WO2016030892A1

WO2016030892A1 - Remote patient monitoring methods

Info

Publication number: WO2016030892A1
Application number: PCT/IL2015/050859
Authority: WO
Inventors: Joshua Schulman; Anya ELDAN
Original assignee: Neuro-Tech Solutions Ltd.
Priority date: 2014-08-27
Filing date: 2015-08-27
Publication date: 2016-03-03

Abstract

A method comprising: (a) monitoring one or more performance characteristics of a subject using a monitor program installed on a Personal Digital Accessory (PDA) used by said subject to generate a data set, and (b) automatically reporting said data set to a remote location using said monitor program.

Description

Remote Patient Monitoring Methods

FIELD OF THE INVENTION

Various described embodiments are in the field of telemedicine.

BACKGROUND OF THE INVENTION

Disorders of attention (e.g. attention deficit hyperactivity disorder or ADHD) affect over 5% of children and adolescents worldwide according to a comprehensive meta-analysis by Polanczyk et al. (Am. J. Psychiatry (2007) 164:942-948) making ADHD the most common childhood onset psychiatric disorder. Furthermore, it has been estimated that approximately 2/3 of ADHD cases are not resolved in adulthood, leading to a worldwide pooled prevalence of ADHD of 2.5% (Faraone et al. (2006) Psychol. Med. 36:159-165).

Computerized Continuous Performance Test (CPT) systems for ADHD, in which a subject is asked to respond to a test stimulus which appears on the computer's screen or other output device, are known.

In general, CPTs are neuropsychological tests that measure a person's sustained and selective attention. Sustained attention refers to the ability to maintain a consistent focus on a continuous activity or stimuli. Selective attention refers to the ability to focus on relevant stimuli and ignore competing stimuli. CPTs include, but are not limited to Integrated Visual and Auditory CPT (IVA-2), Test of Variables of Attention (T.O.V.A.) and the Conners' CPT-II and CPT-III. These CPTs are often used as part of a battery of tests evaluate executive functioning or the capacity of a subject to sort and manage information. In addition CPTs such as QbTest and Quotient, combine attention and impulsivity measures with motion tracking analysis. These types of CPTs provide objective information regarding the three core symptoms of ADHD: hyperactivity, inattention and impulsivity. CPTs are also used specifically to support or to help rule out a diagnosis of Attention Deficit Disorder.

T.O.V.A. measures a person's attention while screening for ADHD. The test is typically 21.6 minutes long, and is presented as a computer game. The test measures a number of variables involving the test takers response to visual and/or auditory stimulus. These measurements are then compared to the measurements of a group of people without attention disorders who took the T.O.V.A.

T.O.V.A. is reported to identify 87% of individuals without ADHD, 84% of non- hyperactive ADHD, and 90% of hyperactive ADHD subjects.

SUMMARY OF THE INVENTION

A broad aspect of the invention relates to monitoring of ADHD subjects.

One aspect of some embodiments of the invention relates to use of a personal digital accessory (PDA; e.g. smart-phone, tablet, APPLE watch, GOOGLE Watch, PEBBLE, FITBIT, BASIS or GOOGLE GLASS) to acquire clinically relevant data on an ADHD subject during routine use of the PDA. For purposes of this specification and the accompanying claims the term the term "performance characteristic" indicates a measure of the way that a user interacts with a program or "App" their PDA. Examples of performance characteristics include, but are not limited to, text input rate, text error rate, dwell time and saccade frequency.

Another aspect of some embodiments of the invention relates to use of existing

PDA hardware to acquire clinically informative data. According to various exemplary embodiments of the invention, the hardware includes an accelerometer and/or microphone and/or speaker(s) and/or touchscreen and/or camera and/or WiFi or GPS receiver.

Another aspect of some embodiments of the invention relates to providing raw or processed signal data from motion-sensing hardware in the PDA to the monitor program. Examples of motion- sensing hardware include, but are not limited to, accelerometers and/or magnetometers and/or gyroscopes.

Another aspect of some embodiments of the invention relates to monitoring of subject activity during performance of routine PDA activities to acquire clinically informative data. Routine PDA activities include, but are not limited to, text input (e.g. e- mail, SMS and instant messaging), gaming, voice calls, reading (e.g. e-books, RSS feeds, web pages, e-mail or messages) and audio listening (e.g. music or audio books). In some exemplary embodiments of the invention cache and/or log file data is collected and/or created and/or analyzed. This is fundamentally different from CPT type tests.

Another aspect of some embodiments of the invention relates to installation of data collection software (DCS) on the PDA. In some embodiments the DCS gathers data on body movement and/or voice features (e.g. interruption frequency during conversation) and/or text input rate and/or text error rate and/or length and/or structure of textual inputs and/or application usage (e.g. dwell time and/or frequency of switching) and/or reaction time to onscreen stimuli (e.g. pop-up windows) and/or audio alerts and/or eye movement (rate and/or focus).

For example, data on response to audio alerts is (in some embodiments) measured as time from an initial telephone ring to responding. According to various exemplary embodiments of the invention response is indicated by raising the device, or touching a button or screen object.

For example, response to visual stimulus is measured (in some embodiments) as time from an initial appearance of an on-screen alert to opening or dismissing the indicated content (e.g. an incoming message).

For either or both of the above examples ADHD is expected to cause an increase in response time variability (Tamm L, et al. Neurotherapeutics. 2012 Jul; 9(3): 500-508). Medication or other effective treatment is expected to manifest as a decrease in variability relative to baseline performance in the same subject.

For example, eye movement is measured (in some embodiments) as frequency of spontaneous saccade from the display screen. Normal individuals or medicated ADHD subjects (patients) are expected to exhibit less saccade activity than un-medicated ADHD subjects (patients).

Another aspect of some embodiments of the invention relates to automatic launching of a program. In some embodiments when the program is automatically launched data is automatically transmitted (e.g. a message is automatically sent or information is automatically uploaded to a server). In some embodiments the data is transmitted in the background (i.e. no message or upload window appears on the display screen of the PDA). Alternatively or additionally, in some embodiments a text field in an automatically generated message is populated. Text fields include "to:" (recipient), subject and body (of the message). Examples of programs useful in this context according to various exemplary embodiments of the invention include e-mail programs (e.g. G- MAIL, MICROSOFT OUTLOOK and YAHOO MAIL), text messaging programs (SMS and/or MMS), instant messaging programs (e.g. GOOGLE CHAT, MICROSOFT EVI and WHATSAPP) and cloud connection (e.g. XMPP based, for example, Google Cloud Messaging).

Another aspect of some embodiments of the invention relates to use of unique identifiers (UIDs) to protect confidential medical information transmitted over a network. For example, in some embodiments each subject is assigned a unique alphanumeric string or machine-readable symbol (e.g. bar-code or QR code). When automatic transmission of data pertaining to subject activity during performance of routine PDA activities occurs, the UID is provided in the message instead of the subject' name. Since the subject activity during performance of routine PDA activities is clinically informative, it can be viewed as confidential medical information. In some embodiments UIDs are automatically decoded to subject names by a computer (or server) operated by a health care provider (or institution).

It will be appreciated that the various aspects described above relate to solution of technical problems associated with monitoring of ADHD subjects without physical presence of caregivers/healthcare providers.

It will be appreciated that the various aspects described above relate to solution of technical problems associated with the provision of objective data concerning behavior of ADHD subjects with and/or without medication in real-life situations.

Alternatively or additionally, it will be appreciated that the various aspects described above relate to solution of technical problems related to patient compliance with medication schedules.

Alternatively or additionally, it will be appreciated that the various aspects described above relate to solution of technical problems related to preservation of patient confidentiality while transmitting medical information across an unsecure network.

In some exemplary embodiments of the invention there is provided a method including: (a) monitoring one or more performance characteristics of a subject using a monitor program installed on a Personal Digital Accessory (PDA) used by the subject to generate a data set, and (b) automatically reporting the data set to a remote location using the monitor program. In some exemplary embodiments of the invention, the monitoring includes collecting data generated by operation of one or more applications on the PDA by the subject. Alternatively or additionally, in some embodiments the monitoring includes collecting data from two or more PDAs associated with a single subject. Alternatively or additionally, in some embodiments the method includes collecting text input rate data from a virtual keyboard module in the PDA. Alternatively or additionally, in some embodiments the method includes collecting text error rate data from a virtual keyboard module in the PDA. Alternatively or additionally, in some embodiments the method includes collecting data pertaining to rate and multiplicity of text inputs from a virtual keyboard module in the PDA. Alternatively or additionally, in some embodiments the method includes collecting data pertaining to structure of text inputs from a virtual keyboard module in the PDA. Alternatively or additionally, in some embodiments the method includes collecting data pertaining to dwell time. Alternatively or additionally, in some embodiments the method includes collecting data pertaining to switching among applications. Alternatively or additionally, in some embodiments the method includes detecting initiation of a microphone out signal while an audio in signal is present during a telephone call on the PDA. Alternatively or additionally, in some embodiments the method includes logging duration of microphone out signal while an audio-in signal is present during a telephone call on the PDA. Alternatively or additionally, in some embodiments the method includes logging frequency of occurrence of the initiation. Alternatively or additionally, in some embodiments the method includes collecting data pertaining to reaction time to on-screen stimuli. Alternatively or additionally, in some embodiments the method includes issuing a camera-on signal to a front facing camera of the PDA without interfering with operation of an application being used by the user, capturing a series of frames of an eye or eyes of the user together with eyelid borders and identifying pupil positions relative to items onscreen and analyzing the frames to generate data pertaining to eye movement of the user while operating the application. Alternatively or additionally, in some embodiments the method includes issuing a camera-on signal to a front facing camera of the PDA without interfering with operation of an application being used by the user, capturing a series of frames an eye or eyes of the user together with eyelid borders and identifying pupil positions relative to screen or items on it and analyzing the frames to generate data pertaining to pupillary response and blink rate of the user while operating the application. Alternatively or additionally, in some embodiments the automatically reporting employs a cloud connection (e.g. XMPP-based connection). Alternatively or additionally, in some embodiments the automatically reporting employs a messaging program selected from the group consisting of an e-mail program, an SMS program, an MMS program and an instant messaging program. Alternatively or additionally, in some embodiments the method includes suppressing appearance of a window of the messaging program during the automatically reporting. Alternatively or additionally, in some embodiments the method includes automatically populating one or more text fields in the message. Alternatively or additionally, in some embodiments the method includes providing signal data from motion-sensing hardware in the PDA to the monitor program.

In some exemplary embodiments of the invention there is provided a method including: (a) monitoring one or more performance characteristics of a subject using a monitor program installed on a Personal Digital Accessory (PDA) used by the subject to generate a first data set during a first data collection period; and (b) monitoring the one or more performance characteristics of the subject during use of the PDA using the monitor program to generate a second data set during a second data collection period. In some exemplary embodiments of the invention, the method includes automatically reporting the first and second data sets to a remote location using the monitor program. Alternatively or additionally, in some embodiments the method includes automatically reporting the first and second data sets to a user of the PDA using the monitor program.

In some exemplary embodiments of the invention there is provided a method including: (a) deploying a monitor program on a Personal Digital Accessory (PDA) used by a subject; and (b) receiving data pertaining to one or more performance characteristics of the subject on a digital device. In some exemplary embodiments of the invention, the method includes decoding a unique identifier in the data to ascertain an identity of the subject. Alternatively or additionally, in some embodiments the method includes, integrating the data into a digital medical record of the subject.

Unless otherwise defined, all technical and scientific terms used herein have the same meaning as commonly understood by one of ordinary skill in the art to which this invention belongs. Although suitable methods and materials are described below, methods and materials similar or equivalent to those described herein can be used in the practice of the present invention. In case of conflict, the patent specification, including definitions, will control. All materials, methods, and examples are illustrative only and are not intended to be limiting. As used herein, the terms "comprising" and "including" or grammatical variants thereof are to be taken as specifying inclusion of the stated features, integers, actions or components without precluding the addition of one or more additional features, integers, actions, components or groups thereof. This term is broader than, and includes the terms "consisting of" and "consisting essentially of" as defined by the Manual of Patent Examination Procedure of the United States Patent and Trademark Office. Thus, any recitation that an embodiment "includes" or "comprises" a feature is a specific statement that sub embodiments "consist essentially of and/or "consist of the recited feature.

The phrase "consisting essentially of" or grammatical variants thereof when used herein are to be taken as specifying the stated features, integers, steps or components but do not preclude the addition of one or more additional features, integers, steps, components or groups thereof but only if the additional features, integers, steps, components or groups thereof do not materially alter the basic and novel characteristics of the claimed composition, device or method.

The phrase "adapted to" as used in this specification and the accompanying claims imposes additional structural limitations on a previously recited component.

The term "method" refers to manners, means, techniques and procedures for accomplishing a given task including, but not limited to, those manners, means, techniques and procedures either known to, or readily developed from known manners, means, techniques and procedures by practitioners of architecture and/or computer science.

Implementation of the method and system according to embodiments of the invention involves performing or completing selected tasks or steps manually, automatically, or a combination thereof. Moreover, according to actual instrumentation and equipment of exemplary embodiments of methods, apparatus and systems of the invention, several selected steps could be implemented by hardware or by software on any operating system of any firmware or a combination thereof. For example, as hardware, selected steps of the invention could be implemented as a chip or a circuit. As software, selected steps of the invention could be implemented as a plurality of software instructions being executed by a computer using any suitable operating system. In any case, selected steps of the method and system of the invention could be described as being performed by a data processor, such as a computing platform for executing a plurality of instructions. BRIEF DESCRIPTION OF THE DRAWINGS

In order to understand the invention and to see how it may be carried out in practice, embodiments will now be described, by way of non-limiting example only, with reference to the accompanying figures. In the figures, identical and similar structures, elements or parts thereof that appear in more than one figure are generally labeled with the same or similar references in the figures in which they appear. Dimensions of components and features shown in the figures are chosen primarily for convenience and clarity of presentation and are not necessarily to scale. The attached figures are:

Fig. la is a simplified schematic representation of a system according to some exemplary embodiments of the invention;

Fig. lb is a simplified schematic representation of a data transmission organization according to some exemplary embodiments of the invention;

Fig. lc is a simplified schematic representation of a data transmission organization according to some exemplary embodiments of the invention;

Fig. Id is a simplified schematic representation of an exemplary monitor program according to some exemplary embodiments of the invention;

Fig. le is a block diagram illustrating information flow and data processing within server 115 of Fig. la according to various exemplary embodiments of the invention;

Fig. 2 is a simplified flow diagram illustrating a method according to some exemplary embodiments of the invention;

Fig. 3 is a simplified flow diagram illustrating a second method according to some exemplary embodiments of the invention; and

Fig. 4 is a simplified flow diagram illustrating a third method according to some exemplary embodiments of the invention.

DETAILED DESCRIPTION OF EMBODIMENTS

Embodiments of the invention relate to systems and methods for remote data gathering.

Specifically, some embodiments of the invention can be used to gather data pertaining to performance characteristics of a user of a personal digital accessory (PDA) The principles and operation of systems and/or methods according to exemplary embodiments of the invention may be better understood with reference to the drawings and accompanying descriptions. Before explaining at least one embodiment of the invention in detail, it is to be understood that the invention is not limited in its application to the details set forth in the following description or exemplified by the Examples. The invention is capable of other embodiments or of being practiced or carried out in various ways. Also, it is to be understood that the phraseology and terminology employed herein is for the purpose of description and should not be regarded as limiting.

System overview

Fig. la is a simplified schematic representation of a system for remote patient monitoring indicated generally as 100, according to some exemplary embodiments of the invention. Depicted exemplary system includes a plurality of Personal Digital Accessories (PDA) 110 and a plurality of medical service providers 120. For clarity of presentation a single PDA 110 and a single service provider 120 are depicted although in actual use system 100 typically includes a large number of service providers 120 and a large number of PDAs 110 each of which belongs to a particular subject in the care of service provider 120. Although PDA 110 is depicted as a smartphone or tablet, in other exemplary embodiments of the invention, is a wearable device. In some embodiments a smartphone or tablet linked to a wearable device function as a single PDA 110.

System 100 employs a monitor program installed on each of PDAs 110. In some embodiments the monitor program includes data collection software (DCS) and/or data transmission software (DTS).

According to various exemplary embodiments of the invention the DCS is designed and configured to monitor various signals going to/from specific hardware components of PDA 110 and/or to collect data from various caches and/or buffers in PDA 110. For example, data on text entry error rate is collected in some embodiments by counting "keystrokes" from a virtual keyboard and computing the frequency with which automatic corrections which replace typed characters are activated (e.g. number of replacements/ 100 words).

In the depicted embodiment, DTS gathers collected data and transmits it as a data set 112. According to various exemplary embodiments of the invention data set 112 is transmitted either directly to medical service provider 120 or to a server 115. In those embodiments which employ a server, data set 116 transmitted to medical service provider 120 is either identical to data set 112 or is processed to make evaluation by a medical professional easier.

According to various exemplary embodiments of the invention medical service provider 120 is an individual practitioner or an institution. In some embodiments service provider 120 incorporates 121 the data (112 and/or 116) into a digital medical record (DMR) 122 of a subject associated with a specific PDA 110.

Alternatively or additionally, in some embodiments server 116 delivers processed data set 116 to PDA 110 for display to a user of the PDA and/or to be stored for later retrieval by service provider 120 (e.g. during a subsequent visit to a doctor). In some embodiments PDA 110 processes data set 112 to generate processed data 116 (see 116 surrounded by dashed lines).

Exemplary organization of data for transmission

Examples of programs useful for transmitting data sets 112 and/or 116 include, but are not limited to cloud connection (e.g. XMPP-based, for example GOOGLE Cloud Messaging), e-mail programs (e.g. G-MAIL, MICROSOFT OUTLOOK and YAHOO MAIL), text messaging programs (SMS and/or MMS) and instant messaging programs (e.g. GOOGLE CHAT, MICROSOFT IM and WHAT'S APP). In some embodiments which employ server 115, XMPP-based cloud connections contribute to ease of implementation. In some embodiments in which data set 112 is transmitted to an individual serving as service provider 120 message based delivery contributes to ease of implementation.

GOOGLE (GCM) cloud messaging is a framework including client and server functionalities that can be included in an application. GCM is configured to send data (e.g. 112) to a server (e.g. 115) specified by user. The server provides responses (e.g. 116) GCM does not display message content. According to GCM based embodiments, there is a service running which collects data pertaining to one or more performance characteristics and/or other data from PDAs 110 and periodically sends it to server 115 for analysis. In this conception, each of PDAs 110 is a user client.

For example, GCM supports the definition of a Task class, which in this case, would activate collection of data from various hardware components and/or software applications on PDA(s) 110. In some embodiments which employ GCM, dataset 1112 is split into several transmissions to conform to GCM size restrictions on the size of a transmitted "message".

GCM also supports Periodic Task Class functionality which allows data (e.g. 112) to be uploaded according to schedule (e.g. weekly, daily, twice per day, three times per day. six times per day, hourly or intervening or greater frequencies).

Fig. lb is a simplified schematic representation of a data transmission organization according to some exemplary embodiments of the invention indicated generally as 112. Depicted exemplary data set 112 includes a "to" field 130 indicating an intended recipient. According to various exemplary embodiments of the invention field 130 is formatted as an e-mail address, a telephone number, a URL or an IP address. Depicted exemplary data set 112 includes a "message ID" field 132 identifying the person associated with a specific PDA 110 (e.g. their name and/or an insurance policy number and/or a unique identifier (UID) assigned to conceal their identity (e.g. alphanumeric string and/or barcode and/or QR code). In some embodiments message ID field 132 also includes temporal information (e.g. date(s) and/or times(s)).

Depicted exemplary data set 112 includes a "message data" field 133 populated with data relating to one or more performance characteristics of the person referred to in message ID fields 132.

Fig. lc is a simplified schematic representation of a data transmission organization according to some exemplary embodiments of the invention indicated generally as 116. Message ID field 132 is as described above for 112. The "to" field 131 indicates service provider 120 and is formulated, according to various exemplary embodiments of the invention as is formatted as an e-mail address, a telephone number, a URL or an IP address. In some embodiments "message data" field 135 contains a processed form of the data in 133. In some embodiments the processed data contributes to ease of medical diagnosis (e.g. by presenting one or more performance characteristics as normalized scores and/or in a graphical format (e.g. performance characteristic as a function of time).

Overview of Exemplary PDA

Fig. Id is a simplified schematic representation of an exemplary monitor program

140. In some embodiments program 140 is installed or deployed in PDA 110 of Fig. la. According to depicted exemplary program 140, control module 144 instructs the clock 141 of PDA110 to provide an output signal to data set 112 so that every item added to the data set gets a time stamp. In some embodiments presence of time stamps contributes to an ability to calculate rates of various performance characteristics. As used here, clock includes calendar so that time stamps include dates.

In the depicted embodiment application manager 143 of PDA 110 communicates with control module 144 to operate camera 160. When control module 144 operates camera 160, frames from the camera are added to data set 112 (each frame with a time stamp). Alternatively or additionally, in some embodiments control module 144 suppresses appearance of the normal "viewfinder" output of camera 160 in favor of whatever application is currently running in the foreground in application manager 143 (i.e. camera operates in the background). According to various exemplary embodiments of the invention operation of camera 160 by control module 144 is triggered by appearance of designated applications as the "in use" application at application manager 143. For example, in some embodiments use of an internet browser, e-book reader or news program causes module 144 to launch camera 150.

In the depicted embodiment application manager 143 informs control module 144 when a phone call is in progress (e.g. using a mobile network or a voice over Internet protocol). According to exemplary program 140, application manager 143 provides data pertaining to speaker line in signal 180 (e.g. digital side of D/A converter) and microphone line out signal 181 (e.g. digital side of A/D converter) to control module 144 for inclusion in data set 112. In the drawing this communication is indicated as being routed through application manager 143 although other routing configurations are employed in other embodiments. In some embodiments voice like signals are identified by a specific frequency range (e.g. 100-3500Hz). In some embodiments assignment of a frequency range contributes to a reduction in false positives from background noise.

US20080234558 Al describes recognition of speech in an audio signal and is fully incorporated herein by reference for all that it contains.

ANDROID operating system (OS) (GOOGLE) includes a speech recognizer function that allows programs to access to the microphone stream to identify when a speaker starts and finishes. Alternatively or additionally, ANDROID OS has a Media Recorder API that allows audio to be captured. In some embodiments the speech recognizer and/or media recorder apply time stamps. In some embodiments the time stamp contributes to an ability to detect and/or map and/or log occurrences (and/or duration) of subject operating PDA 110 speaking wile one or more other participants in the call is speaking (as evidence by a signal to the speakers of PDA 110).

In some embodiments occurrence of interruptions by a user of PDA 110 during speech of another party during a phone conversation serves as an indicator of impulsive behavior, a characteristic of ADHD. In depicted exemplary program 140, control module 144 instructs the virtual keyboard 150 module of PDA 110 to provide information on certain keystrokes to dataset 112. According to various exemplary embodiments of the invention the keystrokes include delete 151 and/or done or send 152 and/or a selection from an auto-correct 153 menu suggestion.

In some embodiments control module 144 instructs motion sensor 170 to provide an output signal to data set 112.

According to various exemplary embodiments of the invention control module

114 transmits data set 112 to a remote location either periodically (e.g. using a message program) or on an on-going basis (e.g. using a cloud based communication system). In those embodiment which employ a messaging system control module 144 launches the relevant messaging program, suppresses appearance of a message window (i.e. program runs in the background) and auto-populates the relevant fields.

Exemplary server

Fig. le is a block diagram illustrating information flow and data processing within server 115 of Fig. la according to various exemplary embodiments of the invention.

Fig. le indicates that incoming data set 112 is analyzed by an analytic module 150. In the depicted embodiment analytic module 150 compares data set 112 with personal database 140 and/or population database 142.

Personal database 140 contains historic information on performance characteristics in data set 112 for the specific person that is the subject of data set 112.

Population database 142 contains information on performance characteristics in data set 112 for a large number of people that are not the subject of data set 112. In some embodiments population database 142 contains data only for people that have no current medical diagnosis. In some embodiments, population database 142 contains data also for people that have one or more current medical diagnoses. For example, in some embodiments population database 142 contains data for a "normal" population, an ADHD population and an Asperger's syndrome population.

In some embodiments comparison is accomplished by employing basic statistical methods such as Z-score comparing specific signals at various time points. Alternatively or additionally, in some embodiments analytic Module 150 integrates features of incoming data 112 to create a unique user profile. According to these embodiments analogous profiles are used in population DB 140 and personal DB 142. In some embodiments these profiles are created with the help of sensor fusion algorithms such as Bayesian networks, Kalman filters or other techniques suitable for time-series or single- trial analysis and/or employ machine learning and data mining techniques such as (for example) self-organizing maps.

Based on the results of this comparison analytic module 150 provides an output in one or more if the following formats: percentile score 143; diagnosis 160 (e.g. ADHD positive), graph 150, or personal index score 141. According to various exemplary embodiments of the invention one or more of these outputs is incorporated into processed data set 116.

According to some embodiments of the invention percentile score 143 includes statistical information (e.g. 1.5 standard deviations above the mean of the normal population).

According to some embodiments of the invention graph 150 depicts performance characteristics from data set 112 in comparison to the average of a normal population and/or in comparison to the average of a population with a specific diagnosis (e.g. ADHD) and/or in comparison to historic performance data from the same person (retrieved from DB 140).

According to some embodiments of the invention personal index score 141 presents performance characteristics from data set 112 as a relative statistic based upon historic performance data from the same person (retrieved from DB 140). For example, 35% improvement since last year and/or 6% improvement since last month.

First Exemplary Method Fig. 2 is a simplified flow diagram illustrating a method of remote data collection and reporting according to some exemplary embodiments of the invention indicated generally as 200.

In the depicted embodiment, method 200 includes monitoring 210 one or more performance characteristics of a subject using a monitor program installed on a Personal Digital Accessory (PDA) used by the subject to generate a data set (e.g. 112) As indicated above the monitor program includes DCS. In some embodiments monitoring 210 includes collecting data from two or more PDAs associated with a single subject. For example, in some embodiments a single subject use a smart phone (e.g. IPHONE) and a bracelet device (e.g. APPLE watch). In some embodiments of the invention the two or more PDAs each transmit data 112 in parallel. In some embodiments a primary PDA (e.g. a smartphone) receives a signal from a secondary PDA (e.g. a bracelet device) and incorporates data from that signal into data 112. According to various exemplary embodiments of the invention the signal is transmitted via a wired connection or a wireless connection.

Depicted exemplary method 200 also includes automatically reporting 220 the data set to a remote location using the monitor program.

According to various exemplary embodiments of the invention the PDA operates in ANDROID, IOS or any other operating system.

Depicted exemplary method 200 also includes (as part of said monitoring) collecting 230 data generated by operation of one or more applications on the PDA by the subject. For example, in some embodiments 230 includes collecting text input rate data 232 from a virtual keyboard module in the PDA by the monitor program.

For example, in some embodiments 230 includes collecting text error rate data 233 from a virtual keyboard module in the PDA by the monitor program. For example, in some embodiments the number of corrections executed by the keyboard program is logged. In some embodiments use of the backspace key indicates a correction. Correlating backspace with correction obviates a need for text analysis. In some embodiments calculation of error rate includes transmission of user keystrokes to server 115. Existing applications which include this capability are, for example, Swiftkey, Fleksy and Swype.

For example, in some embodiments 230 includes collecting data pertaining to rate and/or multiplicity of text inputs 234 from a virtual keyboard module in the PDA by the monitor program. This refers to the rate with which new text messages (or-e-mails) are sent and/or the number of texts/mails sent per unit time (e.g. per day or per hour). In some embodiments the impulsive character of ADHD contributes to sending more messages at a faster rate than non-ADHD or treated ADHD.

For example, in some embodiments 230 includes collecting data pertaining to structure 235 of text inputs from a virtual keyboard module in the PDA by the monitor program. In some embodiments this is also done with virtual keyboard transmission to server 115 as described hereinabove. Structure indicates message length. In some embodiments untreated ADHD is correlated to shorter messages.

For example, in some embodiments 230 includes collecting data pertaining to dwell time 236. Dwell time has two components, each of which correlates to sustained attention.

The first component is application dwell time. Application dwell time refers to the overall time a user maintains a particular application in the foreground with periodic interaction such as scrolling or activating links. Dwell time (e.g.) 236 is reported as part of date set 112. In some embodiments server 115 and/or analytic module 150 convert the raw data into an attentional metric for application dwell time which is reported as part of dataset 116.

In some embodiments collection 230 of dwell time data 236 includes recording foreground processes in the operating system as part of data set 112. Alternatively or additionally, in some embodiments analytic module 150 calculates the number of times the foreground application is changed in a given time window and compares this number of changes to a comparable individual historical (e.g. using DB 140) or group metric (e.g. using DB 142) of changes under similar conditions.

The second component is item specific dwell time. Item specific dwell time refers to a sustained reading attention for a content item (e.g. news article or story).

In some embodiments analytic module 150 calculates a range of expected item specific dwell times for a content item based on individual and group history of reading similar content items (e.g. using DBS 140 and/or 142). According to various exemplary embodiments of the invention similar content items are defined by one or more content parameters such as, for example, publication name, author name and word count. According to various exemplary embodiments of the invention content parameters are included in data set 112 delivered to analytic module 150.

In some embodiments content items are presented in a web browser. In some embodiments presentation of content items in a web browser contributes to a reduction in the number of baseline comparison points since the number of potential articles is long. In some embodiments commonly read content items presented in a browser are flagged for use (e.g. first headline article on a popular news site) while other less popular content items are ignored. In some embodiments use of preselected content items from selected sites or content providers contributes to an ability to provide a more robust dataset 112.

In some embodiments analytic module 150 calculates whether the subject keeps the given content item visible (defined by scrolling, no change in URL or other identifier and application maintained in the foreground) for a time period which deviates significantly from the expected item specific dwell time. According to various exemplary embodiments of the invention the deviation is either actual dwell time greater than expected dwell time or actual dwell time less than expected dwell time.

In some embodiments analytic module 150 analyzes application dwell time and item specific dwell time together. For example, if a user launches a content application, and spends 15 minutes on the application during one session but an average of 15 seconds on each item presented within the application, application dwell time is 15 minutes but the item specific dwell time is 15 seconds. In some embodiments identification of content items within an application is made by monitoring a switch in URL. For example, if the application is a news reader, 15 minutes application dwell time may be normal, but 15 seconds dwell time per news article may indicate an attention deficit disorder.

In some embodiments comparisons are made on a per-app or per-site basis. Optionally, this contributes to a reduction in variability. Since providers (e.g. news or magazines) tend to have typical article lengths, this policy contributes to a reduction in confounds based on site design.

For example, in some embodiments 230 includes collecting data pertaining to switching 237 among applications. Switching 237 refers to how many times in the course of a given time window, e.g. a session defined by screen-on, a subject switches from one application in the foreground to another. For example, ANDROID OS contains an Activity Manager that allows programmers to poll it and receive the Foreground Package information. In some embodiments collection of data 237 includes polling of foreground package information conducted at regular intervals with time/date stamps. According to various exemplary embodiments of the invention the intervals arte daily, every 8 hours, every four hours, every hour, every 15 minutes, every 5 minutes, every minute or intermediate or shorter intervals.

For example, in some embodiments 230 includes collecting data pertaining to reaction time 238 to on-screen stimuli. On-screen stimuli include, but are not limited to dialog boxes indicating arrival of email or SMS. In some embodiments an untreated/uncontrolled ADHD subject is more likely to respond to dialog boxes so that faster reaction correlate to the disease. In some embodiments data 238 is collected using one or more Activity parameters in the Notification Compat builder for ANDROID OS.

Alternatively or additionally, in some embodiments method 200 includes detecting 240 initiation of a microphone out signal while an audio in signal is present during a telephone call on the PDA. A microphone out signal while an audio in signal is present during a telephone call is indicative of one participant in the conversation interrupting the other. In some embodiments method 200 includes logging 242 duration of microphone out signal while an audio-in signal is present during a telephone call on the PDA. In some embodiments method 200 includes logging 244 frequency of occurrence of the initiation.

In some embodiments method 200 includes issuing a camera-on signal to a front facing camera of the PDA without interfering with operation of an application being used by the user (i.e. the application remains active on the screen instead of the camera "view finder") and capturing a series of frames of an eye or eyes of the user together with eyelid borders and identifying pupil positions relative to items onscreen. This facilitates analyzing the frames to generate data pertaining to eye movement 254 of the user while operating said application. Alternatively or additionally, this facilitates analyzing the frames to generate data pertaining to pupillary response 256 and blink rate 257 of the user while operating said application. In some embodiments monitoring of eye movement 254 and/or pupillary response and/or blink rate 257 is undertaken by the monitoring program when applications requiring sustained attention (e.g. Web browser or e-book reader or news application) are in operation. In some embodiments reporting 220 employs a messaging program selected from the group consisting of an e-mail program, an SMS program, an MMS program and an instant messaging program. Optionally, the monitoring program suppresses appearance of a window of the messaging program during said automatically reporting. Background sending of message makes the reporting transparent to a user of PDA 110.

Alternatively or additionally, in some embodiments method 200 includes automatically populating one or more text fields (e.g. "to"; "subject" and "body") in the message.

In the depicted embodiment, method 200 includes providing 270 signal data from an accelerometer, magnetometer, gyroscope or other motion- sensing hardware in the PDA to the monitor program. For example, ANDROID OS contains Sensor Manager and Sensor Event Listener which allow collection of signal data from these sensors.

Second Exemplary Method

Fig. 3 is a simplified flow diagram illustrating a performance monitoring method according to some exemplary embodiments of the invention indicated generally as 300. Depicted exemplary method 300 includes monitoring 310 one or more performance characteristics of a subject using a monitor program installed on a Personal Digital Accessory (PDA) used by the subject to generate a first data set during a first data collection period and monitoring 320 the one or more performance characteristics of the subject during use of said PDA using said monitor program to generate a second data set during a second data collection period. According to some exemplary embodiments of the invention the difference between the first data collection period and the second data collection period is absence/presence of treatment. According to various exemplary embodiments of the invention the treatment includes a medication and/or neurostimulation and/or neurofeedback. Examples of medications according to exemplary embodiments of the invention include stimulant drugs and non- stimulant drugs. Stimulant drugs include, but are not limited to amphetamines (e.g. ADDERALL and VYVANSE) and Methylphenidates (e.g. FOCALIN; METHLIN; RITALIN, METADATE and CONCERTA). Non-Stimulant drugs include, but are not limited to STRATTERA, INTUNIV and various antidepressants (e.g. WELLBUTRIN, TOFRANIL, PAMELOR; AVENTYL and NORPRAMINE) as well as blood pressure medications (e.g. CLONIDINE and TENEX). The underlying principle is that the treatment efficacy is reflected in the difference in performance characteristic(s) monitored at 310 and 320).

In some embodiments method 300 includes, automatically reporting 330 the first and second data sets to a remote location (e.g. server 115 and/or service provider 120 in Fig. 1) using the monitor program.

Alternatively or additionally, in some embodiments method 300 includes automatically reporting (340) the first and second data sets to a user of said PDA using said monitor program. In some embodiments reporting 340 employs a remote server (e.g. 115 in Fig. 1). In some embodiments reporting 340 delivers a processed data set to the user of the PDA.

Third Exemplary Method

Fig. 4 is a simplified flow diagram illustrating a remote subject monitoring method according to some exemplary embodiments of the invention indicated generally as 400. According to various exemplary embodiments of the invention method 400 is practiced by medical service providers (e.g. 120) in the form of individuals (e.g. doctors and/or pharmacists and/or institutions (e.g. hospitals, clinics or HMOs)

Depicted exemplary method 400 includes deploying 410 a monitor program on a Personal Digital Accessory (PDA) used by a subject and receiving 420 data pertaining to one or more performance characteristics of the subject on a digital device. According to various exemplary embodiments of the invention the digital device includes a desktop computer and/or laptop computer and/or smartphone AP wearable device and/or server.

In some embodiments method 400 includes decoding 430 a unique identifier in the data to ascertain an identity of said subject. According to various exemplary embodiments of the invention the unique identifier includes an alphanumeric string and/or bar code and/or QR code.

Alternatively or additionally, in some embodiments method 300 includes integrating 440 the data into a digital medical record of the subject.

According to various exemplary embodiments of the invention method 400 includes receipt of data 420 corresponding to all, or any subset of, data types described in the context of collecting 230 (e.g. 232 and/or 233 and/or 234 and/or 235 and/or 236 and/or 237 and/or 238 and/or 254 and/or 256 and/or 257) and/or detecting 240 (e.g. 242 and/or 244) and/or providing 270. Alternatively or additionally, in some embodiments the PDA of method 400 includes two or more PDAs acting in concert as described hereinabove.

Exemplary use scenarios

In some embodiments data (e.g. 112 and/or 116 in Fig. 1) provides an initial indication of a subject's baseline condition (i.e. without treatment) for use in formulation of an initial diagnosis and/or treatment plan by a medical practitioner.

In some embodiments the subject himself, or a non-professional caregiver (e.g. parent or teacher) relies upon data (e.g. 112 and/or 116 in Fig. 1) to provide an initial indication of their baseline condition (i.e. without treatment) and decide whether consultation with a healthcare professional is advisable.

In some embodiments comparison of data (e.g. 112 and/or 116 in Fig. 1) from different time periods provides additional information about treatment efficacy and/or patient compliance with treatment and/or dosing regimen.

For example, in some embodiments (see Fig. 3) a difference between a first data set 310 and a second data set 320 provides an indication of treatment efficacy (i.e. when the first data set represents an untreated time period and the second data set represents a treated time period. According to these embodiments, an improvement in one or more performance characteristics provides an indication of treatment efficacy. In some embodiments greater treatment efficacy contributes to an increase in improvement in one or more performance characteristics.

For example, in some embodiments (see Fig. 3) a difference between a first data set 310 and a second data set 320 provides an indication of patient compliance with a treatment (i.e. when the first data set represents first treated time period and the second data set represents a subsequent treated time period. According to these embodiments, a deterioration in one or more performance characteristics provides an indication of patient non-compliance with treatment. In some embodiments flagrant non-compliance (e.g. stopping medication for a prolonged period of time) contributes to an increase in deterioration one or more performance characteristics. Alternatively or additionally, a gradual deterioration in one or more performance characteristics indicates that a patient is become refractive to treatment.

In some embodiments use of shorter periods for data reporting generates additional information. For example, if an un-medicated subject has a score of 10 with respect to a specific performance when data is collected each day between 8 AM and 4PM and the same subject has a score of 6 between 8 AM and 4PM on a day when a single dose of medication is administered at 7AM; hourly reporting might reveal that the un-medicated subject has a score between 9 and 11 throughout the day, while the medicated subject scores 4.5 between 8AM and 11 AM and exhibits higher scores between 11 AM and 4 PM so that the average score for the day is 6. Such a subject might benefit from a divided dose and/or a medication with an extended release formulation.

In some embodiments display of processed data 116 on PDA 110 provides feedback to the subject. According to various exemplary embodiments of the invention this feedback demonstrates treatment efficacy and/or contributes to an ability of the subject to train themselves to improve one or more performance characteristics.

Alternatively or additionally, in some embodiments a subject elects to have location specific comparisons made. Optionally, location is determined by use of a specific WiFi router. These embodiments allow a user to compare their level of attention at the office to their level of attention at home (e.g. when telecommuting) and/or at a public location (e.g. at an airport or a coffee shop).

Exemplary advantages

Previously available treatment alternatives for ADHD relied heavily on subjective evaluations provided by the subject themselves and/or by caregivers (e.g. parents and/or teachers). The reliability of these subjective evaluations is questionable and conflicting reports from the subject and a caregiver are difficult to resolve.

Objective evaluations were typically provided by CPT. Administration of CPT was generally done infrequently due to cost and/or convenience considerations.

In some exemplary embodiments of the invention, objective evaluation data (e.g.

112 and/or 116) is provided. Alternatively or additionally, in some embodiments the data is provided on an ongoing basis. Alternatively or additionally, the data is gathered is gathered un-obtrusively without interfering with the subject's normal interaction with their PDA.

In some embodiments one or more performance characteristics described herein are collected by application 140 and associated with metrics collected in other contexts. For example, in some embodiments CPT outputs are included in data set 112 and/or 116. Exemplary CPT outputs include, but are not limited to the Attention, Timing, Hyperactivity and Impulsivity from the MOXO test (Neuro-Technology Solutions; Israel), the Attention State Analysis metrics in the Quotient ADHD System and motion analysis in the QbTest.

Alternatively or additionally, in some embodiments one or more performance characteristics described herein are associated with scores on validated questionnaires used to assess disorders, such as the Adult ADHD self -report scale, Child Behavior Checklist, or Conners Parent and Teacher Rating Scales.

In some embodiments CPT outputs and/or validated questionnaires includes calculation of a subject- specific transfer function. According to various exemplary embodiments of the invention the subject specific transfer function is created by machine learning such as neural network. In some embodiments machine learning associates comparable behavioral features collected by system 100 with metrics collected in other contexts in both baseline and treated conditions for an individual (e.g. via db 140) or through the use of a standardized database (e.g. 142) for comparison.

In some embodiments system 100 provides outputs of one or more performance characteristics in both a native format (112 and/or 116) and in a format that displays results in a manner consistent with the outputs of another ADHD assessment or tracking tool.

Exemplary correlations

In some embodiments pupil size serves as a performance characteristic. Increased attention correlates with pupil size (Hess EH and Polt JM (1960) Pupil Size as Related to Interest Value of Visual Stimuli. Science 132(3423): 349-350)

Therefore, untreated (or inadequately treated) ADHD subjects are be expected to exhibit variation in pupil size during task performance. In some embodiments a volatility metric (e.g. beta) is incorporated into the monitor program to measure this variation). According to some exemplary embodiments of the invention pupillary response data 256 is collected 230 at PDA 110 and included in data set 112. In some embodiments data 256 is analyzed by analytic module 150 at server 115. In some embodiments the analysis includes comparison with data in DBS 140 and/or 142. Alternatively or additionally, in some embodiments pupil size data rate is compared to population statistics and/or personal history (see 142 and 140 in Fig. 1 and accompanying explanation).

In some embodiments blinking rate 257 serves as a performance characteristic. Increased blink rate correlates with focus on a task in non-ADHD patients but not in ADHD patients. (Caplan R et al. (1996) Blink rate in children with attention-deficit- hyperactivity disorder Biological Psychiatry 39: 12: 1032-8). Therefore, untreated (or inadequately treated) ADHD subjects are be expected to blink less frequently during task performance.

According to some exemplary embodiments of the invention blinking rate data

257 is collected 230 at PDA 110 and included in data set 112. In some embodiments data 257 is analyzed by analytic module 150 at server 115.

According to various exemplary embodiments of the invention blink rate is compared to population statistics and/or personal history (see 142 and 140 in Fig. 1 and accompanying explanation).

In some embodiments saccade rate serves as a performance characteristic.

Decreased saccade rate correlates with focus on a task (Kowler E et al. (1995) The role of attention in the programming of saccades. Vision Research 35(13): 1897-1916). Therefore, untreated (or inadequately treated) ADHD subjects are be expected to saccade more frequently during task performance.

According to some exemplary embodiments of the invention saccade rate data (eye movement 254) is collected 230 at PDA 110 and included in data set 112. In some embodiments data 254 is analyzed by analytic module 150 at server 115. According to various exemplary embodiments of the saccade rate is compared to population statistics and/or personal history (see 142 and 140 in Fig. 1 and accompanying explanation).

In some embodiments accelerometer data indicates body movement which is not necessarily a performance characteristic but is clinically relevant for ADHD. Fidgeting or tapping (F/T) motion involves movement of a limb recorded by the accelerometer while the subject's body is in one place. Incidence of F/T is likely to be higher and/or with earlier onset following a quiescent period in the untreated or uncontrolled ADHD subject. In addition, untreated/uncontrolled F/T will have a shorter periodicity yet individually-distinct and more- stable frequency [>7 and <10Hz] than F/T in treated ADHD. (Ben-Pazi H et al. Abnormal rhythmic motor response in children with attention- deficit-hyperactivity disorder. Developmental Medicine & Child Neurology , 45: 743-745 (2003). As with other data analyses described above, analytic model 150 compares this data to population statistics and/or personal history (see 142 and 140 in Fig. 1 and accompanying explanation).

It is expected that during the life of this patent many new user applications will be developed and the scope of the invention is intended to include all such new technologies a priori.

Alternatively or additionally, it is expected that during the life of this patent many new performance parameters will be correlated to attention deficit disorders will be developed and the scope of the invention is intended to include all such new correlations a priori.

Although the invention has been described in conjunction with specific embodiments thereof, it is evident that many alternatives, modifications and variations will be apparent to those skilled in the art. Accordingly, it is intended to embrace all such alternatives, modifications and variations that fall within the spirit and broad scope of the appended claims.

Specifically, a variety of numerical indicators have been utilized. It should be understood that these numerical indicators could vary even further based upon a variety of engineering principles, materials, intended use and designs incorporated into the various embodiments of the invention. Additionally, components and/or actions ascribed to exemplary embodiments of the invention and depicted as a single unit may be divided into subunits. Conversely, components and/or actions ascribed to exemplary embodiments of the invention and depicted as sub-units/individual actions may be combined into a single unit/action with the described/depicted function.

Alternatively, or additionally, features used to describe a method can be used to characterize an apparatus and features used to describe an apparatus can be used to characterize a method.

It should be further understood that the individual features described hereinabove can be combined in all possible combinations and sub-combinations to produce additional embodiments of the invention. The examples given above are exemplary in nature and are not intended to limit the scope of the invention which is defined solely by the following claims.

Each recitation of an embodiment of the invention that includes a specific feature, part, component, module or process is an explicit statement that additional embodiments of the invention not including the recited feature, part, component, module or process exist.

Specifically, the invention has been described in the context of ADHD but might also be used in the context of other hyperactivity and/or attention disorders.

All publications, references, patents and patent applications mentioned in this specification are herein incorporated in their entirety by reference into the specification, to the same extent as if each individual publication, patent or patent application was specifically and individually indicated to be incorporated herein by reference. In addition, citation or identification of any reference in this application shall not be construed as an admission that such reference is available as prior art to the present invention.

The terms "include", and "have" and their conjugates as used herein mean "including but not necessarily limited to".

Claims

CLAIMS:

1. A method comprising:

(a) monitoring one or more performance characteristics of a subject using a monitor program installed on a Personal Digital Accessory (PDA) used by said subject to generate a data set, and

(b) automatically reporting said data set to a remote location using said monitor program.

2. A method according to claim 1 , wherein said monitoring comprises collecting data generated by operation of one or more applications on said PDA by said subject.

3. A method according to claim 1 wherein said monitoring comprises collecting data from two or more PDAs associated with a single subject.

4. A method according to claim 2, comprising collecting text input rate data from a virtual keyboard module in said PDA.

5. A method according to claim 2, comprising collecting text error rate data from a virtual keyboard module in said PDA.

6. A method according to claim 2, comprising collecting data pertaining to rate and multiplicity of text inputs from a virtual keyboard module in said PDA.

7. A method according to claim 2, comprising collecting data pertaining to structure of text inputs from a virtual keyboard module in said PDA.

8. A method according to claim 2, comprising collecting data pertaining to dwell time.

9. A method according to claim 2, comprising collecting data pertaining to switching among applications.

10. A method according to claim 2, comprising detecting initiation of a microphone out signal while an audio in signal is present during a telephone call on said PDA.

11. A method according to claim 10, comprising logging duration of microphone out signal while an audio-in signal is present during a telephone call on said PDA.

12. A method according to claim 10, comprising logging frequency of occurrence of said initiation.

13. A method according to claim 2, comprising collecting data pertaining to reaction time to on-screen stimuli.

14. A method according to claim 2, comprising:

issuing a camera-on signal to a front facing camera of said PDA without interfering with operation of an application being used by said user;

capturing a series of frames of an eye or eyes of said user together with eyelid borders and identifying pupil positions relative to items onscreen; and

analyzing said frames to generate data pertaining to eye movement of said user while operating said application.

15. A method according to claim 2, comprising:

capturing a series of frames an eye or eyes of said user together with eyelid borders and identifying pupil positions relative to screen or items on it; and

analyzing said frames to generate data pertaining to pupillary response and blink rate of said user while operating said application.

16. A method according to claim 1, wherein said automatically reporting employs a cloud connection.

17. A method according to claim 16, wherein said cloud connection is XMPP based.

18. A method according to claim 1, wherein said automatically reporting employs a messaging program selected from the group consisting of an e-mail program, an SMS program, an MMS program and an instant messaging program.

19. A method according to claim 18, comprising suppressing appearance of a window of said messaging program during said automatically reporting.

20. A method according to claim 18, comprising automatically populating one or more text fields in said message.

21. A method according to claim 1, comprising providing signal data from motion- sensing hardware in said PDA to said monitor program.

22. A method comprising:

(a) monitoring one or more performance characteristics of a subject using a monitor program installed on a Personal Digital Accessory (PDA) used by said subject to generate a first data set during a first data collection period; and

(b) monitoring said one or more performance characteristics of said subject during use of said PDA using said monitor program to generate a second data set during a second data collection period.

23. A method according to claim 22, comprising:

(c) automatically reporting said first and second data sets to a remote location using said monitor program.

24. A method according to claim 22, comprising:

(c) automatically reporting said first and second data sets to a user of said PDA using said monitor program.

25. A method comprising: (a) deploying a monitor program on a Personal Digital Accessory (PDA) used by a subject; and

(b) receiving data pertaining to one or more performance characteristics of said subject on a digital device.

26. A method according to claim 25 comprising, decoding a unique identifier in said data to ascertain an identity of said subject.

27. A method according to claim 25 comprising, integrating said data into a digital medical record of said subject.