IMPROVED PERSONAL HEALTH DATA COLLECTION

Abstract

The invention disclosed herein relates to improvements in the collection personal health data. It further relates to a Personal Health Monitor (PHM), which may be a Personal Hand Held Monitor (PHHM), that incorporates a Signal Acquisition Device (SAD) and a processor with its attendant screen and other peripherals. The SAD is adapted to acquire signals which can be used to derive one or more measurements of parameters related to the health of a user. The computing and other facilities of the PHM with which the SAD is integrated are adapted to control and analyse signals received from the SAD. The personal health data collected by the SAD may include data related to one or more of blood pressure, pulse rate, blood oxygen level (SpO.sub.2), body temperature, respiration rate, ECG, cardiac output, heart function timing, arterial stiffness, tissue stiffness, hydration, blood viscosity, blood pressure variability, the concentration of constituents of the blood such as glucose or alcohol and the identity of the user.

Claims

1. A kit comprising an occlusion device, a pulse wave velocity (PWV) device and analysing means for analysing signals produced by the occlusion device and the PWV device, which devices and means are adapted to function cooperatively, wherein: the occlusion device is for the non-invasive measurement of a subject's blood pressure and comprises: area means for measuring the change in luminal area of an artery of the subject during a heartbeat; contacting means for contacting a body part of the subject containing the artery and for having pressure exerted thereon, either by pressing the contacting means against the body part or by pressing the body part against the contacting means; and pressure means for measuring the instantaneous pressure between the body part containing the artery and the contacting means; the PWV device comprises: measuring means for making measurements from which the PWV can be derived; the analysing means is adapted to: analyse the measured values of instantaneous pressure exerted on the contacting means and the change in luminal area so as to make a determination of the subject's blood pressure and, from the measurements made by the measuring means and the determined blood pressure, derive an improved estimate of blood pressure derived from PWV.

2. An integrated device comprising: area means for measuring the change in luminal area of an artery of a subject during a heartbeat; contacting means for contacting a body part of the subject containing the artery and for having pressure exerted thereon, either by pressing the contacting means against the body part or by pressing the body part against the contacting means; pressure means for measuring the instantaneous pressure between the body part containing the artery and the contacting means; measuring means for making measurements from which the pulse wave velocity (PWV) can be derived; and analysing means which is adapted to analyse the measured values of instantaneous pressure exerted on the contacting means and the change in luminal area so as to make a determination of the subject's blood pressure and, from the measurements made by the measuring means and the determined blood pressure, derive an improved estimate of blood pressure derived from PWV.

3. (canceled)

4. A kit comprising an occlusion device, a pulse wave analysis (PWA) device and analysing means for analysing signals produced by the occlusion device and the PWA device, which devices and means are adapted to function cooperatively, wherein: the occlusion device is for the non-invasive measurement of a subject's blood pressure and comprises: area means for measuring the change in luminal area of an artery of the subject during a heartbeat; contacting means for contacting a body part of the subject containing the artery and for having pressure exerted thereon, either by pressing the contacting means against the body part or by pressing the body part against the contacting means; and pressure means for measuring the instantaneous pressure between the body part containing the artery and the contacting means; the PWA device comprises: measuring means for making measurements from which an estimate of blood pressure can be derived using PWA; the analysing means is adapted to: analyse the measured values of instantaneous pressure exerted on the contacting means and the change in luminal area so as to make a determination of the subject's blood pressure and, from the measurements made by the measuring means and the determined blood pressure, derive an improved estimate of blood pressure using PWA.

5. An integrated device comprising: area means for measuring the change in luminal area of an artery of a subject during a heartbeat; contacting means for contacting a body part of the subject containing the artery and for having pressure exerted thereon, either by pressing the contacting means against the body part or by pressing the body part against the contacting means; pressure means for measuring the instantaneous pressure between the body part containing the artery and the contacting means; measuring means for making measurements from which an estimate of blood pressure using pulse wave analysis (PWA) can be derived; and analysing means which is adapted to analyse the measured values of instantaneous pressure exerted on the contacting means and the change in luminal area so as to make a determination of the subject's blood pressure and, from the measurements made by the measuring means and the determined blood pressure, derive an improved estimate of blood pressure using PWA.

6. (canceled)

7. The kit of claim 1, wherein the analysing means is further adapted to: from measurements made by the measuring means, derive an estimate of the PWV; from the estimate of the PWV, derive an estimate of the subject's blood pressure; and use the estimate of the subject's blood pressure derived from the estimate of the PWV to: enhance the accuracy of the determined blood pressure; speed up the processing of the measurements of instantaneous pressure and change in luminal area to make the determination of blood pressure; or improve the search strategy of optimisation techniques used by in making the determination of blood pressure.

8. The integrated device of claim 2, wherein the analysing means is further adapted to: from measurements made by the measuring means, derive an estimate of the PWV; from the estimate of the PWV, derive an estimate of the subject's blood pressure; analyse the measured values of instantaneous pressure exerted on the contacting means and the change in luminal area so as to make a determination of the subject's blood pressure; and use the estimate of the subject's blood pressure derived from the estimate of the PWV to: enhance the accuracy of the determined blood pressure; speed up the processing of the measurements of instantaneous pressure and change in luminal area to make the determination of blood pressure; or improve the search strategy of optimisation techniques used by in making the determination of blood pressure.

9. The kit of claim 1, wherein the measuring means uses an electrical sensor to detect the electrical trigger of the heartbeat.

10.-12. (canceled)

13. The kit of claim 1, which is adapted to provide an estimate of systolic and diastolic blood pressure.

14. The kit of claim 1, which further includes means for instructing the user to adjust how hard the device is pressed against the body part or the body part is pressed against the device.

15. The kit of claim 1, wherein the analysing means is adapted to make an estimate of arterial stiffness and to use that estimate to improve the accuracy of the estimate of blood pressure or the ease of analysing the PWV.

16. The kit of claim 1, wherein the analysing means is adapted to make an estimate of the stiffness of the tissue surrounding the artery and to use that estimate to improve the accuracy of the estimate of blood pressure or the ease of analysing the PWV.

17. The kit of claim 16, wherein the estimate of the stiffness of the tissue surrounding the artery includes an estimate of the state of hydration of the tissue.

18. The kit of claim 1, wherein the analysing means is adapted to estimate the Pre-Ejection Period.

19.-54. (canceled)

55. The integrated device of claim 2, wherein the measuring means uses an electrical sensor to detect the electrical trigger of the heartbeat.

56. The integrated device of claim 2, which is adapted to provide an estimate of systolic and diastolic blood pressure.

57. The integrated device of claim 2, which further includes means for instructing the user to adjust how hard the device is pressed against the body part or the body part is pressed against the device.

58. The integrated device of claim 2, wherein the analysing means is adapted to make an estimate of arterial stiffness and to use that estimate to improve the accuracy of the estimate of blood pressure or the ease of analysing the PWV.

59. The integrated device of claim 2, wherein the analysing means is adapted to make an estimate of the stiffness of the tissue surrounding the artery and to use that estimate to improve the accuracy of the estimate of blood pressure or the ease of analysing the PWV.

60. The integrated device of claim 59, wherein the estimate of the stiffness of the tissue surrounding the artery includes an estimate of the state of hydration of the tissue.

61. The integrated device of claim 2, wherein the analysing means is adapted to estimate the Pre-Ejection Period.

Description

[0070] In the examples, reference is made to the accompanying drawings, which are provided by way of illustration only and which do not limit the scope of the invention, in which:

[0071] FIG. 1 is a representation of the pressure in an artery through a heartbeat and the area of that artery;

[0072] FIG. 2 illustrates how the change in area varies as a function of the applied pressure;

[0073] FIG. 3 is a recording of the pressure in an automatic oscillometric cuff;

[0074] FIG. 4 illustrates the first step of an exemplary process using a measured PPG signal; and

[0075] FIG. 5 shows a cross-section of a device according to the third aspect of the present invention together with a representation of proximity signals.

Example 1

Calibration of PWV and PWA

[0076] A limitation of all PWV and PWA techniques is that they must be calibrated for each user. This requires the user to make several measurements of blood pressure using an occlusion (cuff) device at the same time as measurements of PWV or PWA. These allow the PWV or PWA to be calibrated and then used to detect changes in blood pressure from that measured with the cuff. The calibration typically remains valid for a period of time of days to weeks, after which it must be repeated. This limits the utility of the PWV or PWA technique since it also needs access to a cuff device.

[0077] The absolute measurement of blood pressure by cuff-less occlusion, using a separate device as part of a kit or as part of an integrated device, may be used as a calibration for the PWV or PWA measurement. The PWV or PWA measurement may then be used to make quick and easy measurements of blood pressure until it is necessary to recalibrate.

[0078] The calibration procedure may be further enhanced by making several calibrations under different conditions, such as for example at different times of day or before and after taking exercise. Such distributed calibrations may be exploited to improve the accuracy of the subsequent PWV or PWA measurements or to extend the period until it is necessary to recalibrate.

Example 2

Stability of Pulse Wave Analysis

[0079] PWA is simple and easy to use but it is not easy to achieve adequate accuracy. One of the reasons is that the measured optical waveform depends on how hard the user presses the measurement device against the body part. The pressure sensor in the pressure means can be used with its optical sensor to generate PWA waveforms at a specific pressure by providing feedback to the user to press harder or softer. This can be used to ensure that the measurement pressure is the same as that used for calibration or can be used to provide the PWA analysis with a set of waveforms captured at different pressures.

[0080] Alternatively, the actual measured applied pressure may be used, without providing feedback to the user, as an input to the PWA algorithms so as to improve their accuracy and/or extend the time before needing re-calibration.

Example 3

Estimation of Pre-Ejection Period (PEP)

[0081] The PTT found using an electrical signal includes the PEP and so the estimated PWV will not be correct. PEP is fairly stable for an individual and so an occasional measurement of this can be used to correct the measured PTT.

[0082] PCT 4, FIG. 9 and the Ninth aspect of PCT 4 show that devices according to the Leman applications can measure PEP directly. This measurement maybe used to improve the accuracy of the PWV estimate.

Example 4

Direct Estimates of Arterial Stiffness

[0083] PWV is related to blood pressure via the arterial stiffness. If this stiffness is known, it is possible to make a more accurate estimate of that relationship and hence a more accurate estimate of blood pressure derived from PWV. Since the waveform analysed by PWA also depends on PWV, the stiffness can also be used to improve the accuracy of PWA.

[0084] PCT 4, page 11, lines 9 to 14 discloses that the local arterial stiffness can be measured directly by the Leman devices.

Example 5

Direct Estimates of Stiffness of Surrounding Tissue

[0085] The effective stiffness of an artery also depends on the stiffness of tissue surrounding it. Aspect 5 of PCT 5 discloses that devices according to the Leman applications can make an estimate of the stiffness of that tissue, including its change due to hydration. This can also be used to improve the accuracy of PWV and PWA measurements, in a similar way to the fourth example above.

Example 6

Improving the Cuff-Less Occlusion Technique using PWV Data

[0086] PCT 2, lines 24 to 30 discloses that an estimate of the arterial stiffness may be used by the cuff-less occlusion device to improve some of the techniques for extracting blood pressure from the occlusion data. It assumes that the estimate is found directly from the measured data but there is advantage in using an independent estimate, derived from a PWV or PWA measurement. This can contribute to both the accuracy of the result and the speed of processing.

[0087] The LMD applications disclose several techniques for extracting blood pressure from the data derived from the sensors that use a search or optimisation algorithm. These operate by searching the solution space, including searching for the diastolic and systolic blood pressures. An estimate of these values that is derived from PWV or PWA can be used to narrow the search space or at least to indicate starting values for the search. This reduces the time taken for the search and reduces the risk that the search selects a sub-optimum value of the solution.

Example 7

Isobaric Correction

[0088] Referring to FIG. 1, the dashed line shows the typical luminal area of an artery as a function of the difference between the instantaneous pressure of the arterial blood and the instantaneous pressure of the tissue surrounding the artery. The vertical dotted lines show the pressure difference at the time of systole (when the arterial pressure is maximum so the difference is minimum) and diastole (when the arterial pressure is minimum so the difference is maximum). The double-ended arrow, labelled deltaA, shows the change in area between systole and diastole.

[0089] Note that the exact form and vertical scale of FIG. 1 will depend on the size and stiffness of the artery, the stiffness of the surrounding tissue and the properties of the measurement means.

[0090] It is clear that the value of deltaA depends on the pressure of the tissue surrounding the artery. FIG. 2 is a typical plot of deltaA as a function of the pressure of the tissue surrounding the artery, labelled as the “applied pressure”. Typical values of diastolic pressure (DBP) and systolic pressure (SBP) are marked on FIG. 2.

[0091] By plotting deltaA in FIG. 2 and, if necessary, normalising it by the maximum of deltaA in this plot, the vertical scale of FIG. 1 no longer is significant.

[0092] This is a mature technique for use in devices that measure blood pressure where the pressure in the surrounding tissue does not change significantly within one beat. FIG. 3 illustrates this. It is a recording of the pressure in the cuff of a conventional automated oscillometric blood pressure monitor. The changes in pressure on each heartbeat are at most 2.5 mmHg, a clinically acceptable level of uncertainty. However, if these changes were much greater, either randomly or systematically, it would not be possible to make a sensible estimate of the pressure of the tissue surrounding the artery. The pressure at the time of systole would be wrong for diastole, the pressure at the time of diastole would be wrong for systole and the average pressure, as well as being wrong for both, is meaningless because FIG. 1 is non-linear.

[0093] This aspect of the present invention does not use deltaA directly. Instead, it uses the following sequence of steps: [0094] 1. Extract from the data an estimate of Anp, the luminal area of the artery at diastole on each heartbeat, and simultaneously measure the instantaneous applied pressure (assumed to be the same as the pressure surrounding the artery); [0095] 2. Plot A.sub.DBP as a function of the instantaneous applied pressure; [0096] 3. Fit a smoothed curve through the points representing A.sub.DBP versus instantaneous applied pressure to give a parametric model of A.sub.DBP versus instantaneous applied pressure; [0097] 4. Repeat steps 1 to 3 for A.sub.SBP vs instantaneous applied pressure; and [0098] 5. Create a set of “pseudo heartbeats” wherein deltaA is estimated by subtracting the value of A.sub.SBP given by its parametric model from the value of A.sub.DBP given by its parametric model, both values taken at the same instantaneous applied pressure (the term “isobaric” reflects this same instantaneous pressure).

[0099] This set of pseudo heartbeats may then be analysed using any of the analytical methods that would otherwise be used for actual heartbeats, but with a known instantaneous applied pressure.

[0100] The smoothed curve may be found using curve-fitting techniques that are well-known by persons skilled in the art, such as the Loess algorithm. As well as providing a parametric model, the parameters of the curve-fitting technique may be selected to smooth the data and so reduce the effect of measurement noise.

[0101] If the instantaneous pressure of the tissue surrounding the artery lies between the diastolic blood pressure and the systolic blood pressure, the luminal area of the artery will increase rapidly as the instantaneous arterial pressure exceeds the instantaneous pressure of the tissue surrounding the artery. It will also fall rapidly as the instantaneous arterial pressure falls below the instantaneous pressure of the tissue surrounding the artery. The timing of these two events during the heartbeat may also be used to estimate the diastolic and systolic blood pressure, in a manner analogous to the use of deltaA. For example, in an ideal model with no noise, the interval between those two times is zero if the instantaneous pressure of the tissue surrounding the artery equals or exceeds the systolic blood pressure. Similarly, that interval equals the duration of the heartbeat T.sub.H if the instantaneous pressure of the tissue surrounding the artery equals or is less than the diastolic blood pressure.

[0102] Some techniques for finding diastolic and systolic blood pressure exploit that interval. They can be compensated for the effect of varying applied pressure by the same technique as is used for deltaA, where the equivalent steps are: [0103] 1. Extract from the data an estimate of T.sub.R, the time at which the luminal area of the artery grows rapidly on each heartbeat, and simultaneously measure the instantaneous applied pressure (assumed to be the same as the pressure surrounding the artery); [0104] 2. Plot T.sub.R as a function of the instantaneous applied pressure; [0105] 3. Fit a smoothed curve through the points representing T.sub.R versus instantaneous applied pressure to give a parametric model of T.sub.R versus instantaneous applied pressure; [0106] 4. Repeat steps 1 to 3 for T.sub.F, the time at which the luminal area of the artery falls rapidly on each heartbeat, vs instantaneous applied pressure; and [0107] 5. Create a set of “pseudo heartbeats” wherein deltaT is estimated by subtracting the value of TR given by its parametric model from the value of T.sub.F given by its parametric model, both values being taken at the same instantaneous applied pressure.

[0108] This set of pseudo heartbeats may then be analysed using any of the analytical methods that would otherwise be used for actual heartbeats, but with a known instantaneous applied pressure. It will be apparent to a person skilled in the art that other combinations of T.sub.F, T.sub.R and T.sub.H may be used, such as (T.sub.F−T.sub.R)/T.sub.H.

Example 8

Viscosity of Blood

[0109] FIG. 4 illustrates the first step of an exemplary process using a measured PPG signal, as a function of pressure, in this case for green light. It shows only the low frequency signal. The high frequency fluctuations due to the arterial luminal area are too small to see on this plot.

[0110] FIG. 4 also shows how the signal can be effectively modelled using as input the pressure signal by including in the model:

[0111] a term related to the integral of pressure;

[0112] a term related to the Systolic blood pressure, above which the arteries are occluded;

[0113] a linear variation in sensitivity due to deformation of the tissue; and

[0114] small terms related to the instantaneous pressure and rate of change of pressure.

[0115] Similar results may be obtained for other colours of PPG light, including but not restricted to red and infra-red, and also for the high frequency PPG signals.

[0116] The model parameters are used as inputs to the machine learning to find the combination of parameters that best predicts the viscosity of the blood.

Example 9

Proximity Detection

[0117] FIG. 5 shows a cross-section on an LMD device, together with a representation of the proximity signals. These signals may be analysed by the signal processing means to estimate the distance from the surface. That distance may be used to provide feedback to the user to place the device at the correct distance. Alternatively, the estimated distance may be used to correct errors caused by distance to any measurement that is made when not touching the body part.

[0118] It should be clearly understood that, for all of the aspects of the present invention, the examples and figures and the description thereof are provided purely by way of illustration and that the scope of the invention is not limited to this description of specific embodiments; the scope of the invention is set out in the attached claims.