected) embedding dimension, and the determination of the Lyapunov exponents (exponential divergence) as a significant characteristic value, depending on the chosen embedding dimension, is used to assess the course of development of the acutely predictive dynamic complexity of the cardiovascular system, and the determination of the attractor location tiling area as a suitable structural measure is used to track the development of the attractor, and the determination of the mean squares of successive differences of the relevant interval time variabilities is advantageously used to identify and monitor the acute dynamic fluctuations and the stability of the circulation.

The above Analysis methods can also be correlated with other physiological parameters and laboratory values: such as Correlation with the heart rate, blood volume or flow, serum sodium values, as well as other circulatory load parameters and / or certain physiological control parameters for diagnosis and monitoring of the dependencies of the circulatory regulation on specified endogenous or exogenous pressures as well as the determination and estimation of regulatory or deregulatory loads Areas or of compensatory or decompensatory episodes are advantageously used.

a. Correlation dimension analysis:

A means of analyzing the attractors

Orbitals represent the determination of their dimension. The acutely prevailing or changing regulatory activities can, for example, occur during a transient phase significantly reduce the number of variables that determine the respective embedding dimension. The determination of the current dimension taken up by a system in the phase space is therefore suitable to provide a significant measure for the dynamic modes involved and their transitions. This is particularly advantageous since the dimension of an attractor has a property that is invariant to changes in scale and therefore the representation and representation that is practically selected in each case has no influence on the dynamics of the system. The following dimension variants from the theory of complex dynamics are now known to the person skilled in the art in this area: capacity and Hausdorff dimension, information dimension, correlation dimension. In principle, these and other future variants can be used in the sense of the method for dimension analysis. In the embodiments shown here, the correlation dimension was initially used. This dimension definition is based on the correlation sum, which indicates the probability with which the distance between two arbitrarily selected trajectory points is less than r. Since the calculation of the correlation sum is associated with a greater computational effort, a simplified and efficient algorithm according to Grassberger and Procaccia is used in this case to calculate the correlation dimension.

b. Lyapunov exponent

The Lyapunov exponent (λ) is a further measure of the stability behavior of the trajectories of the dynamic system of circulatory regulation examined. When determining λ, the exponentially divergent behavior of neighboring trajectories in the phase space is used. This method thus allows statements about the trajectories to one another, the respective dynamics of the tion based on the degree of its exponential divergence and can be classified accordingly, from which clinically relevant criteria regarding the dynamic stability of the circulatory system can be derived. In the theoretical dynamics of nonlinear systems, λ can be determined from the equations of motion of the dynamics. In the case of physiological measured values, there is the difficulty that the system-defining differential equations are in principle unknown. The calculation proposed by A. Wolf (Lit.) for pure time series is therefore used to determine λ on the basis of the time series measured in each case.

c. Position vector history

The determination of the attractor position on the basis of the location vectors of the trajectories has the advantage that even in the case of high-dimensional attractors, which in principle elude direct graphical representation through three-dimensional spatial representations, a course observation of significant changes in the attractor development in connection with changing regulatory Episodes based on a single scalar parameter in the form of the amount of the location vector is made possible. In the case of an embodiment, the time profile of the location vector is advantageously used for continuous circuit monitoring or for load analysis.

A time offset embedding with n> 3 results in multi-dimensional points that cannot be clearly depicted in order to identify and evaluate possible clinically relevant features. Therefore, a dimension reduction must be carried out in order to make an image of the attractor development clear. This can be done indirectly via the location of the current trajectory of the attractor via his location vector current trajectory of the attractor can be reached via its location vector.

FIG. 2 shows the determination of the position of the trajectory based on the current location vector.

A change in the attractor position of a chronologically developing sequence of points in space can be produced in one course on the basis of the amounts of the location vectors from the time offset embedding.

d. Attraktorlage-Parkettierungsflache

To obtain a relative measure of interaction e.g. With respect to the correspondingly selected interval times to one another, parqueting can be determined over a defined number of interval times in the phase space and its area determination by polygon summation. This can provide information about the extent of a particular attractor. Here mark e.g. smaller area dimensions determine stabilizing events. With this method, at least three consecutive interval times in a phase space, state space or parameter space are considered and the enclosed area is calculated.

FIG. 3 shows the determination of the enclosed area of successive interval times in a phase space.

In FIG. 4, this method is applied to a recorded tachogram. 50 consecutive interval times were used to determine an occupied area in the feature space. Step 8: Analysis of the correlating time series of mean squares of successive differences (MQSD)

Since the course of a tachogram expresses the regulatory behavior of the circulatory processes, the MQSD for process variability or fluctuation can be inferred from this derived measure of regulatory activities. These can be described on the basis of a "fluctuation measure". Here, a defined number of interval times in a window are evaluated with regard to their quadratic changes. It has been found that the mean quadratic change magnitudes with respect to every second interval stand out particularly clearly In this case the time offset is τ = 2.

FIG. 5 shows the course of the middle squares of successive differences in changes in interval times.

Strongly filled curve areas indicate increased regulatory activity. This activity becomes clear when you look at the changes in the curve after applying a differentiation.

FIG. 6 shows changes in the middle squares of successive differences between changes in interval times with respect to RR and PTT tachograms shown.

In addition, it is conceivable to use the known time series, for analysis purposes with regard to the temporal dynamics or the dynamics change, to use further known or future propagated complexity measures, such as the determination of different variants of the algorithmic complexity, with such a measure then relating successively each predetermined time sequences and on the basis of the Time series of generated and encoded strings can be determined.

In addition, it is also conceivable that correspondingly assigned feature vectors are created on the basis of the time series for certain excellent episodes, which, after a certain classification and / or representation in a relevant feature space in the course of the time series development, are also assigned to the respective states which are thereby distinguished ,

Step 9: Analysis of the control parameter dependency

The physiological control parameters that are explicitly ascertainable and characterized by the claimed method, which act in the sense of nonlinear dynamics in connection with autonomous self-organization and the manifesting order parameters or dynamic modes of the cardiovascular system, are described in the Be - specifically identified by a. the heart rate, b. mean blood pressure, c. the cardiac output, d. stroke volume, e. certain volume flow rates, f. Volume inflow or outflow, g. certain ergometric work or performance parameters

This under a. to f. Designated control parameters can be recorded and quantified with the help of certain suitable sensors and measuring methods, so that the absolute values or relative values determined for the control parameters with the representations and / or meta presentations obtained from the previous method steps 1 to 8 and / or the derived parameters which relate the relevant ones Characterize cardiovascular conditions, be correlated accordingly. On the one hand, by using the method, certain separate tests can be carried out to determine averaging of such correlations are carried out, for example the dependency of the respectively passed through attractor orbitals and / or the correlation dimension and / or the Lyapunov exponent are inter alia associated with the correspondingly assigned values for the respective control parameters such as the heart rate. For this purpose, it is advantageous if specific values for the control parameter can now be specifically taken by the examined individual for a specific examination period and can be kept largely constant over this time, the modes assigned to the control parameters being able to stabilize accordingly. In most cases, this can be achieved through certain controlled measures or interventions. In the case of the heart rate selected as an example as a specific control parameter, a controlled setting of the heart rates to be achieved in each case can be induced either by certain physical loads (for example ergometry) or by certain pharmacological interventions. When carrying out these correlation studies, the results as a result of the overall progress and, on the other hand, those individually significant and characteristic values of the control parameter in question can be determined, each of which characterizes the individually significant transitions of the dynamic structure formation and which thus also include other novel and clinically relevant patient-specific parameters a far-reaching future diagnostic potential.

For this purpose, different forms of representation are again conceivable for the respectively suitable graphic representation, which allow an adequate overview with regard to the formation of certain excellent structural circulation modes with certain excellent values for the control parameter. A special form of graphic visualization can consist, among other things, in that the course of the various characteristic values ascertained by the relevant analysis, such as for the correlation dimension values, Lyapunov exponents, location vectors and others, is plotted individually or in conjunction as assigned ordinate values against the control parameter values as abscissa values become. From such a visualized representation, on the one hand, the structural dynamic characteristics and covariances that occur in this regard can be recognized directly, which, among other things, also allows the accuracy of the analysis carried out to be checked. On the other hand, the mode changes occurring in the case of characteristic values of the control parameter in the form of abrupt changes in the characteristic values (phase transitions) can easily be determined and marked accordingly or tabulated as corresponding assigned value pairs. These patient-specific significant critical values for the respective control parameters characterize in a similar way, such as the Reynolds number known from flow dynamics, certain transitions in the structural dynamic behavior of the autonomous circuit-specific regulation mechanisms.

As examinations undertaken in this regard by the invention show that in the selected case of the heart rate as a control parameter, in cardiac and circulatory healthy subjects, at first low heart rates up to approx. 100 bpm, a constant and covariant dependency of all relevant characteristic values characterizing the order parameters was found - len, whereas with increasing heart rate above 100 bpm, in each case patient-related, significant sudden and covariant changes occurred with several and certain excellent values for the heart rate. On the other hand, in the course of a clinical course observation or monitoring, the simultaneous determination and display of the prevailing control parameter values can also take place synchronously with the respective acute circulatory conditions represented in parallel and represented in the aforementioned manner and can advantageously be used to expand and specify the diagnostic statements.

As the knowledge of the invention shows, pronounced and individually significant sudden covariant changes in the correlation dimension and the Lyapunov exponent are e.g. recognizable in terms of myocardial excitation processes at the same certain excellent characteristic heart rates.

Investigation procedure on the open circuit and correlations with the volume-specific control parameters:

In contrast to the previously described applications of the method, which are generally related to isovolemic conditions, ie in a closed circulatory system, a specific use case under the different conditions of an open circulatory system will now be described as an example (see use case p. 23, line 22, section b.) Since controllable and usually also quantifiable both hypervolemic and hypo-volemic circulatory situations can occur in connection with an invasively opened circuit, the inflowing or outflowing volume or the corresponding volume- flow (+ dV / dt = inflow, or -dV / dt = outflow), whereby these control parameter sizes are additionally determined with the aid of certain known volumetric methods and in addition to the analysis determined from method steps 1 to 8 lysis results in the form of the designated representations, meta-representations or parameters are brought into direct relationship. The currently prevailing flow can be shown quantitatively either by its absolute values or relative values or in the form of discrete heart rate-related volumes.

At least two time-synchronous time series can be regarded as advantageous forms of representation for continuous circuit monitoring, which on the one hand represent certain characteristic scalar parameters for the order parameters as related ordinate values, such as the location vector, the tiling area or the MQSD parameter, and the related flow size. ß control parameters included as abscissa values. This means that volemic loads and their immediate effects on acute regulation or Observe the compensation performance of the circuit directly. As preliminary investigations by the invention already show, the location vector course of the PTT attractor as well as the HR attractor shows a constant covariant development under a 30-dimensional embedding dimension in correlation with the volume-related control parameter idF of the outflow with a continuous approx. Eight-minute blood draw of a total of 5ooml in connection with the controlled hypovolemic circulatory load specified thereby. Likewise, the volume-dependent development of the attractor in the relevant state space projections and the derived values (correlation dimension, Lyapunov exponent etc.) show a coherent behavior, whereby in this case again characteristic, clearly distinguishable and classifiable changes in the structural dynamic states are observed at certain volume or flow values, which can clearly be associated with certain phases of the regulatory episodes.

While under the clinical condition that the volume inflows (outflows) are in principle measurable and also controllable, and thus the designated correlations of the circulatory-specific order parameters with the volume-specific control parameters can basically be determined, in the other ge - stored clinical cases in which the occurrence of in principle uncontrollable or difficult to estimate occult volume flows, such as in the case of acute blood loss (outflow) or in the event of liquid flooding (inflow), (see p. 22 section a)) the question of the applicability of the claimed method with regard to risk monitoring and rapid in vivo detection of irregular, destabilized, decompensatory or critical Cardiovascular conditions in connection with the acquisition of objective and significant diagnostic and prognostic criteria. Basically, the sole use of the analytical results according to the method, even without an additional correlation with the volume-specific control parameters, offers sufficient diagnostic potential. For certain clinical requirements, however, a combined application and inclusion of further additional diagnostic strategies is also conceivable.

TUR problem and application example of the procedure:

In the case of a clinical application example with regard to the possible and largely uncontrollable flushing of a certain portion of a rinsing solution into the bloodstream, which can lead to serious complications (TUR syndrome) in connection with certain endoscopic interventions, the method can be done both used individually or in combination with so-called accounting procedures for assessment successfully for risk monitoring and for deriving certain termination criteria.

While the known methods attempt to calculate critical amounts of substance as a criterion for risk assessment or based solely on the assessment of the amount of rinsing solution remaining in the body circulation or the absorbed portion of the rinsing solution with the help of balancing weighing methods or with the help of a specific indicator method (e.g. breath alcohol method) On the basis of termination of the operation, it seems questionable whether a reliable risk assessment can be achieved in principle. The known methods are therefore subject to the fundamental disadvantage, which is more likely to result from the underlying approach. According to this, it appears to be barely promising because, due to the extremely high level of complexity, adaptability and plasticity of the autonomous circulatory processes, it can practically be assumed that even the same flushed volume, depending on the currently prevailing circulatory status, is individually as well as interindividually one can represent very different and extremely variable stress for the cardiovascular system. Due to the complex dependency on the respective physiological or pathophysiological conditions, this will affect the acute or postoperative clinical symptoms and their consequences in completely different ways.

In addition, the large number of different cardiovascular complications that occur acute or postoperatively in TUR syndrome cannot be unambiguously and monocausally linked to the individually determined hypervolemic load or the amount of substance absorbed or absorbed (fluid overload). This is also due to the different metabolism and the associated varying time constants and delayed action, as well as due to the different elimination times of the flushing solution and the complex dependence on the patient-specific cardiovascular and kidney function. A sufficiently clinically meaningful assessment of whether and to what degree the flushed flush solution is actually compensated for by the individual functional regulatory services of the patient's circulatory system in acute cases is not possible even if the volume of the fluid or the fluid overload is known. In summary, the system-related conceptual problems that must be taken into account when solving the problem can be characterized by the fact that, due to the complex, adaptive and often networked regulatory and dynamic relationships between the volume flow and the acute prevailing hemodynamic and pharmacokinetic interactions, as well as the changing metabolism and elimination conditions, as well as the individual spectrum of possible TUR complications, it therefore seems impossible from these volumetric data alone to obtain meaningful clinical parameters for the assessment of the multiple risks. This would also be hopeless in principle, provided that the current inflow or the currently absorbed volume of the flushing solution is determined precisely and continuously. The specific patient risk, however, depends on the often effectively interconnected, individually effective and available compensation services in the acute circulatory situation due to the diverse dynamic regulatory mechanisms of the circulatory system (such as the overarching, central, local regulatory mechanisms and organ functions), as well as from the currently initiated clinical measures and interventions (e.g. forced diuresis).

The task of effective and TUR risk monitoring is achieved by using the claimed method and by the corresponding device. In contrast to the known methods, which are aimed at the acquisition of substance-specific parameters and volume-related criteria for the identification of critical loads, the claimed method is based primarily on the dynamic aspect of the autonomous body's own regulation processes. The claimed method advantageously uses the complex performance of these diverse and networked physiological mechanisms, e.g. the large number of highly specific endogenous circulatory sensors (e.g. the afferents of the baro, volume or stretch receptors, etc.) as well as the performance of the central and vegetative nervous system, as well as their efferent interdependencies. In addition, the property of the convergence of the cardiovascular system behavior to only a few physiologically relevant, but highly significant and easily measurable efferent effects is advantageously used in the sense of the method.

Likewise, a certain circumstance with regard to the

Method and thus determined physiological measurement variables, advantageously used for analysis or diagnosis purposes, in which the complex dynamics of the reflex-regulated cardiovascular events in the determined measured time series are encoded accordingly, and the attractors reconstructed therefrom with the help of the method in the relevant ones State spaces represent these comprehensively, which means that the circulatory dynamics can be adequately described. When the TUR risk monitoring method is used clinically, additional additional results from corresponding preoperative examinations can be used for reference purposes with regard to the operative and / or postoperative course. A combined application in connection with additional accounting procedures and / or the inclusion of further vital parameters, laboratory values or other references (such as the measurement of the serum sodium values recognized as the current gold standard) is also conceivable.

For step 10: assignment of the properties and characteristics of the analysis results to physiological properties and findings

The properties and characteristics of the analysis results determined with the previous steps are characterized in that the properties and the course of the temporal development of complex dynamic order states, as well as their direct connection with certain system-specific control parameters, are determined during the analysis and these properties provide certain characteristics which are used for Characterization of the dynamic quality of the autonomous physiological regulatory behavior of the human or animal cardiovascular system can be used, in particular the changes in these characteristics under the influence of various multiple exogenous or endogenous loads, and certain specified and quantified control parameters are determined from these loads, and being from the

Results of the relevant correlations with regard to the control parameters to the analysis results, and furthermore certain characteristic values for the relevant control parameters are determined, which according to step 9 show the individually significant transitions of the related parameters. naming structure formation and its dynamic stability, and

-that the assignment of these features, which characterize the dynamic quality, to corresponding properties, which represent and characterize the corresponding physiological or pathophysiological functions and their related properties, is done by using further clinical or experimental data material as a corresponding reference, whereby the previously phenomenologically oriented findings are objectified and quantified accordingly on the basis of the assignment to the analysis results, and from which completely new corresponding clinically relevant functional parameters, parameters and diagnostic criteria are derived, in particular that such an assignment and reference (as external and Self-reference) through the targeted intervention, stimulation or provocation to achieve certain physiological effects through the use of appropriate methods and means for process interaction on happens, in particular through a targeted provocation of the baroreflex, e.g. under controlled orthostatic stress (tilting table, Schellong test) and / or by intra-abdominal pressure increase (Valsalva maneuver) and / or by thermal stimulation (cold pressure test) and / or by pharmacological intervention (phenylephrine method), among others, which if necessary, can also be carried out as a corresponding preliminary examination, for example before the actual monitoring task, and

-that the test results obtained with such preliminary examinations can serve as an operational function test for the operational readiness of the method. Further assignments in this regard are also due to future clinical and theoretical investigations expect and can then be used advantageously in terms of an expanded applicability of the method. The claimed method, on the other hand, creates the technical and methodological prerequisites that can be used to open up a completely new, clinically relevant field of investigation with far-reaching future application potential, although currently no fully physiologically interpretable insights into the achievable with the method Analysis results exist. For further future experimental investigations with the aid of the claimed method, it is advantageous if these are linked to corresponding model simulations on the basis of the designated measurement data.

The proposed method can also be summarized as follows:

Process for evaluating and in vivo detection of the dynamic quality of an autonomous regulatory behavior of the heart and / or the cardiovascular system of a human or animal body, in particular for the identification and differentiation of complex dynamic cardiovascular states and / or state changes with regard to the pathological or regular behavior and / or with regard to the effects of various types of multiple and changing loads and to obtain objective and quantitative functional parameters, parameters, features and differentiation criteria that characterize the relevant conditions and / or effects for use in clinical functional diagnostics, monitoring and therapy control, with the steps:

a) Identification and specification of the physiological order parameters and control parameters with regard to the pro- cessual regulatory properties, in particular the acquisition of externally accessible process information and / or the achievement of controllable process interactions with regard to the structure-dynamic complex modes in the second mode change;

b) detection of the corresponding physiological output signals and control parameters emanating from the autonomic cardiovascular activity, which contain the dynamic quality of the autonomous reflex or regulatory activity and / or the regulatory performance on the various effect organs;

c) empirical generalization of the measurement data by preparing and summarizing process parameters which are evaluated from at least one of the continuously recorded signal profiles of the physiological output signals and / or the control parameters to form a larger set of empirical data with regard to their successive temporal development, in particular at one time structured and synchronized ensemble of state vectors, which form corresponding state sectors, for the purpose of a generalized representation and description of the dynamic development of the current system states characterized thereby and the various process variables acting on these states and / or for the abstract description and mathematical analysis of the autonomous regulatory behavior the cardiovascular system and / or to extend the applicability of methods for signal exploration using the abstraction with this n reduced complexity,

d) the interaction with the cardiovascular system through targeted actions by means of stimulation, provocation and / or intervention to trigger certain physiological effects, in particular by using physical and / or pharmacological means and strategies for parametric variation of the control parameters,

e) Assignment of the empirical process-related physiological properties of the cardiovascular system as well as the prepared physiological output signals, process parameters, state variables and control parameters for abstract mathematical representation, description and modulation, which sufficiently include the properties of the autonomous regulatory processes and their temporal development with regard to the dynamics and generalize, especially regarding their relationship to complex systems theory and nonlinear dynamics;

f) Representation of one or more physiological output signals and control parameters combined to form a larger group with regard to at least one abstract property containing and characterizing the underlying dynamics for their generalized mathematical description and for subsequent analysis, with regard to the characterization of structural dynamic system properties and / or system states or dynamic Modes, in particular through correlating time series and / or through multidimensional state or feature vectors and / or through reconstructed multidimensionally embedded state space representations and / or state space maps and / or through end-coded character strings;

g) evaluating the quality of various alternative state space reconstructions on the basis of the same existing time series, with regard to the selection and optimization of the suitable embedding window, in particular with regard to the choice of the embedding dimension required and / or the delay time, h) Analysis of the time series and / or the flows in the state space and / or the character strings with regard to the properties of the underlying dynamics, in particular the measurement of correlating time series and / or the topological trajectory relationships (metric) and / or dynamics of the attractor development and / or the determination of the prevailing degree of complexity,

i) determining and determining significant parameters and / or dimensions which characterize the predominant dynamic structure and / or the stability and / or the degree of order and / or the complexity;

j) determining the control parameter dependency of different representations and / or parameters with regard to different control parameters,

k) Classification and assignment of the abstract properties, characteristics and determined in the analysis results

Parameters relating to the dynamic quality of the empirical physiological or pathophysiologically relevant clinical findings, which represent at least one condition of the cardiovascular system and / or a regulatory and / or compensatory functionality.

The invention is further explained with reference to the drawing of Figure 1. FIG. 1 relates to a basic structure for carrying out the method for diagnosing and / or monitoring the cardiovascular system of a living being.

FIG. 1 shows a patient 1, to whose arm 10 a blood pressure measuring system 3 is connected. At the blood pressure measuring system is a beat to beat measuring system in which the blood pressure can be determined continuously. A pneumatic blood pressure cuff, which is used to calibrate the tonometry sensor of the beat to beat blood pressure measurement system, is attached to the left upper arm above the brachial artery. The radial artery is palpatorically located on the same arm to which this blood pressure cuff is attached and the tonometry sensor is fixed above it.

The ECG system 2 is connected to the patient 1 in the usual way to the thorax 11.

Both the EKG system 2 and the blood pressure measurement system 3 are designed in such a way that a continuous determination of measurement data is possible. The measurement data of the EKG 20 and the measurement data of the blood pressure measurement system 30 are sent to a corresponding amplifier device 4 and then digitized via an A / D converter. The A / D converter is arranged in a measuring computer 5, for example. The measurement data acquisition is carried out completely synchronously for the ECG and the blood pressure measurement, so that measurement data samples for both parameters are always available at the same time.

This measurement data measured continuously and in a time-resolved manner

20, 30 are then subjected to an evaluation process 6 in a computing unit 5. The evaluation process has already been described in detail in the text above, so that it will not be dealt with further here. From the measurement data evaluated in the evaluation process 6, a representation of the evaluated measurement data, which can be displayed, for example, for the doctor or surgeon, is then created. The representation of the respective time series in the parameter space and / or the phase space or an serve another representation. The respective doctor can then interpret such a representation and draw the necessary conclusions from it. In a further development, the automatically interpreted result can also be displayed on the screen.

From the measurement computer 5, the measurement data determined are subjected, for example, to an algorithmic evaluation of the measurement data acquired. The algorithmic evaluation comprises at least one determination means 6a for the automatic determination of at least one time-resolved baro-reflex response of the patient 1 from the measurement data, at least one acquisition means 6b for the automatic acquisition of at least one time series from the determined time-resolved baro reflex responses, at least one evaluation means 6c Evaluation of the temporal behavior of the at least one time series and at least one allocation means 6d for automatically assigning the temporal behavior of the at least one time series of the measured values to physiological properties and characteristics of the patient 1.

In a variant of the system (not shown here) for carrying out the method for diagnosing and / or monitoring the cardiovascular system of a living being, a further beat to beat blood pressure measuring system can be used instead of the EKG system. This second beat to beat blood pressure measurement system is then attached to a different distal position of the patient's body than the first blood pressure measurement system. In particular, a first measurement on the arm and a second measurement on the leg of the respective patient can be carried out. Here, too, it is important that the two measurement signals are recorded completely synchronously.

FIG. 1A shows an alternative embodiment which essentially corresponds to that in FIG. 1, so that Reference is made to the corresponding description. Input parameters for patient 1 and for measurement technology computer 5 are provided here.

The synoptic representation in FIG. 7 is given for the purpose of a better overview. In the graphic representation, the parameters determined in the sense of the invention are specified and placed in a larger context in this regard. In addition, the essential process steps and the results that can be achieved are summarized in a generalized form. The use cases described in more detail and other conceivable possible uses of the invention can then also be assigned.

In terms of a generalization, the procedural dynamic parameters, which characterize the autonomous mechanisms of cardiovascular regulation, are first differentiated into two groups from a system-theoretical point of view. One group designates and specifies all status variables and order parameters used in this context, while the other group lists the control parameters that are assigned and specifically identified.

Here, the state variables and / or order parameters are specified by the cardiovascular parameters determined in each case, which a, the autonomous or reflective myocardial excitation processes, b. the hemodynamically effective autonomous or reflex regulatory processes and c. characterize the vascularly effective autonomous or reflexive regulatory processes (local regulation). These are specified in connection with the use cases described below.

All control parameters in the sense of the invention are is aimed at understanding the cardiovascular system of a living being or the stresses exerted on the body as well as certain interventions and / or the correspondingly quantified work or performance turnover applied by the living being itself. In detail, these are

a. specified by certain volumetric loads. This also includes the different conditions of hypervolaemic (+ indicates the inflow) and hypovolemic (- indicates the outflow) stress. These include all relevant volume values and flow values as well as their temporal profiles V (t), dV (t) / dt, V ((N) / beat.

b. Furthermore, certain pharmaceuticals supplied to the body are specified as corresponding pharmacological interventions by quantifying both the different dose parameters and the application conditions relevant for pharmacokinetics. This includes all related dose values and dose rates such as Single dose ED, daily dose TD, effective dose ED 50 and dose course D (t) or dose rate dD (t) / dt or heart rate-related doses D (t) / beat.

c. The ergometric values are to be understood as all those physical stresses which the body applies itself. The sales achieved here are thus quantified by the corresponding amounts of work or benefits and / or by their temporal profiles W (t), P (t). Furthermore, those working or

Performance-related heart rates of an individual are specified, which arise in connection with the regulatory effects and as a result of a targeted and quantified physical load, in particular their temporal development HR (W, t) or HR (P, t). d. Another category of the load variables is to be understood as all those conditions which are suitable for specifically influencing the regulatory system behavior either with the aid of certain stimulation or provocation methods. For this purpose, certain orthostatic loads on the cardiovascular system can be brought about by corresponding changes in the body position, for example, with the aid of a tilting table, these changes in position being specified by the values for the respective tilt angle relative to the orthostasis position. Likewise, the derived variables for the angular velocity or angular acceleration can also be quantified either for a predetermined tilting process and / or in connection with variable orthostasis loads.

Another form of provocation of certain regulatory reflex reactions (e.g. the baro reflex) is the so-called Valsalva maneuver. The expiratory pressure exerted by the individual, e.g. against a fixed or variable resistance is specified by the relevant pressure values or their temporal course and / or by corresponding derived values.

With the so-called cold compressor test, a targeted thermoregulatory reaction of the cardiovascular system can also be brought about. To quantify the temperature stimuli used in this regard, the correspondingly suitable thermodynamic parameters can be used, which characterize the thermal stimulation.

As the synopsis in FIG. 7 also shows, all parameter values used and correspondingly determined for the respective application are combined into corresponding ensembles. quantified and included in the further processing. Corresponding parallel time series are formed on the one hand from these simultaneously and synchronously collected data, and on the other hand these serve as the basis for the process-related execution of the related links, correlations, analyzes and representations which are required to achieve the various results according to the invention. Thus the lower part of the synopsis also contains a compilation of some conceivable options with regard to different parameters or meta representations.

In the following, two selected application examples are described in their respective embodiment used.

Use case (monitoring of hypovolaemic loads when donating blood)

To obtain volume-related control parameters, the method contains suitable measuring devices for continuous volumetric data acquisition during the course of a blood donation.

As a result, the amount of the donated blood volume V (t) and / or the related outflow dV (t) / dt is recorded continuously and in synchronism with the other cardiovascular parameters. From this, the donated blood volume change per heart action V (N) / beat is determined by appropriate determination means.

To obtain certain cardiovascular condition parameters and / or order parameters

(i) the corresponding parameters characterizing the myocardial excitation are determined from the EKG leads recorded at the same time as the volumetric measurement variables with the highest possible resolution and sampling rate, different lead types and lead positions for the ECG signals Application come. These ECG signals, which are continuously recorded during the course of blood donation, on the one hand become the occurrence times of the P, Q, R, S, and T signal components for each individual ECG complex by using appropriate trigger and timing methods (Determination means), such as the windowed maximum detection, slope threshold method, etc. determined with an accuracy of 0.1 ms (time jitter). Furthermore, the RR time intervals regarding the times of occurrence of the R-waves for successive cardiac actions in each case and shown as a tachographic (RR tachogram) time series in synchronism with the other time series. The regulatory-related significant time differences of successive RR intervals thus characterize the heart rate variability ITRV (t) and represent the complex dynamics of the autonomous regulatory processes in the form of chronological RRtachographic time series.

(ii) As a further measurement characterizing the hemodynamic regulation, the corresponding arterial blood pressure curves are continuously and synchronously synchronized with each heart action (beat to beat measurement) at at least one derivation position (eg radial artery, femoral artery) with the help of a corresponding blood pressure measurement system ) with an accuracy of approx. 2 mmHg. On the one hand, these pressure curves are used to determine the occurrence times using appropriate trigger and timing methods for the systolic maxima, diastolic minima and the maxima of the dicrotic wave, and to determine specific time intervals with respect to the corresponding occurrence times.

On the other hand, the pressure values available at the respective performance times are determined from the pressure curves. In particular, the systolic and diastolic pressure values as well as those of the dicrotic wave are determined. Furthermore the magnitude of the pressure differences or ratios are also determined from the values mentioned and are shown in the form of corresponding time series in parallel and in synchronism with the other tachographic and / or parametric time series.

(iii) As a further parameter that characterizes vascular regulation (local regulation), the pulse transit time (PTT) is determined on the basis of the respective occurrence time of an R wave from the EKG signal and the occurrence times of the systoles detected with a corresponding delay from those with the current heart excitation corresponding pulse curve determined. To represent the dynamics of vascular regulatory events, these PTT time series are also shown in the form of PTT tachograms in parallel and synchronously. On the one hand, the correspondingly derived values are used to calculate the pulse wave speed that is acutely prevailing for each individual heart action in connection with the respectively selected derivation position of the blood pressure sensor and the patient-specific anatomical lengths of the vascular section examined in this regard, and its dynamic variability in the form of PWG (t) time series shown. A direct measure of the elasticity of the volume elasticity x (t) with regard to its dynamic variability from the respective pulse wave velocity for the respective heart action and the density p of the blood (= 1.06 g / cm ³ ). The time series representation of the effective one with each heart action

Volume elasticity module and its vasomotor-related variability as well as the time series described above are used for analysis purposes of the dynamic structure of the autonomous cardiovascular regulatory processes. (iv) As a further method step, the formation, correlation of simultaneous meta-representations is further specified on the basis of the time series specified under (i) to (iii) for the aforementioned application example.

To monitor the course and to objectively and quantitatively characterize the overall behavior of the complex dynamic development of the autonomous regulatory behavior of the cardiovascular system, the following are selected for this application from the MetaRepresentations listed on page 42.

These are c. the location vector course (page 58), the middle squares of successive differences (MQSD) (page 60) as well as a 3D feature space representation suitable for this application, in which the amounts of the RR and PTT location vector as well as Control parameters the respective blood volume. To calculate the relevant location vectors, the RR and PTT

Tachogram courses used. A high-dimensional embedding dimension is selected for the delay reconstruction method (dimensions greater than 25 and delay times in the order of the mean RR interval length are advantageous) and the reconstruction of the state vector is carried out. The scalar amounts are calculated for each N-dimensional state vector and represented in the form of corresponding location vector amounts RR-OVB (t) and PTT-QVB (t) either as time-synchronous time rubs in connection (pulse trains) with the other relevant time series or they go into a 3-dimensional feature-space representation selected for this application with the coordinates x: RR-OVB (t), y: PTT-OVB (t) as a cardiovascular state variable and z: V (t) as a volume-related control - parameters on. As an example, FIG. 8 summarizes a selected profile of all of the above and specified time series in an 11-channel time-synchronous representation a) to k), which is used in the course of a blood donation (under parameterized hypovolemic stress) using the claimed Procedures were obtained under in vivo conditions.

FIG. 8 shows the significant changes in the high-resolution dynamic signature of the autonomous cardiovascular system behavior as well as the sensitive relationship between the aforementioned and specified ordering parameters, which in the application serve as clinically relevant and significant parameters in connection with the volume-related control parameters.

FIGS. 9 and 10 likewise show two selected three-dimensional feature space representations in accordance with the above description in the course of blood donation under parametrically controlled hypovolemic load (total outflow = 500 ml) on two different patients. You can see the significant trends of the trajectory topology and trajectory development with regard to three excellent phases over the entire course of the donation. While FIG. 9 shows the normal course of a trajectory development in this regard, in the case of a donor with some ventricular extrasystoles (ES) that occurred during the course of the donation, a significantly changed topology and development appears. A rigorous change in the overall dynamic behavior of the autonomous regulation of the donor can be seen even outside the appearance times of the ES. In clinical application, this method is also used with the method and representation variants corresponding to the invention for objectification, quantification and identification of the autonomous dynamic cardiovascular regulatory behavior.

Use case (diagnosis and monitoring of autonomic cardiac regulation under controlled physical conditions)

In this exemplary embodiment, certain myocardial excitation variables in connection with the heart rate are determined as control parameters as control parameters under targeted parameterized physical exertion. In particular, the formation of certain excitation modes of the myocardium in the form of significant dynamic structures is carried out by using the method steps selected for this purpose in the sense of the claims. To specify the control parameter, a predetermined patient-specific resulting heart rate (HR) is set in beats / min, which results in each case under a specific ergometric load on the patient. For the application example selected here as an example, the correlation dimension analysis according to page 56 is used as order parameters, which means that with differently chosen phase space embedding dimensions (from DIM = 5 to DIM = 40), the correlation dimension that occurs at a specific heart rate and, on the other hand, the heart rate-specific exponential divergence in the form of the Lyapunov exponent according to page 57 as a the dynamics of

Characteristic parameters of myocardial excitation determined.

For this purpose, on the basis of the EKG time signals recorded over the course of the examination, EKG (t) for the respectively selected data ensembles is performed using the delay method (pre- preferably with t between 5 and 15 ms), the corresponding phase space reconstructions are carried out with different embedding dimensions. The correlation dimension assigned to a specific heart rate is then calculated from these reconstructed state variables. The definition of the correlation dimension is based on the correlation sum (Heaviside function). Since the calculation of the correlation sum requires a great deal of computing effort in practice, a simplified and efficient algorithm according to Grassberger and Procaccia was used for this calculation.

As a further relevant measure of the dynamic stability behavior of the determined phase space trajectories relating to the autonomous myocardial excitation processes, the Lyapunov exponent is calculated, which represents a relevant measure for the mean exponential divergence of the trajectories within a myocardium attractor and which is the dynamics of changes in state assigns a corresponding measure of stability. The calculation of the respective acute value for this exponent thus characterizes a suitable patient-specific stability measure for the autonomous myocardial excitation processes. Through the assignment and / or correlation according to the invention of the respectively acute values for these exponents with the acutely occurring load quantities or the control parameter values derived therefrom, such as the heart rate, the relevant course observation thus provides a further suitable, clinically relevant and significant objective and quantitative parameter Application in the field of cardiovascular diagnostics. Here, a positive exponent describes the extent to which the trajectories drift apart. This means that the more positive this exponent becomes, the more sensitive and unstable the behavior of the examined myocardium attractor. FIGS. 9, 10 show an illustration of the FIG patient-specific heart rate dependency (control parameter) of the cardiac order parameter a. the correlation dimension and b. the Lyapunov exponent with different phase space embedding dimensions,

FIG. 9 shows three excellent and significant mode changes in the dynamic structure of myocardial excitation at certain heart rates. FIG. 10 shows the significant changes in the dynamic complexity or the stability of the myocardial excitation, which, depending on the patient, occur in each case at defined heart rates. By a combined monitoring of the course of the patient-specific profiles for the correlation dimension and Lyapunov exponents in connection with the respectively excellent heart rates, in which Significant changes in mode of myocardial excitation are to be expected in future further clinically valuable embodiments of the invention. To define an excitation mode, the product of the dimension value and the value of the Lypunov exponent is proposed based on the knowledge of the invention.

Claims

claims

1. A method for diagnosing and / or monitoring the cardiovascular system of a living being with the steps: a. Automatic, continuous and time-resolved determination of measurement data of at least one cardiac and / or circulatory-specific parameter, in particular blood pressure and / or myocardial excitation; b. Formation of time-structured ensembles of measurement data for generalization and / or complexity reduction with regard to the temporal process-related regulatory development of the cardiovascular system, in particular the heart rate variability and / or the pulse transit time, - c. Determination of at least one time series of the ensembles to represent the temporal and regulatory development of the cardiovascular system; d. Analysis of the temporal behavior of the time series; e. Assignment of the temporal behavior of the time series to empirically determined physiological properties and characteristics of the cardiovascular system, in particular in their relationship to different parameterizable loads; f. Representation of the temporal behavior of the time series and / or the physiological properties and features for diagnosis and monitoring of the cardiovascular system.

A method according to claim 1, characterized in that two cardiac and / or circulatory-specific parameters are measured simultaneously.

3. The method according to claim 2, characterized in that the blood pressure is measured simultaneously in two different distal locations of the body.

4. The method according to claim 2, characterized in that the myocardial excitation is measured by means of an EKG simultaneously with the blood pressure.

5. The method according to any one of the preceding claims, characterized in that the formation of time-structured ensembles is achieved by forming windows of measurement data.

6. The method according to claim 5, characterized in that the measurement data in the windows are analyzed with regard to periodic components or rhythmic components, in particular the time interval between two heartbeats, and the analyzed values are used as the time-structured ensembles.

A method according to claim 6, characterized in that with the analyzed values of the window, the time series in step c. is determined.

8. The method according to any one of the preceding claims, characterized in that for the analysis of the temporal behavior of the time series this is represented in a meta-representation by means of a reconstruction method.

9. The method according to claim 8, characterized in that the time series is represented in the form of Lorenz plots, phase spaces, parameter spaces, trajectory plots and / or Poincare plots.

10. The method according to claim 8 or 9, characterized in that the time series is represented in the parameter space by means of a delay method.

11. The method according to any one of claims 8 to 10, characterized in that the parameter is represented as a state vector.

12. The method according to any one of claims 8 to 11, characterized in that accumulation points, attractors and / or trajectories of a state vector are determined from the representation of the time series.

13. The method according to claim 12, characterized in that the temporal behavior of the accumulation points, attractors and / or trajectories is determined.

14. The method according to claim 12 or 13, characterized in that statements about the spatial-temporal relationships of the respective accumulation points, attractors and / or trajectories with respect to one another are derived from the temporal behavior of the accumulation points, attractors and / or trajectories in the parameter space.

15. The method according to any one of claims 12 to 14, characterized in that a measure for monitoring the course of the long-term development of the cardiovascular system is derived from the temporal behavior of the accumulation points, attractors and / or trajectories in the phase space.

16. The method according to any one of the preceding claims, characterized in that in step e. The empirical determination of the physiological properties corresponding in each case with the temporal behavior of the time series is carried out by simultaneous measurement of the respective physiological properties, in particular the heart rate, the mean blood pressure, the cardiac output and / or the stroke volume.

17. The method according to claim 16, characterized in that the empirical determination at a defined load on the cardiovascular system, in particular by using physical and / or pharmacological means.

18. The method according to any one of the preceding claims, characterized in that additional external and / or internal cardiac and / or circulatory-specific control parameters in the analysis of the temporal behavior of the time series and / or the assignment of the temporal behavior of the time series to empirically determined physiological Properties to be included.

19. The method according to claim 18, characterized in that the heart rate, the mean blood pressure, the cardiac output, the stroke volume, defined volume flow rates, the volume inflow or outflow and / or ergometric work or performance parameters are used as control parameters.

20. The method according to any one of the preceding claims, characterized in that the assignment of the temporal behavior of the time series to empirically determined physiological properties and features in step e. is made automatically.

21. System for carrying out the method according to one of the preceding claims, characterized by at least one measuring means (2, 3) for the automatic and continuous measurement of at least one cardiac and / or circulation-specific parameters (20, 30) of the living being (1), at least one recording means (4) for the automatic and time-resolved recording of the parameter (20, 30) measured with the measuring means (2, 3), and at least one evaluation means (5 ) for evaluating the continuously and time-resolved parameter (20, 30).

22. System according to claim 21, characterized in that at least one cardiac and / or circulatory-specific parameter (20, 30) is the blood pressure and / or the myocardial excitation.

23. System according to claim 21 or 22, characterized in that at least one measuring means is a blood pressure measuring device (3) and / or an EKG (2).

24. System according to at least one of claims 21 to 23, characterized in that at least one measuring means (2, 3) is non-invasive.

25. System according to at least one of claims 21 to 24, characterized in that at least one measuring means (3) is designed for measurement on a distal body part of the living being.

26. System according to at least one of the claims ^"21 to 25, characterized in that at least one measuring means (3) is designed as a pressure sensor.

27. System for the diagnosis and / or monitoring of the cardiovascular system of a living being, characterized by at least one measuring means (2, 3) for the automatic measurement of at least one cardiac and / or circulatory-specific parameter (20, 30), at least one determining means (6a ) for the automatic determination of at least one time-resolved baro-reflex response of the living being from the measured cardiac and / or circulatory-specific parameters (20, 30), at least one extraction means (6b) for the automatic acquisition of at least one time series from the determined time-resolved baro-reflex responses, at least one Evaluation means (6c) for evaluating the temporal behavior of the at least one time series of the at least one measured baro-response, at least one allocation means (6d) for automatically assigning the temporal behavior of the at least one time series to physiological properties and characteristics of the living being, and at least one display means (8) for displaying the physiological properties and characteristics of the living being.

28. System according to claim 27, characterized in that at least one baro-reflex response is the pulse transit time, the heart rate, the blood pressure and / or the baro-reflex sensitivity.

29. System according to claim 27 or 28, characterized in that at least one baro-reflex response is the pulse transit time variability, the heart rate variability and / or the blood pressure variability.

30. System according to one of claims 27 to 29, characterized in that the at least one measuring means is designed as an EKG device (2) and / or blood pressure measuring device (3).

31. System according to one of claims 27 to 30, characterized in that at least one measuring means (2, 3) is non-invasive.

32. System according to one of claims 27 to 31, characterized in that the at least one determination means (6a), the at least one extraction means (6b), the at least one evaluation means (6c) and / or the at least one assignment means (6d) is designed as software means.

33. System according to one of claims 27 to 32, characterized in that in the at least one determination means (6a), the at least one extraction means (6b), the at least one evaluation means (6c) and / or the at least one assignment means (6d) Method according to one of claims 1 to 20, wherein the representation in step f. is carried out by the representation means (8).

34. System according to one of claims 27 to 33, characterized in that in the allocation means (6a) the temporal behavior of the time series is set in relation to at least one stored, empirically determined behavior of a time series of the same baro-reflex response, which when excited the cardiovascular system of the same or a different living being (1) was determined.

35. System according to claim 34, characterized in that the cardiovascular system of the living being is stimulated by physical action, in particular infusion, blood sampling and / or physical stress, and / or by pharmacological action.

36. System according to one of claims 27 to 35, characterized in that in the allocation means (6d) additionally at least one control parameter is used to assign the temporal behavior of the at least one time series to physiological properties and characteristics of the living being.

37. System according to claim 36, characterized in that the at least one control parameter is additionally provided by the at least one measuring means (2, 3) and / or by at least one further measuring means.

38. System according to claim 36 or 37, characterized in that the at least one control parameter is the mean heart rate, the mean blood pressure, the infusion volume, the blood withdrawal volume, the distension agent volume or the distension agent balance and / or an ergometer performance.

39. System according to one of claims 27 to 38, characterized in that when monitoring a patient when the time behavior of the time series is assigned to a critical cardiovascular state, a warning is output on the display means (8).

40. Use of a system according to at least one of claims 27 to 39, 21 to 26 and / or a method according to at least one of claims 1 to 20 in intensive care medicine, sports medicine, rehabilitation medicine, anesthesiology, monitoring Fitness equipment and / or general cardiovascular diagnostics, in particular for monitoring an exercise ECG.

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