WO2004003818A2

WO2004003818A2 - A physiological and/or psychological monitoring system

Info

Publication number: WO2004003818A2
Application number: PCT/GB2003/002744
Authority: WO
Inventors: Behrooz Toloui
Original assignee: NATMED HOLDINGS Ltd
Current assignee: NATMED HOLDINGS Ltd
Priority date: 2002-06-27
Filing date: 2003-06-27
Publication date: 2004-01-08
Anticipated expiration: 2004-12-27
Also published as: AU2003242844A1; GB0214912D0; WO2004003818A3

Abstract

A physiological and/or psychological monitoring system comprising a central server/ database. Remote monitoring stations are provided for receiving user input and for sending user input to the central server. At the central server the input is analysed and a report generated for the user from the input. This report may include a user score, a text comment, and a graphical representation.

Description

Physiological and/or Psychological Monitoring System

This invention relates to a physiological and/or psychological monitoring system and in particular to a system which monitors physiological and/or psychological data to produce a diagnosis/prognosis and recommendation for further action.

It is known that heart rate variability (HRV) is a measure of the resilience of a person's nervous system and thus this is a useful measurement for stress levels for persons. Heart rate variability is measured beat to beat. Differences and underlying trends can then be detected. Typically, heart rate variability is measured by an electrocardiograph device which measures heart beats through one or more body sensors (typically 3 are used) . Other measuring apparatus may be used such as detecting volume charges in blood flow, and remote sensors for ECG schemes. A heart beat signal comprises two peaks P & R and two troughs Q & S in order PQRS . It is usual to filter the signal to isolate the timing of the R peaks, these being usually much larger amplitude than the P peaks or the Q and S troughs. The RR interval is then used as the basic measure for heart rate variability. To get a sample of heart rate variability, it is usual to take samples from a person over a period of time of e.g. 5 minutes or for a predetermined number of heart beats, e.g. 512 beats.

A computer is then used to process the data to calculate the variability of the RR intervals using standard statistical analysis tools. This gives a measure of heart rate variability.

Preferred embodiments of the present invention seek to provide a system which is able to make physiological and/or psychological measurements from persons over a local or wide area network. Measurements are uploaded to a central server where analysis is performed on them. The results are then downloaded to the units where the measurements took place, from a conclusion and recommendation engine which gives advice and treatment recommendations.

Preferably the system is used repeatedly by persons over a period of months or years thereby building up a history of data for each person which can be used to modify the advice and treatment recommendations.

The system may operate on a hard wired local area network, or a wireless local area network. It may also operate on a fixed line wide area network or on a dial-up wide area network or by a mobile communication system which incorporates a data service such as the GPRS mobile communication system.

A preferred embodiment of the invention will now be described in detail by way of example with reference to the accompanying figures in which:

Figure 1 shows a schematic block diagram of a system embodying the invention implemented over a wide area network;

Figure 2 is a more detailed diagram of the purchase point and monitoring unit of Figure 1;

Figure 3 shows a typical output from the system; and

Figure 4 shows schematically the functions of a central server/database for use in an embodiment of the invention.

Figure 1 shows how an embodiment of the invention may be implemented over either a wide area or local area network. The core of the system is a central server/database (2) . This is in communication with a user purchase point (4) via a data line and a financial data line (they may be the same line) . In a local area network these will usually be wired connections, although they may be local area network wireless connections. In a wide area network there may be leased line connections, dial-up connections, or wireless mobile communication connections such as GPRS connections.

The purchase point is preferably provided, in conjunction with a monitoring unit (6) at a location where it is desired to make the service available. Large organisations may choose to have their own internal systems installed on their own LAN. Alternatively, a subscriber service may be run whereby organisations such as companies, health clubs, doctors surgeries, hospitals, etc. each have a purchase point and a monitoring unit (6) which can communicate using any of the methods discussed above with a central server/database (2) provided at a remote location by a service provider.

When a user wishes to test his stress levels, he will use the purchase point which is provided with a convenient user input interface. This may be a personal computer provided with dedicated software, or a dedicated unit for use with the system and provided with an appropriate form of user input, e.g. keyboard or touch sensitive screen.

A person using the system for the first time will be required to put in some basic identification and personal data and financial data such as credit card details. A payment can be made to the central server/database such that the credit is held for a person enabling him to use the system a predetermined number of times. Alternatively, the system can be arranged to hold the credit card details for a user and to debit the credit card with an appropriate amount each time a person uses the system. The relevant data is held in a user record at the central server/database (2) .

When the central server/database has all the identification and personal data required and the necessary financial data to permit use of the system it authorises the purchase point (4) , via the dataline, to issue an authorisation to the monitoring unit (6) . The monitoring unit (6) has two inputs. These can be seen with reference to Figure 2. First is a physiological input such as an electro-cardiograph (8) . The second is an electronic questionnaire input (10) . These may be used in any order .

The electro-cardiograph unit is coupled to sensors (12) which can be positioned on a person's body to monitor heart beat waveforms. When the sensors are in position the monitoring unit is instructed to commence reading of the waveforms via the ECG unit. It will do this for a predetermined period of time, e.g. 5 minutes or for a predetermined number of heart beats eg. 512 and will store this data in temporary storage in the monitoring unit (6) for subsequent downloading to the central server/database.

The purchase point (4) is also shown in Figure 2 along with the user input (14) discussed above.

The electronic questionnaire input (10) to the monitoring is typically a lifestyle and depression or anxiety questionnaire (or any other questionnaire if required) . A standard questionnaire can be provided for all users or questionnaires specific to a particular type of user can be provided in response to the personal data held in the user record. Thus if a user is known to be overweight, questions pertinent to this condition can be asked. The system will already store personal details of the person such as height and weight . The electronic questionnaire input is used to record subjects which contribute to stress levels such as life events contributing to stress, and other factors about life style including factors such as levels of smoking, drinking, etc.

The data input from the electronic questionnaire input (10) and the ECG unit (8) are sent to the monitoring unit (6) and we then downloaded to the central server/database (2) which analyses the data from the ECG unit (8) and the electronic questionnaire input (10) . From this it produces a heart rate variability measure as discussed above. This can then be presented to a user with a stress (coping and overall well-being) level rating. The HRV measure is also preferably presented to a user in graphical form, such as in the form of a histogram and a scattergram. An example of the output stress ratings and graphical HRV measures is shown in Figure 3. This also includes a conclusion generated by the central server/database and advice. This conclusion is arrived at on the basis of the measured data and the responses to the questionnaire.

The graph in the top left hand corner of figure 3 is on a background colour changing from green at the top, through yellow, to red at the bottom. A score in the green zone indicates low stress levels and good reserves, whilst a score in the red zone indicates a breakdown in regulatory systems and reserves at a low level . Scoring in the yellow zone area intermediate position. Indications can be provided to indicate improvements or deteriorations over time .

Conclusion and advice are generated automatically by the central server/database. All relevant data held by the central server/database is taken into consideration in generating the conclusion and advice. Typically a number of predefined conclusions and advices are stored in the central server/database and can be delivered to the monitoring unit for production to the person using the system. With more sophisticated computing equipment some form of automatic conclusion generation could be used to produce a more flexible range of conclusion and advice data.

One possible outcome of the advice is that the person needs to take further medical advice as to what steps should be taken to alter his or her lifestyle to reduce stress levels and improve general health. When this is necessary, a telephone number is provided on the output of the monitoring unit as shown in Figure 3. Using this, the person makes a telephone call to a call centre (16) . This call centre logs the person's identification and obtains data and financial data about the person from the central server/database. This includes the test history, including the most recent tests taken by the person. This data is then e-mailed to a medical services unit (18) where it may be viewed by a doctor or other person qualified to give help advice. This doctor or other person may then either call the person concerned to give oral advice or may generate written treatment advice. The written treatment advice will then be stored by the medical services unit (18) until accessed by the person for whom it is intended via the purchase point 4. When this happens, the purchase point (4) sends a signal to the central server/database (2) asking for the treatment advice. The central server/database communicates this request to the medical services unit (18) which it then transmits it to the relevant purchase point . Alternatively, the treatment advice may be sent by post, by email or by SMS text messaging.

In this advice process, the user's financial data is again checked to insure that he has sufficient credit with the system to obtain the treatment advice. This is first done by the call centre (16) . The medical services unit (18) then either uses the credit store at the central server/database or instructs it to debit a user's credit card with the appropriate amount. Once the financial data has been authorised, the medical services unit (18) is permitted to produce the treatment advice and to make it available to the person.

The central server holds archives of data which is processed to generate conclusions and recommendations. This is known as a conclusion engine. It is capable of making recommendations and conclusions based on each clients results which can be relayed to the client through various methods such as printed matter posted to the client, electronic transmission orders via computer screen, and others which will be apparent to those skilled in the art. It is essential that communications are secure and therefore appropriate levels of security are provided on transmissions .

Figure 4 shows the functionality of the central server (2) . It includes a database of user records (14) in which personal data and historical analysis data is stored for each user. An analysis engine (18) performs analysis on new data and historical data to produce user reports via the conclusion engine (2) as discussed above. A financial engine (22) deals with all financial transactions and authorisations resulting therefrom.

The database of user records and conclusion engine take account of improvements and deterioration with time to change recommendations.

The processed information can be printed either locally or through the central server/database to any other authorised printing location.

For each person registered with the system a graph of their progress covering various indices can be plotted. These can include sleep, smoking, alcohol, caffeine, exercise, and drug use, as well as depression and anxiety.

Security systems are set up on the central server/database such that the data can only be accessed by authorised personnel .

Using the system as described above enables people to monitor their stress levels and their progress in dealing with these by making modifications to lifestyle. By using a distributed network of either fixed or mobile terminals each including a purchase point and monitoring unit the system becomes very versatile. It can be provided by employers at peoples place of work. It can also be provided at health clubs, in doctors surgeries, etc. For people particularly concerned about their stress levels units could be provided at home. A plug-in card for a personal computer could be provided with all the circuitry necessary to use the computer as an electro-cardiograph enabling home use and subsequent transmission of data, typically by e-mail to the central server/database.

The service can be provided at a corporate level with e.g. monthly charges for a set amount of use. Cluster reports around a given population within an organisation can be provided to see if there are any systemation problems.

The monitoring unit when provided with adequate computing power can be arranged to perform the analysis of input data locally. This feature is most useful if there is a problem with the communication link to the central server (2) . Mobile telephones and PPA's can be used as input devices .

The system has been described here in the context of a system which looks at HRV with depression and anxiety to monitor stress levels in combination with life style inputs. However, the system could be modified for the monitoring of other physiological and psychological conditions as will be apparent to those skilled in the art.

We now discuss some of these statistical methods used for analysing HRV in an embodiment of the invention. These are used to derive the scoring systems discussed above.

The measures obtained after analyses of a series of instantaneous heart rates or NN intervals can be divided into 2 classes:

1. those derived from direct measurements of the instantaneous heart rate or NN intervals

2. those derived from the differences between NN intervals

The variables to be obtained are the following:

• Mean heart rate (HR, int/min) • Mean NN interval (mNN or mRR, ms)

• Standard deviation of the NN interval (sdNN or sdRR, ms) - the square root of variance between the NN intervals .

Since variance is mathematically equal to total power of spectral analysis, sdNN reflects all the cyclic components responsible for variability in the period of recording.

• Standard deviation of the average NN interval calculated over 5-min periods within the 24 - hours recording (SDANN, ms) .

This parameter is an estimate of the changes in heart rate due to cycles longer than 5 minutes

• Mean of the standard deviations of all NN intervals for all 5 in segments of entire recording (SDNN index, ms)

This index reflects the variability due to cycles shorter than 5 minutes

• The square root of the mean squared differences of successive NN intervals (RMSSD, ms) .

• The number of pairs of adjacent NN intervals differing by more than 50 ms in the entire recording (NN50)

• NN50 count divided by the total number of all NN intervals (pNN50, %)

The last three measurements reflect high frequency variations in the structure of HRV and thus are highly correlated.

The series of NN intervals can also be converted into several geometric patterns: • interval tachogram is a graph of the NN intervals complexes (Fig 1)

• A scaterogram looks like a "cloud" which consists of a number of points. Abscissa of the point is the length of the previous NN interval. Ordinate of the point it the length of the subsequent NN interval

(Fig. 2) .

The decreased HRV is reflected in a greater density and smaller size of the cloud. The type of the point distribution is determined by origin of QRS complexes .

• The triangular index (HRVTi) is the integral of the density distribution divided by the maximum of the density distribution. The index reflects total heart rate variability measured over 24 hours and is more influenced by the lower than by the higher frequencies .

Methods for calculation of power spectral density may be classified as parametric and non-parametric,^• in most instances both methods provide comparable results. The important characteristics of the spectrum are the power of the spectrum and the powers of its separate zones. Four main spectral components are distinguished.

Analysis of short-term recordings (5 min)

• Total Power ms² - Variance of all NN intervals (Fig. 3)

• VLF, ms² - power in the very low frequency range

(0, 003-0,04)

• LF, ms² - power in the low frequency (0,04 - 0,15 Hz)

• LFnorm, n.u. - LF power in normalized units: LF/ (Total Power - VLF)*100

• HF, ms² - power in the high frequency range (0,15 - 0,4 Hz)

• HFnor , n.u. - HF power in normalized units: HF/ (Total Power - VLF) *100

• LF/HF - ratio LF [ms²] /HF [ms²]

Analysis of the long - term recording (24 hours)

• Total Power ms² - Variance of all NN intervals

• ULF, ms² - power in the ultra low frequency range

(<0,003 Hz)

• VLF, ms² - power in the very low frequency range

(0,003 - 0,04 Hz)

• LF, ms² - power in the low frequency (0,04 - 0,15 Hz)

• HF, ms² - power in the high frequency range (0,15 - 0,4 Hz)

• a - slope of the linear interpolation of the spectrum in a log-log scale

Based on the above statistical analysis, the scores can be given to various statistical parameters and an index of results produced which can be used to derive a scoring system for the stress analysis. Typically aging dependent statistical parameters are determined, given scores, then summed and the system uses a look-up table to determine the score to assign to a stress rating.

In addition, a conclusion entry is provided which in dependence on the value output by the index denotes a text comment on the state of health of an individual. Text comments are stored in a database and this database will grow as more tests on subjects are performed.

Claims

1. A physiological and/or psychological monitoring system comprising a central server/database; a plurality of remote monitoring stations for receiving user input and for sending the user input to the central server; means at the central server for analysing the user input ; means at the central server for generating a user report from the analysed user input .

2. A monitoring system according to claim 1 in which the remote monitoring stations communicate with the central server via a mobile communications system.

3. A monitoring system according to claim 2 in which the remote monitoring stations receive input data from a user via sensors positioned on his or her body.

4. A monitoring system according to claim 3 in which the input data is electro-cardiograph (ECG) data.

5. A monitoring system according to claim 4 in which the means for analysing user input derives heart rate variability (HRV) data from the ECG data.

6. A monitoring system according to claims 1, 2, 3, 4 or 5 in which the central server stores historical data for users and the means for generating a report also uses the historical data in generating a user report.

7. A monitoring system according to any preceding claim in which the user input comprises data representing responses to a questionnaire.

8. A monitoring system according to any preceding claim in which the central server includes means for storing financial data for a user in dependence on which the system is authorised in response to a user request to receive a user input for analysis.

9. A method for monitoring a physiological and/or psychological condition of a user comprising the steps of: providing a remote monitoring station for a user input of physiological and/or psychological data to be received; sending the user input from the remote monitoring station to a central server; analysing the user input at the central server; and generating a user report from the analysed data.

10. A method according to claim 9 including the steps of; receiving financial data from a user and, authorising use of the remote monitoring station in dependence in the financial data.

11. A method according to claim 9 or 10 including the step of storing previously analysed data for a user at the central server and using previously analysed data in the step of generating a user report.

12. A method according to claim 9, 10 or 11 including the step of instructing a user via a report to seek further advice.

13. A method according to claim 12 including the step of receiving a call from a user requesting further advice and providing data relating to that user to an advisor or producing advice for the user.

14. A method according to claim 13 including the step of receiving financial data relating to the user and authorising the production of user advice in dependence on the financial data.

15. A monitoring station for use in a physiological and/or psychological monitoring system comprising means for receiving user input and for sending the user input to a central server for analysis.

16. A monitoring station according to claim 15 including means for performing analysis of data.

17. A central server for use in a physiological and/or psychological monitoring system comprising: means to receive data supplied from remote monitoring stations; " means for analysing the data; and means for generating user reports from the analysed data.

18. A physiological and/or psychological monitoring system comprising: means for receiving physiological and/or psychological input from a user; means for analysing user input; and means for generating a user report from the analysed user input .

19. A physiological and/or psychological monitoring system according to claim 18 in which the user report includes a user score.

20. A physiological and/or psychological monitoring system according to claim 18 in which the user score as associated with it a text comment .

21. A physiological and/or psychological monitoring system according to claim 19 in which the user score is determined from a statistical analysis of the user input.

22. A physiological and/or psychological monitoring system according to claim 19 in which the user score is displayed graphically.

23. A physiological and/or psychological monitoring system according to 22 in which the graphic display is colour coded from green to red to indicate the good or bad scores.

24. A physiological and/or psychological monitoring system according to 22 in which the graphic display includes an indication of improvement or deterioration in the condition of the user.