CN103300819A - Learning patient monitoring and intervention system - Google Patents
Learning patient monitoring and intervention system Download PDFInfo
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- CN103300819A CN103300819A CN2013100836748A CN201310083674A CN103300819A CN 103300819 A CN103300819 A CN 103300819A CN 2013100836748 A CN2013100836748 A CN 2013100836748A CN 201310083674 A CN201310083674 A CN 201310083674A CN 103300819 A CN103300819 A CN 103300819A
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Abstract
A patient monitoring and intervention system, comprises an interface for receiving data representing multiple different parameters from multiple different sensors, comprising sensors in a patient bed and attached to a patient including, a heart rate sensor, a respiration sensor and a pressure sensor indicating bed pressure points. A learning processor determines a normal range for a set of the different received patient parameters for the patient by recording the patient parameter values over a time period and analyzing the recorded parameter values to determine their range. A data processor determines if the set of different received patient parameters exceeds the determined normal range and in response to this determination and in response to the type of parameters in the set and medical record information of the patient, initiates adjustment of a patient bed and at least one of, (a) changes medication administered to a patient and (b) alerts a worker of the patient parameter change.
Description
This is by the non-provisional application of the people such as C. Schultz in the provisional application sequence number 61/611,260 of submission on March 15th, 2012.
Invention field
The present invention relates to use patient monitoring and the interfering system that is attached to patient's sensor in the sick bed neutralization, it determines the normal range of the patient parameter that a winding is received with the study processor and in response to adjusting sick bed above the parameter of the normal range of determining, change gives patient's medicine and gives the alarm to the worker.
Background technology
Preferably make monitoring and intervene can be supported in hospital, family, other is controlled with organized environment in and patient medical health care in not controlled environment (such as the scene of the accident, disaster area and other outdoor environment).Under such setting, may there be a large amount of casualties to need fast identification and severity classification.Such situation all is challenging for monitor patients with transporting them.Processing these according to the system of inventive principle needs and problems of being associated are supported from a large amount of patients in real time the seamless concurrent collection of dissimilar medical data and supported automatic nursing intervention for these patients.System according to inventive principle processes these deficiencies and relevant problem.
Summary of the invention
System provides a kind of hospital patient watch-dog transparent and intelligence, and it is carried out with system unit and wired or wireless a plurality of sensors that are connected to this unit and relates to processing, data base and Presentation Function and execution patient data monitoring, storage and the knowledge base function that generates alarm.Patient monitoring comprises with interfering system: be used for receiving from a plurality of different sensors the data of a plurality of different parameters of expression, these a plurality of different sensors comprise the sensor (pressure transducer that comprises heart rate sensor, respiration pickup and indication bed pressure spot) that is attached to patient in the sick bed neutralization.The study processor is by record patient parameter value within a period of time and analyze the parameter value that records to determine their scope, the normal range of coming to determine for patient a different set of patient parameter that receives.Data processor determines that the different patient parameter that receives of this group surpasses determined normal range and determines and in response to the type of the parameter in this group and patient's medical record information in response to this, initiate the adjustment of sick bed and following at least one: (a) change the medicine that gives patient, and (b) change to worker's alarm patient parameter.
Description of drawings
Fig. 1 illustrates the hospital's configuration that is attached to the sensor that in the sick bed or wirelessly is attached to patient according to embodiments of the invention.
Fig. 2 illustrates according to the patient monitoring of embodiments of the invention and interfering system.
Fig. 3 illustrate according to embodiments of the invention comprise automatic learning depend on patient sensing data normal mode for patient automatically and the process chart of monitoring and the intervention of guide arranged.
Fig. 4 illustrates the method for the sensing data that obtains according to the processing of embodiments of the invention, and the method comprises that self-adapted sensor is selected, classification feature is selected and response or action selection.
Fig. 5 illustrates the example flow diagram of processing according to the home care that is used for automatic monitoring patient and identification unusual condition of embodiments of the invention.
Fig. 6 illustrates the flow chart of the processing of being carried out by the patient monitoring of foundation embodiments of the invention and interfering system.
The specific embodiment
Fig. 1 illustrates the hospital's configuration that is combined in the sick bed 103 or wirelessly is attached to patient 105 sensor, the hospital patient monitoring transparent and intelligence of this hospital's Configuration.System in one embodiment is combined sensor and infrastructure in sick bed 103, in infrastructure, provides system unit 107(by each sick bed and be also referred to as sensor bridge).The physics bed accessory has unit and wired or wireless a plurality of sensors that are connected to this unit of similar system.Bed for example wirelessly is connected to infrastructure 109(, Ethernet) and process for each execution at the computer that is connected to ethernet network.System unit 107 obtains wired analog input and numeral input, measurement is carried out digital sample and they are routed to remote processing station (for example, server) from sensor.Remote server is carried out processing, data base and the Presentation Function that generates alarm and is carried out patient data's monitoring, storage and knowledge base function.Server has been realized from nurse station, has been passed through bed to patient data's a comprehensive security webserver connectivity from the doctor position with patients home.
Fig. 2 illustrates patient monitoring and the interfering system 10 that comprises monitor node 43,45,47,49 and 51 network, and this monitor node comprises internuncial processing and the communication unit 107(Fig. 1 in the environment (for example comprising the scene of the accident) that cooperation realizes disperseing geographically together individually).Doctor and other medical worker communicate by letter with back-end server 30 by ad hoc network (that is the network of, setting up for specific and potential interim function) with system 10.Server 30 comprises data processor 15, study processor 25, storage vault 17, interface 27 and display 19.Interface 27 receives the data of a plurality of different parameters of expression from a plurality of different sensors, these a plurality of different sensors comprise the sensor (pressure transducer that comprises heart rate sensor, respiration pickup and indication bed pressure spot) that is attached to patient in the sick bed neutralization.In one embodiment, server 30 is the equipment of networking, and its indication is possible (to comprise the connection that the patient record is connected with drug information, and the connection of arriving other health care expert to other health care resource.Study processor 25 is by record patient parameter value within a period of time and analyze the parameter value that records determining their scope, thereby determines the normal range of one group of a plurality of different patient parameter that receive for patient.Unit 25 is also from similar patient's data set learning standard, and medical and health work person's parameter that settles the standard in one embodiment.Data processor 15 is determined that the different patient parameter that receives of these groups surpasses determined normal range and is definite and in response to the type of the parameter in this group and patient's medical record information in response to this, processor 15 is initiated the adjustment of sick bed and following at least one: (a) change the medicine that gives patient, and (b) change to worker's alarm patient parameter.
Storage vault 17 is stored in patient's normal range of the patient sensor parameter value data in a period of time, the determined patient parameter group that records and indicates the action of carrying out and the data of response in response to the patient parameter value surpasses the normal range of determining within a period of time.Display 19 gives information and alarm Xiang the doctor.Even in the situation that there is not broadband connection (such as in the disaster area), the autonomous character of this ad hoc network provides local connectivity.Unit 107 obtains data, it is carried out pretreatment and sends necessary information at network 21 in this locality.Therefore, be minimized in the load on the network and the storage demand on server 30.The definition of necessary sensor information is different and is adaptive or at user option for each application.Larger data volume (such as original sensor data) can be stored in this locality also can be accessed via for example high bandwidth connection (connecting such as USB) in the unit 107.
Comprise with the scope of the integrated sensor in unit 107: be programmed into the wired sensor in intelligent bed or the intelligent room (mattress, medicated pillow, baffle plate, wall).This sensor comprises: microphone (for the sound of breathing, heart beating, stomach), vibration (for pulse, tremble, onste, muscle spasm and ballism), pressure (for tighten, body position, tissue can compressed partial high pressure forces, determine whether patient leaves bed), temperature (for fever, blood circulation, comfortable), chemical constitution (for urine, antiperspirant, saliva) and the professional liner that uses at special time (for oximetry, EEG, metabolism, protein group, genomic expression).Additional portable sensor can be used and be connected by ad hoc by wireless technology.Therefore, also can be at monitor patients beyond the bed.For example, the sensor in the smart machine as panel computer and smart phone is supplied with additional data.Additionally, wrist device measuring pulse, temperature, blood pressure, lung oxygenate index (oxygenization), galvanic skin response (GSR) conductivity and limited protein group/genome chip sampled data is provided.Similarly equipment is adhered to other extremity or chest and is realized the analysis of the sound of breathing stomach function regulating with the effect of monitoring for example diet, gastrointestinal program or to the reaction of medicine.In addition, body sensor (comprising accelerometer) is used for the signal that monitoring is walked about, such as (reaction or mobile) speed, stability (for example, whether patient waves or walk haltingly and blush), vigilance or sleepy, gait and posture.Photographing unit (on bed, glasses or on smart machine) is used to the tracking of eyes tracking, palor and facial expression (for example, indication painful or fear).Microphone (on bed or smart machine) is for assessment of patient's voice (for example, detecting apoplexy), health creak sound and crack, grieved sound or keyword (for example, help or pain).In addition, smart machine is used for additional input and order (for example, increasing temperature, help) from patient.
Mutual by unit 107(or worker) automatically commander's actuator control sick bed position (reduce the damage that heart attack or cardiac shock cause, prevent from breathing and the snoring problem) and medicament dispenser (being used for avoiding life-threatening situation).System 10 in one embodiment provides patient's remote household care monitoring.
Fig. 3 illustrate comprise automatic learning depend on patient sensing data normal mode for patient automatically and the process chart of monitoring and the intervention of guide arranged.Follow after the beginning at step 303 place, if data processor 15 in step 305, determine iteratively new sensing data whether available and data be available, then interface 27 obtains sensing data and records sensing data and is used for the back and uses and file in step 307.Processor 15 is identified the feature in the sensing data that obtains and tagsort is being become the normal or unusual middle model 316 of indicating normal condition as patient that uses in step 311 in step 309.System also realizes selecting for the doctor of the parameter value of the special circumstances with a patient or specific one group of patient within preset time or under one group of environment.Obtaining in the normal patient data model 316 adopting training dataset from the data of patient and (optionally) expertise 313 at step 319 learning processor 25.If the generation that is characterized as unusually and indicates event in the sensing data that processor 15 identifications are obtained in step 323 is then notified the worker these data by audition, vision or haptic alerts or communication information in step 326.Order in response to the worker who is caused by checking of data with alert in step 341, in step 346, initiate medical intervention (for example, the use of medication management, Medical Equipment) and in step 349, record and the medical intervention of sensing data is stored in the storage vault 17.The worker's order that does not need to intervene in response to the indication in step 341 selectively is initiated in step 343 in step 351 place termination and with audition-visual communication of patient and other worker.
Processor 15 is automatically analyzed detected event in step 323 by comparing the identified emergency situation with patient parameter or from value and threshold value that parameter obtains in step 329.If the emergency of detecting, then in step 331, initiate the medical intervention action (for example, basic first aid, via the foot of bed order raise, delivering oxygen) and in step 336, record and the medical intervention of sensing data is stored in the storage vault 17.Similarly, if in step 329, do not detect emergency, then in step 333, initiate comfortable action for patient.In response to the success of the action of determining in step 339, handling process turns back to beginning and step 305 and reprocessing.If do not detect successfully, then handling process is advanced from notifying process 326.In addition, in response to worker's status request 361, interface 27 obtains sensing data in step 363, and processor 15 is extracted in the sensing data in step 366 feature and handling process continue from worker's notifying process 326.
Study processor 25 is automatically learnt to depend on patient's normal mode sensing data and is adopted in one embodiment the human expert to supervise and be input in the study processing.The decision of the decision of the key of system and overseer user's key is recorded and is used in helps treatment in the future in the learning model.Study processor 25 obtains patient data alive, and (normally) patient particular range of the dissimilar parameter of a plurality of dimensions is crossed in study, the monitoring abnormal conditions, and be controlled at patient's relevant equipment of medical science on every side in emergency room and the home care environment.Employing is for telemedicine, remote diagnosis, remote programmable and the mutual connectivity to the health care personnel, and system adopts intelligent assistant (unit 107) network to come unusual situation and trend is carried out advanced processing and cloud storage, search, query generation, schema-based are found.System pellucidly (not with nurse or doctor mutual) carries out and comprises by obtaining constantly dissimilar patient data and provide data to come to transmit, store also deal with data in distributed mode via the network of dynamic-configuration to data processor 15 from sensor from the unit 107 of bed.
Processor 15 local, in distributed system or remotely deal with data and obtain reasoning measure (by with the sensing data combination with the relevant amount of reasoning) and carry out the diagnosis demonstration by study specific to the specific normal sensing data of the patient of given patient.Processor 15 checks constantly that also sensor function finds to damage incorrect the reading that causes by sensor for example.System (for example determines the restriction of patient's particular safety, minimum, maximum and rest heart rate), compare remotely or carry out at the patient location place abnormality detection to real time data by the pattern that patient's current state and processor 25 are learnt via sensing data, this sensing data be under the normal condition given patient and from by have with the similar population statistics of patient situation (comprise age, body weight, highly, sex, conceived state) and the patient population of the similar medical condition data collection that obtains.System also with received medical science and social knowledge come execute exception detection and display measurement and diagnostic data (on the network equipment and be authorized to be connected on the equipment of grid).
System 10 (on data base and one or more treatment facility) in the large scale system knowledge base carries out other data acquisition and processing capacity, is included in and stores data among the data base, learns, carries out auxiliary function from the patient data.System's 10 foundation are obtained about the bridge of the information of the auxiliary portable equipment that is connected to patient and audition-visual communication of realization and patient.System carries out action, call contact automatically for example, for example, if detect abnormal data, patient attempts leaving bed or waking up.System is according to controling environment (such as temperature) from patient's sensing data or activating message function, control medicament distribution and electronic equipment (such as TV, microwave) if the breathing problem of detecting then rotate sleeping patient and carry out simple function of emergency treatment (such as raising in bed upper body or the lower part of the body).System also carries out such as the action that input is provided to management personnel, law and facilities management group and assess disease communication mode.
System 10 disposes efficiently netted (mesh) communication construction of robusts, itself in addition do not have therein to make system equipment can keep collaboratively connectivity in the arranging of infrastructure support.For example, in the disaster area, patient can be placed on the stretcher that system enables, and its collection, analyzes and acts on from patient and directly collect data.Each system equipment also is maintained to the connectivity of center system by the mesh topology that is created in the mode that cooperates by system equipment.Because these equipment person that both shown as the data collection also shows as data retransmission person is so such mesh topology further expands wireless range.Therefore, each packet that generates from origin system equipment is selected best available route by jumping at some other system equipments.By equipment self automatically and independently carry out mesh topology establishment, configure and keep operation, and do not have any needs of human interaction.Therefore, do not need the technical staff to appear at the website place of deployment.
Fig. 4 illustrates the method for processing the sensing data that obtains, and the method comprises that self-adapted sensor is selected, classification feature is selected and respond and action is selected.The method has expert's decision of the medical condition that depends on adaptively patient, current sensor reading, the nurse who depends on precedent and doctor and the stage of available amount of training data.In the first step shown in the hurdle 403, data processor 15(Fig. 2) in response to patient's medical condition of patient and (a) decision and (c) at least one in the available amount of training data of current sensor parameters value, (b) clinician in comparable medical science case, and from available sensor, select adaptively a plurality of different sensors, so that best treatment to be provided in specific cases.One group of sensor is selected such as blood pressure, heart rate, health vibration, and the humidity level in the part of the pressure of given body position and patient surface is used for monitoring for the significant content of patient's medical condition.Use in one embodiment by the look-up table of clinician's configuration and carry out this adaptive selection.
In exemplary operation, for the patient with heart, importantly monitor blood pressure and heart rate.Obtain constantly from the data of selected sensor and with these data and be delivered at training and the sorting phase by 25 execution of study processor shown in the step on hurdle 405.Study processor 25, is selected to be used for determining (a) normal range and (b) at least one function of abnormal ranges by the study processor adopting from a plurality of difference in functionalitys for a plurality of different patient parameter groups that receive from the patient data of the available record of sensor amount with (ii) from the patient data's of the available record of sensor the type at least one in response to (i) adaptively.The patient data's of this record type comprises normal and healthy patient sensor reading and unusual patient sensor reading.These a plurality of functions comprise (a) class support vector machines, (b) class interconnection vector machine and (c) at least two in the multiclass interconnection vector machine.For example at-J. Shawe-Taylor and N. Cristianini. Kernel Methods for Pattern Analysis. Cambidge University Press, New York, NY has described SVM in 2004. (pages or leaves 211 and following etc.).For example at-C. M. Bishop. Pattern Recognition and Machine Learning (Information Science and Statistics). Springer, New York, NY, 2006.(page or leaf 345 and following etc.) in RVM has been described.Processor 25 is in response to about patient's available information and select adaptively between different learning machines.For example, if limited patient data be recorded (by determining with predetermined threshold) and from normally/data of health sensor reading are available, then select a class kernel support vector machine (a class SVM).
As follows, order
Expression with
Comprise
NIn the training data example one
dThe vector of sensor reading or feature.In addition, order
With
Soften and the support vector weight of expression SVM.In addition, order
Nuclear matrix in the expression symmetric positive definite
Element.The cost function of one class SVM by
Given, obey:
With
On the data sample group that records before, found to make the minimized weight of this cost function
In classifying step, the given threshold value of study before whether the new data instance of class SVM assessment is included in
Hypersphere in, the radius in kernel spacing comprises
The border that is arranged in the point in the inboard and outside of this classification is illustrated in the heart rate on hurdle 405 blood pressure is drawn.If have the sufficient training data that is collected to come the probability in Modelling feature space, then replace a class SVM by processor 25 with another machine learning method (such as interconnection vector machine (RVM)).Rather than only returning normal or unusual classification, RVM causes the estimation of the posterior probability of current state.For example, can to indicate 95% probability be that sensing data represents the normal patient situation in output.If have information or data about the specific exceptions situation, then these can use the multiclass learning method to be trained.Different embodiment adopts different sensors to select, learn and improve one's methods and is not limited to SVM and RVM.
In the step shown in the hurdle 407, the result by data processor 15 usefulness sort programs selects action and response adaptively.Determining that a plurality of different patient parameter groups that receive surpass in the situation of the normal range of determining, data processor is selected the action that will be performed in response to lower at least one adaptively: (a) from patient data's amount of the available record of sensor, (b) criticality from the patient parameter of the type of the patient data's of the available record of sensor type, (c) selected function, (d) patient's the medical condition reception different with (e).For example, as long as study processor 25 does not have sufficient data volume (being less than predetermined threshold quantity), a class SVM machine learning method just is used to the patient parameter that obtains from one group of sensor selecting is classified.In this case, when detecting when unusual, the underconfidence of minute apoplexy due to endogenous wind is to initiate urgent action.Therefore one group of action simplifying is selected and notifies care-giver or nurse.Data processor 15 initiates to operate and the data of identifying the action of taking are carried out record as being asked by the clinician.If pattern is detected and data for modeling, then learn the clinician's that processor 25 initiates to record behavior in the case in future.If the credibility (for example, 98% probability being arranged) that exists enough data to provide patient the abundance of Deviant Behavior just is being shown and in response to patient's medical condition and the criticality of sensing data, processor 15 is notified patient's the doctor in charge.For example, if patient has heart and blood pressure is raised to abnormal level, then initiate immediately action by processor 15.
In the situation that urgent, the overseer notifies ambulance and advances to simultaneously position with contact patients.System also controls patient's medicament distribution via the automatic vending machine of Long-distance Control and automatically reminds patient to take medicine and verify that medicine is taken.For example, if in case of emergency or patient pain is arranged, the overseer provides additional medicine via the smart phone that is linked to system.In this mode, overdose is prevented from and in the situation that needs the Emergency Assistance doctor to know definitely when which kind of medicine the point place has taken.The training module for patient that system carries out, controls and the assessment doctor stipulates.For example, interactive game is initiated on system cycle ground, comprises the eye motion tracking that recovers for apoplexy or muscular training and for the joint mobility that restores.Assess test result and predict recovery time.If recover to be obstructed, then the needs of the notified progress of patient and doctor or intervention.System automatically or remote auto ground or in response to the manual mutual and utensils of control domestic of overseer.For example, if patient is cold or perspiration, then automatically adjust room temperature, if patient starves, activate microwave by the overseer.System also can be with intelligent baby bed use, and this is intelligent baby bed for example to be used for monitoring child's sleep, child's position (for example in the side, stomach or back) and abnormal pattern of crying prevents that the child who happens suddenly is dead.
In another embodiment, system by effectively controlling each environment and accelerate recovery time, monitor and improve measured emergency room (ER) patient's sensing data (such as blood pressure, blood oxygen saturation SPO2 and heart rate).For example, the reaction according to the patient who measures can automatically be controlled at the temperature in the bed, can automatically activate message function and improve blood circulation or can carry out other and measure to avoid a skin ulcer or other harmonic motion problem.In addition, when detecting the sound of snoring, system automatically rotates the patient between sleep period.This is used to prevent barrier sleep apnea (OSA).The typical characteristic of this imbalance is hypoxemia, and it is saturated that it can cause being less than 50% oxygen.And the arrhythmia of heart is generally caused by OSA.For right heart failure, pulmonary hypertension, stagnated blood of liver, angle edema with dizzyly dispose in advance some patients OSA.The air mattress that has a plurality of independent Controllable Air bags by control is realized rotating.If heart attack or apoplexy are detected, then system carries out basic first aid, such as raising patient's upper body (being reduced in the pressure on the involved area) if or the cardiovascular system apoplexy, then raise patient's foot (realizing the better blood circulation in head).The immediately management of such measure has minimized response time and has therefore reduced potentially consequent infringement until the specialty rescue arrives.
The people of system monitoring in hazardous environment (such as disaster area (for example, being caused by fire, earthquake, hurricane, flood, nuclear accident, the attack of terrorism etc.)).For example, in the situation that have a large amount of victims and infrastructure to damage, usually can not help immediately everyone.The different patients' of system monitoring state and the patient who helps the most serious injured needs of identification to help immediately.And system made local communication networking and realization are to patient data's real time access.This can be used to be evaluated at the needs of the additional help in the zone and therefore help total emergency response.System also monitors aid (for example, fireman, soldier, doctor, technical staff's) state.For example, consequential emergency (for example, if in the situation that in fire house collapse bury the fireman), follow the trail of aid's position and realize helping immediately.And the assignor promotes possible the determining of toxin, communicable infection and radiation that be exposed in the information of the persistent period of specific location.Additionally, the sensor that is attached to the aid is used to draw other people of environmental aspect map (for example, temperature, ambient sound, radiation, pathogenic bacteria, fuel gas, CO2 concentration) and warning of hazardous zone.Pressure, loss and the grade that is exposed to toxic substance are also monitored and be used for making the disaster aid in turn, and distribute comparably their somatotonia and prevent overworked and collapse.
System comes the sleep of monitor patients by assessment heart rate, breathing, pulse and patient's action.Each patient is different and is supposed to have different medical conditions.System adapts to constantly and learns the normal sensor parameters value output in (for example, minimum, maximum heart rate) in predefined physical boundary for each patient.If patient wakes up, irritated, attempt to leave bed or the abnormality sensor data be shown, then notify the overseer and activate local alarm in bed.The abnormality sensor data for example comprise in the past not shown this irregular or the heart rate that increases or the slight breathing problem for patient.In this case, the overseer activates and the photographing unit of access in patients home by smart phone when working with other patient.The overseer assesses situation and for example stops patient by the speaker in the room and patient talk (or communicate by letter such as video conference via another exchange method) and leave bed, nextly inquire about possible reason or come to provide oral support for patient for abnormal conditions.
In the example of operation, John is 65 years old male, and he is standing heart disease in the past ten years, and John is by unit 107 monitoring, if this unit 107 constantly and is accurately followed the trail of his heart beat and any variation arranged or unusual behavior then warn him.System collects various types of health and fitness informations (comprising temperature, pulse frequency and exercise data) from John's health and collides for following the trail of unexpected falling with health.John's bed is intelligent bed, has some sensors that are embedded in the bed structure, comprises the chemical sensor that can detect urine, perspiration and saliva and the pressure transducer that detects motion and the high pressure on body part.Intelligent bed is directly communicated by letter with unit 107 and transmission sensor reading periodically.Unit 107 is (comprise the local sensor that directly is positioned on the unit 107 and such as the remote source that is embedded in the sensor on the intelligent bed) Information Monitoring from some sources.Unit 107 is checked this information and is analyzed in real time it, and estimates patient's state.System learns and identifies from the historical data of patient sensor collection by analysis patient's normal parameter reading of patient constantly from the patient sensor reading.System access provides for the general data storehouse of the health data of various types of diseases and conditions and out of Memory source.This information of system acquisition is also with this information and patient's historical data and normal reading and the sensor reading of other static data (such as patient's age, class origin and health records) combination and Discover the patients.Therefore, system makes the patient who self is adapted to from different background and age group and various health problem and disease.
John's intelligent bed also is the motor-driven bed that has for the function of the position of automatically adjusting the head of a bed and tailstock.Before two months, when John lay in his bed when upper, main blood circulation shock occurs in him.He can not move and nobody can be cried for help.Unit 107 identifies abnormal blood pressure immediately, heart beating and adnormal respiration and give the alarm to the emergency medical personnel about this situation.Before ambulance arrived, system compared to identify potential problem by sign and the symptom with sensor reading and general medical science burning issue, thereby utilized valuable minute, and detected John and may just stand blood circulation and suffer a shock.In addition, system knows foot raised makes foot be higher than head (being commonly called as Trend), and this is that the shock of the type is relaxed in the first aid position of standard, and activates the intelligent bed motor and raise patient's foot and reduce patient's head.In this case, system intelligence ground serves as Emergency paramedic and improves patient care.
Fig. 5 illustrates the example flow diagram of processing for the home care of automatic monitoring patient and identification patient's unusual condition.In step 506, following the beginning at step 503 place, data processor 15 obtains the sensor parameters data of one group of sensor of selection from storing 504, and extracts data characteristics and pattern in step 509.In step 511, patient data's feature that 25 pairs of processors of study extract and the normal or Deviant Behavior that pattern is classified and whether definite data of classifying indicate given patient in step 514.In response to normal classification, patient data's feature of in step 521, extracting and pattern is used to improve patient model and in step 528 this model of storage, process turning back to step 509.In step 521, from improve processing, get rid of abnormal data.Based on the combination of sensor reading and under some situations of identifying, the normal value of these readings is the normal values that depend on from the data value of other sensor.
System identification for the group of the abundant unusual value of given medical condition and in some cases unusual determining comprise a series of step rather than only search or single formula.In addition, a series for the treatment of comprises that one group of action and system monitor complicated sensor input again when being adapted to specific cases.System comprises for the different ability of coming detecting sensor by manufacturer, brand, service life, position, environment, and the difference of the sensing data analysis sensor that is adapted to detect.If in step 514, determined Deviant Behavior, then step 526 learning processor 25 to the worker give the alarm and in step 517 data processor 15 determine whether to take in response to Deviant Behavior preconcerted operations.If processor 15 is taked preconcerted operations in response to Deviant Behavior, then in step 534, initiate action by processor 15, process turning back to step 506.If processor 15 determines not take in response to Deviant Behavior preconcerted operations, then in step 531 processor 15 for the patient population of sharing demographic characteristic (age, body weight, height, sex) with this patient with patient's medical condition data and history (obtaining from data base 561,563) and medical symptom with treat data and carry out relevant.
System 10 automatically identifies (comprising the medical sensor reading that is attached to patient body and bed) patient's unusual condition by checking dissimilar information.From medical data base 563,561 and information centre gather static information (such as age and race), general medical science information and statistical information.Relevant in response to this, processor 15 determines that patient's medical conditions are whether critical and if it is notify the worker in step 541 in step 537.Processor 15 need further to determine whether first-aid intervention and if it is initiate action (for example raising foot by the bed adjustment with respect to head) in step 549 in step 547.Processing continues from step 506.
System obtains patient parameter and according to the complex patterns detection error of record from the sensor of a plurality of patients' of being attached to sensor and patients room, determines that whether deviation obviously and from the different suitable action of on selection of using carry out with as responding.System provides data pattern to be used for and comparing for this patient or the data value of patient population identification normal mode and the preassigned pattern of scope of obtaining from learning model with the method for favourable different types of sensing data combination, processing and combination sensor data.In response to this relatively, system takes action, and comprises that the actuating via the patient bed parts comes removing patient.
System records constantly the patient parameter data of the indication patient health state that obtains from the sensor of a plurality of patients' of being attached to sensor and patients room and detects deviation with the complex patterns of record.System determines that based on predetermined adaptive threshold whether obviously and the suitable action of selection from the look-up table that the parametric model with the action that will take specific to relating to of patient (comprise the management medicine, adjust patient bed and give the alarm to personnel) is associated deviation.System learnt and diagnoses new data and act on it from the historical patient particular data that the sensor by a plurality of patients' of being attached to sensor and patients room obtains within a period of time.
System is from the sensor receive data, process sensor data produces intermediate object program in combination, whether predetermined patient's particular safety (normally) scope that this intermediate object program is relevant with threshold value, scope, the data that recorded in the past and patient compares, come the pattern of detection of complex and come definite deviation with normal range obvious.System use look-up table or predetermined rule with obvious result be mapped to action (look-up table hurdle and sensing data, the data from the combination of sensing data, the threshold value that is associated, action task obtains need the data of execution specific action to be associated; This specific action comprise the management medicine, with this ad hoc fashion adjustment bed and by for example communicating by letter to generate alarm with destination via phone, IP address, Email).Processing is learnt to improve constantly from the data of monitoring by system.
Study processor 25 is processed the patient data that the training data group is learnt the model of statistical knowledge, this statistical knowledge comprises the patient's particular data about patient's present situation (normality) in complexity, multidimensional, leap time and space, and this study processor 25 is monitored the event of the medical science decision that may indicate " unusually " situation and need to make as response.The activation of the temperature of system by changing bed, back/pedal position, message function changes patient's environment, thus control and improvement Medical situation or patient's comfortable parameter.System based on according to a plurality of forms by patient worn or be embedded in a large amount of sensor in the environment (bed, room) and extract about the information of patient's medical condition and the abnormality detection by the data-driven jointly utilizing expertise and for example classify with a class and detect variation in patient's medical condition.System comprises the user interface of the intervention (including but not limited to provide medicine) that realizes the mutual and care-giver in case of emergency between patient and the care-giver.System adopts intelligent assistant's (unit 107) network to come unusual situation and trend is carried out advanced processing and cloud storage, search, inquiry, schema-based are found, and adopts for telemedicine, remote diagnosis, remote programmable and the mutual connectivity to the health care personnel.
System adopts the efficient netted communication construction of robust, and it does not make system equipment can keep collaboratively connectivity in having the arranging of infrastructure support.For example, in the disaster area, patient is placed on the stretcher that system enables, and its collection, analyzes and acts on from patient and directly collect data.Each system equipment also is maintained to the connectivity of center system by the mesh topology that is created in the mode that cooperates by system equipment.Because these equipment person that not only shows as the data collection also shows as the data retransmission at the same time person is so such mesh topology is further processed the demand of wireless range.Therefore, each packet that generates from origin system equipment is jumped over the route of selecting the best available by running through some other system equipments.By equipment self automatically and independently carry out mesh topology establishment, configure and keep operation, and do not have any needs of human interaction.
Fig. 6 shows the flow chart of the processing of being carried out by patient monitoring and interfering system.In the step 602 of the beginning of following step 60 1 place, data processor 15 is in response to patient's medical condition of patient and (a) decision and (c) at least one in the available amount of training data of current sensor parameters value, (b) clinician in comparable medical science case, and selects adaptively a plurality of different sensors from available sensor.In one embodiment, data processor 15 is selected the patient parameter group of a plurality of different receptions from a plurality of different groups in response to the single parameter of a plurality of different parameters surpasses predetermined threshold value.Sensor comprises for the chemical sensor of the chemical parameters of sensing body fluid and a plurality of different patient parameter group that receives and comprises chemical parameters.Sensor also comprises the sensor that is positioned at least one following position: (a) mattress, (b) medicated pillow and (c) supporting member of bed comprise sensor and protein group or the genomic expression sensor of metabolic system association.Sensor comprises for detection of at least one microphone and the signal data of automatically analyzing the sound that expression detects the data processor that audio parameter is provided in breathing, heart beating and the stomach sound, and the patient parameter group of a plurality of receptions comprises this audio parameter.Sensor also comprise for detection of pulse, tremble with onste at least one vibrating sensor and the signal data of automatically analyzing the vibration that expression detects provide the data processor of the parameter that obtains from vibration and the patient parameter group of a plurality of different reception to comprise the parameter that obtains from vibration.Sensor comprises that the patient parameter group for the sign of life sensor of at least one of sense blood pressure, blood oxygen saturation SPO2, ECG signal and temperature and a plurality of different reception comprises the sign of life parameter.
In step 605, interface 27 receives the data of a plurality of different parameters of expression from a plurality of different sensors, these a plurality of different sensors comprise the sensor (pressure transducer that comprises heart rate sensor, respiration pickup and indication bed pressure spot) that is attached to patient in the sick bed neutralization.The bed pressure spot comprise tighten, at least one in can compressed partial high pressure force of body position and tissue.Step 607 learning processor 25 in response to (i) from the patient data of the available record of sensor amount with (ii) from the patient data's of the available record of sensor the type at least one, from a plurality of difference in functionalitys, select adaptively to be used for determining (a) normal range and (b) at least one function of abnormal ranges by the study processor adopting for a plurality of different patient parameter groups that receive.Normal scope be from have with the similar population statistics of patient situation (comprise age, body weight, highly, sex, conceived state) and the patient population of similar medical condition obtain.Training data can both come from this patient (catching particular condition) and also come from other patients (catch common scenarios, healthy and unusual both) and promote faster multicategory classification and diagnosis.The patient data's of this record type comprises with Types Below, comprises normal and healthy patient sensor reading and unusual patient sensor reading.These a plurality of different functions comprise (a) class support vector machines, (b) class interconnection vector machine and (c) at least two in the multiclass interconnection vector machine.Study processor 25 is learnt and is fed into to upgrade this study from supervision and the data of new case from case.But not study in diagnostic mode, and the just application of study and being in the production model, processor 25 for example comprises grader, evaluator, diagnostor and treatment specifier in one embodiment.
In step 610, study processor 25 is by record patient parameter value within a period of time and use in the parameter value of analytic record selected function when determining their scope, determines the normal range of the patient parameter group of different receptions for patient.Data processor 15 determines that the patient parameter group of these different receptions surpasses determined normal range and determines and in response to the criticality of the patient parameter of the type of the parameter in this group and patient's medical record information and different reception, select adaptively the action that will be performed in response to this in step 613.A plurality of preconcerted operations comprise: initiate to adjust sick bed, change the medicine that gives patient, to worker's alarm patient parameter change, as indicated by the clinician labelling from the parameter of sensor and labelling from the parameter of sensor in order in training, use.Action also comprise rotate automatically that patient supports to breathe, raises back or foot, medicine is provided, reminds patient and monitoring ingestion of medicines amount and in environment confusion, undermanned (such as the disaster area) arrange treatment by precedence.The processing of Fig. 6 stops at step 631 place.
Processor used herein be for execution be stored in the machine-instructions on the computer-readable medium in case execute the task and can comprise hardware and firmware any one or the equipment of combination.Processor can comprise that also storage is for the memorizer of the executable machine readable instructions of executing the task.Processor uses for executable program or information equipment by manipulation, analysis, modification, conversion or transmission information, and/or by information router is arrived outut device, acts on information.Processor can use or comprise the ability of computer, controller or microprocessor, for example, and arranges processor with executable instruction and can't help the special function that general computer carries out with execution.Processor can with any other processor coupling (but on electricity and/or comprise execution unit), realized the mutual and/or communication between them.Computer program instructions can be loaded onto on the computer (comprise and be not limited to general purpose computer or special-purpose computer or other for generation of the blood processor able to programme of machine), so that the computer programming instruction of carrying out at computer or other blood processor able to programme creates the mode that is used for realizing in the specific function of (one or more) piece of (one or more) flow chart.User interface processor or maker are known elements, comprise that electronic circuit or software or the combination of the two are used for generating displayed map picture or their part.User interface comprises the displayed map picture of the user interactions of one or more realizations and processor or miscellaneous equipment.
As used herein, executable application comprises for for example in response to user instruction or input and arrange code or the machine readable instructions of the function that processor realizes being scheduled to (such as the function of operating system, function that context data obtains system or the function of out of Memory processing system).Executable program is that code snippet or machine readable instructions, subprogram or other are used for carrying out the part that the different code section of one or more specific processing maybe can be carried out application.These processing can comprise receive input data and/or parameter, executable operations and/or carry out function and be provided as result's output data and/or parameter in response to the input parameter that receives on the input data that receive.As used herein, graphic user interface (GUI) comprises one or more by video-stream processor generation and realization and the displayed map picture of the user interactions of processor or miscellaneous equipment and data acquisition and the processing capacity that is associated.
UI comprises that also executable program maybe can carry out application.Executable program maybe can be carried out and use the signal that the domination video-stream processor generates expression UI displayed map picture.These signals are fed into the display device that shows for the image of being watched by the user.Executable program maybe can be carried out application and also receive signal from user input device (allowing the user that the device of data is provided to processor such as keyboard, mouse, light pen, touch screen or any other).Maybe can carry out under the control of application at executable program, processor is in response to the signal manipulation UI displayed map picture that receives from input equipment.Under this mode, the user uses input equipment and displayed map picture mutual, the user interactions of realization and processor or miscellaneous equipment.Can be in response to user command automatically or carry out fully or partly function and the treatment step of this paper.In response to executable instruction or equipment operating and carry out the activity (comprising step) that can automatically perform, need not the direct promotional activities of user.
The system of Fig. 1-6 and processing are not exclusive.Can obtain other system, processing and program command table according to principle of the present invention and finish identical target.Although described the present invention with reference to specific embodiment, should be understood that, the embodiment that this paper illustrates and describes and variation only are for illustrative purposes.Without departing from the scope of the invention, can be by the modification of those of skill in the art to current design.System self-adaption ground selects one group of sensing data, study functional processor to come sensing data that treatment of selected selects to determine the normal patient scope of data of sensing data, and system responses surpasses the normal range of determining and the action that adaptively selection will be carried out in sensing data.In addition, in interchangeable embodiment, process and use on one or more (for example, the distributed) treatment facility on the network of the unit that can be positioned in linked, diagram 2.The function that provides in Fig. 1-6 and any in the step can use hardware, software or the combination of the two to realize.The claim key element of herein interpreted under the regulation of the 6th section of 35 U.S.C. 122 not, unless use phrase " be used for ... device " put down in writing clearly this element.
Claims (22)
1. a patient monitoring and interfering system comprise:
Interface is used for receiving the data that represent a plurality of different parameters from a plurality of different sensors, and described a plurality of different sensors comprise the sensor and the sensor that is attached to patient in sick bed, and described sensor comprises:
Heart rate sensor,
Respiration pickup, and
The pressure transducer of indication bed pressure spot;
The study processor is used for by record patient parameter value within a period of time and analyzes the parameter value that records determining their scope, determines the normal range of a plurality of described different patient parameter groups that receive for described patient; And
Data processor, be used for to determine that this different patient parameter group that receives surpasses determined normal range and determines and in response at the type of the parameter of this group and described patient's medical record information in response to this, initiation is to the adjustment of sick bed with lower at least one:
(a) change the medicine that gives patient, and
(b) change to worker's alarm patient parameter.
2. according to claim 1 system, wherein,
Described data processor surpasses predetermined threshold value and select described a plurality of described different patient parameter groups that receive from a plurality of different group in response to the single parameter of described a plurality of different parameters.
3. according to claim 1 system, wherein,
Described sensor comprises for the chemical sensor of the chemical parameters of sensing body fluid and described a plurality of described different patient parameter group that receives and comprises described chemical parameters.
4. according to claim 1 system, wherein,
Described sensor comprises the sensor that is positioned at least one following position: (a) mattress, (b) medicated pillow and (c) supporting member of bed.
5. according to claim 1 system, wherein,
Described sensor comprises for detection of at least one microphone and the signal data of automatically analyzing the sound that expression detects the described data processor that audio parameter is provided in breathing, heart beating and stomach sound or the vibration, and described a plurality of described different patient parameter group that receives comprises described audio parameter.
6. according to claim 1 system, wherein,
Described sensor comprise for detection of pulse, tremble and onste at least one (a) vibrating sensor and (b) video camera, the signal data that described data processor is automatically analyzed the vibration that expression detects provides the parameter and the described a plurality of described different patient parameter group that receives that obtain from vibration to comprise the described parameter that obtains from vibration.
7. according to claim 1 system, wherein,
Described sensor comprises for the sign of life sensor of at least one of sense blood pressure, blood oxygen saturation SPO2, ECG signal and temperature and described a plurality of described different patient parameter group that receives and comprises the sign of life parameter.
8. according to claim 1 system, wherein,
Described bed pressure spot comprise tighten, at least one in can compressed partial high pressure force of body position and tissue.
9. according to claim 1 system, wherein,
Described sensor comprises the sensor that metabolic system is associated, and
Described data processor is automatically initiated with lower at least one item:
A) automatically rotate patient and support to breathe,
B) automatically raise patients back or foot,
C) automatically provide medicine, and
D) determine in response to described, automatically arrange treatment by precedence.
10. according to claim 1 system, wherein,
Described sensor comprises protein group or genomic expression sensor.
11. system according to claim 1, wherein,
Described normal scope be from have with the similar population of patient statistics situation and similarly the patient population of medical condition obtain, described demographics comprise age, body weight, highly, sex, conceived state.
12. system according to claim 1, wherein,
Described data processor is in response to patient's medical condition of patient and (a) decision and (c) at least one in the available amount of training data of current sensor parameters value, (b) clinician in comparable medical science case, and selects adaptively described a plurality of different sensor from predetermined available sensor.
13. system according to claim 1, wherein,
Described study processor, is selected to be used for determining (a) normal range and (b) at least one function of abnormal ranges by described study processor adopting from a plurality of different predetermined functions for described a plurality of described different patient parameter groups that receive from the patient data of the available record of sensor amount with (ii) from the patient data's of the available record of sensor the type at least one in response to (i) adaptively.
14. system according to claim 13, wherein,
The patient data's of described record type comprises type, comprises normal and healthy patient sensor reading and unusual patient sensor reading.
15. system according to claim 13, wherein,
Described a plurality of different function comprises (a) class support vector machines, (b) class interconnection vector machine and (c) at least two in the multiclass interconnection vector machine.
16. system according to claim 13, wherein,
Described data processor surpasses determined normal range in response to definite described a plurality of described different patient parameter groups that receive, and described data processor is selected the action that will be performed in response to lower at least one adaptively: (a) from patient data's amount of the available record of sensor, (b) from the patient data's of the available record of sensor type and (c) type of selected function.
17. system according to claim 13, wherein,
Described data processor surpasses determined normal range in response to definite described a plurality of described different patient parameter groups that receive, and described data processor is selected the action that will be performed in response to lower at least one adaptively from a plurality of preconcerted operations: (a) criticality of the described different patient parameter that receives of patient's medical condition and (b).
18. system according to claim 17, wherein,
Described a plurality of preconcerted operations comprise: initiate to adjust sick bed, change the medicine that gives patient, to worker's alarm patient parameter change, as indicated by the clinician labelling from the parameter of sensor and labelling from the parameter of sensor in order in training, use.
19. system according to claim 1 comprises:
Link the mesh communication network of described sensor and described system, described network makes described system equipment can keep collaboratively connectivity.
20. a patient monitoring and interfering system comprise:
Interface is used for receiving the data that represent a plurality of different parameters from a plurality of different sensors, and described a plurality of different sensors comprise the sensor in sick bed and are attached to patient's sensor;
The study processor is used for by record patient parameter value within a period of time and analyzes the parameter value that records determining their scope, determines the normal range of a plurality of described different patient parameter groups that receive for described patient; And
Data processor, be used for surpassing determined normal range in response to definite described a plurality of described different patient parameter groups that receive, from a plurality of different preconcerted operations, select adaptively the action that will be performed in response to lower at least one: (a) patient's medical condition, (b) criticality of the described different patient parameter that receives, described action comprise (i) initiate to adjust sick bed, (ii) change give patient's medicine and (iii) change to worker's alarm patient parameter at least one.
21. a patient monitoring and interfering system comprise:
Interface is used for receiving the data that represent a plurality of different parameters from a plurality of different sensors, and described a plurality of different sensors comprise the sensor in sick bed and are attached to patient's sensor;
The study processor is used for
In response to (i) from patient data's amount of the available record of described a plurality of different sensors with (ii) from the patient data's of the available record of described a plurality of different sensors the type at least one, from a plurality of different predetermined functions, select adaptively to be used for to determine (a) normal range, (b) abnormal ranges and (c) at least one function of the unusual combination of scope for described a plurality of described different patient parameter groups that receive, and
By record patient parameter value within a period of time and use and analyze the parameter value that records selected function when determining their scope, determine normal range or the degree of a plurality of described different patient parameter groups that receive for described patient; And
Data processor, surpass determined normal range in response to definite described a plurality of described different patient parameter groups that receive, from a plurality of different preconcerted operations, select adaptively the action that will be performed in response to lower at least one: (a) from patient data's amount of the available record of sensor, (b) from the patient data's of the available record of sensor type and (c) type of selected function.
22. a method that is used for patient monitoring and intervention comprises following activity:
Receive the data of a plurality of different parameters of expression from a plurality of different sensors, described a plurality of different sensors comprise the sensor and the sensor that is attached to patient in sick bed, and described sensor comprises:
Heart rate sensor,
Respiration pickup, and
The pressure transducer of indication bed pressure spot;
By record patient parameter value within a period of time and analyze the parameter value that records determining their scope, determine the normal range of a plurality of described different patient parameter groups that receive for described patient; And
Determine that this different patient parameter group that receives surpasses determined normal range and determines and in response to the type of the parameter in this group and described patient's medical record information in response to this, initiation is to the adjustment of sick bed with lower at least one:
(a) change the medicine give patient and
(b) change to worker's alarm patient parameter.
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| US13/718023 | 2012-12-18 |
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