Device and method for measuring blood pressure

Abstract

Method for determining a user's blood pressure by measuring a parameter following a monotonic variation during a systole, the method comprising: a) during at least one cardiac cycle, proximal measurement of the parameter at a first distance from the heart and distal measurement of the parameter at a second distance from the heart, the second distance being greater than the first distance; b) from each measurement, estimation of a characteristic representative of the variation of the parameter during systole at each distance; c) comparison of each characteristic; d) determination of the blood pressure based on the comparison resulting from step c), using a calibration model.

Description

Title of the invention: Device and method for measuring blood pressure. Technical field

[0001] The technical field of the invention is the measurement of blood pressure. ANTERIOR ART

[0002] Most blood pressure measurement devices use a pressure sensor coupled to a compression cuff placed on a limb, usually an arm. Blood pressure is characterized by measuring the pressure exerted by the cuff at one or more characteristic times. The pressure sensor is sensitive to heartbeats and their amplitude. Generally, the devices are positioned around the brachial artery.

[0003] In consumer blood pressure monitors, a pressure sensor determines the air pressure in the cuff. The cuff is compressed to achieve arterial occlusion. During cuff deflation or inflation, pressure oscillations occur. These oscillations increase until they transiently reach a maximum amplitude. At this instant, the pressure in the cuff is considered equal to the mean arterial pressure in the brachial artery. From the detected maximum amplitude, the times corresponding to the systolic and diastolic blood pressures are estimated based on empirical laws. The mean arterial pressure is therefore a quantity that can be easily measured by a consumer device. From this measurement, the systolic and diastolic blood pressures can be calculated.

[0004] One drawback of the previously described blood pressure monitors is the need to achieve sufficient compression to obtain arterial occlusion. While the discomfort is acceptable for spot measurements, the compression is hardly acceptable for continuous blood pressure monitoring.

[0005] Measurement methods have been developed that do not require compression of a limb. These are known as "cuffless" or "cuffless" measurement methods. For example, the Bramwell-Hill equation is used to estimate a change in blood pressure from a pulse wave velocity estimated by detecting a pulse wave in two different body areas, for example, at the aorta and the wrist, or at the carotid and femoral arteries. The pulse wave velocity corresponds to the distance between the two areas divided by the time difference between the two detected pulse waves. However, this type of method requires temporal synchronization, so that the time difference can be determined for the same heartbeat. Temporal synchronization may require another measurement, for example, an electrical measurement such as an ECG (Electrocardiogram).

[0006] It is also possible to estimate blood pressure by analyzing the shape of a pulse wave. However, this type of method is relatively complex to implement, as it depends on physiological parameters such as left ventricular volume, systemic vascular resistance, and vascular compliance.

[0007] Systole corresponds to the contraction of the left ventricle of the heart to eject blood into the arterial network. During a cardiac cycle, it is during systole that the pressure reaches a maximum level, called systolic pressure.

[0008] The article Obata Y, Mizogami M, Singh S, Nyhan D, Berkowitz DE, Steppan J, Barodka V. “Ejection time: influence of hemodynamics and site of measurement in the arterial tree.” Hypertens Res. 2017 Sep;40(9):811-818 establishes a link between the difference in systolic duration and vascular characteristics.

[0009] The article by Trian JE, “Arterial Blood-Flow Acceleration Time on Doppler Ultrasound Waveforms: What Are We Talking About?” establishes a link between the shape of the systolic peak, including the systolic rise time, also referred to as acceleration time, and stenosis or, more generally, peripheral arterial disease. This article describes an estimation of the systolic rise time from Doppler velocimetry.

[0010] The inventors propose a method for estimating blood pressure that is simple to implement and does not require compression of an artery. The method can be implemented using a compact device. It is well suited for continuous blood pressure measurement. Description of the invention

[0011] A first object of the invention is a method for determining a user's blood pressure by measuring a parameter following a monotonic variation during a systole, the method comprising: - a) during at least one cardiac cycle, proximal measurement of the parameter at a first distance from the heart and distal measurement of the parameter at a second distance from the heart, the second distance being greater than the first distance; - b) from each measurement, estimation of a characteristic representative of the variation of the parameter during systole at each distance; - c) comparison of each characteristic; - d) determination of blood pressure, based on the comparison resulting from step c), using a calibration model.

[0012] The characteristic representing the variation of the parameter during systole may include a duration of the monotonic variation of the parameter during systole.

[0013] The characteristic representing the variation of the parameter during systole may include a slope of the monotonic variation of the parameter during systole.

[0014] According to one possibility: - steps a) and b) are implemented during several heartbeats; - the representative characteristic of the variation of the parameter during systole includes an average duration of the monotonic variation of the parameter during the systole of said heartbeats.

[0015] According to one possibility: - steps a) and b) are implemented during several heartbeats; - the representative characteristic of the variation of the parameter during systole includes an average or maximum slope of the monotonic variation of the parameter during the systole of said heartbeats.

[0016] The parameter can be chosen from: - the intensity of light backscattered or transmitted through an artery; - the intensity of an acoustic wave reflected by an artery; - a vibration induced by systole; - an electrical impedance induced by systole.

[0017] Step d) may involve the use of an analytical calibration model.

[0018] The calibration model can be a supervised artificial intelligence algorithm.

[0019] According to one possibility, each measurement is carried out by applying a sensor face and of preference over the user's body.

[0020] A second object of the invention is a device for estimating a user's blood pressure, comprising: - two sensors, configured to be applied facing an artery of the user, and configured to measure a user parameter, the parameter following a monotonic variation during a systole; - a processing unit, intended to implement steps b), c) and d) of a process according to the first object of the invention from the parameter measured by each sensor.

[0021] Each sensor can be chosen from: an acoustic sensor, an optical sensor, a tonometric sensor or an electrical impedance sensor, or an electromechanical sensor.

[0022] The invention will be better understood from the detailed examples given below, illustrated by the following figures: FIGURES

[0023] Figures IA and IB schematically illustrate a first embodiment of a device according to the invention.

[0024] Fig. 1C represents another embodiment of the device according to the invention.

[0025] Figure 2 shows the position of a proximal body area and an area distal body.

[0026] Fig. 3 schematically illustrates two systolic rise times corresponding respectively to a proximal body area and a distal body area.

[0027] Figure 4 schematically illustrates the main steps of a process according to the invention.

[0028] Figure 5A describes systolic peaks measured respectively at the level of a zone proximal body area and a distal body area.

[0029] Fig. 5B represents fiducial points on a systolic peak.

[0030] Figure 6A represents a first calibration model, based on a difference in systolic rise time.

[0031] Fig. 6B represents a second calibration model, based on a difference in slopes of systolic peaks.

[0032] Fig. 7A represents an embodiment in which an average is determined from measurements taken on a proximal body area and on a distal body area.

[0033] Fig. 7B represents an embodiment in which interpolations are performed between measurement points.

[0034] Fig. 7C represents an embodiment in which matching is performed between measurement points. PRESENTATION OF SPECIFIC IMPLEMENTATION METHODS

[0035] Figure 1A shows an example of a device 1 for implementing the invention. The device comprises two measurement modules 2. Each measurement module 2 includes a sensor 20, configured to detect a physiological parameter representative of a dimension or volume of an artery at different times. The user can be a human or a living animal. In the embodiment described with reference to Figures IA to IC, the device 1 implements an optical sensor.

[0036] Each measuring module is intended to be applied against the user's body, for example against the user's skin, without penetrating the body. Each measuring module is non-invasive.

[0037] The device 1 is intended to be applied to the face, and preferably against a body area 5 of the user, or at a short distance from it, for example less than 5 mm. The device is preferably located outside the body. The body area 5 may, for example, be located on the neck or a shoulder, wrist, or finger of the user. In the example shown, device 1 is connected to a bracelet-type link 3 so that it is secured against a wrist. Device 1 can be applied to any other sufficiently vascularized body area: abdomen, chest, earlobe, thigh, ankle, leg; these examples are not exhaustive.

[0038] Each module 2 comprises a light source 10, configured to emit an incident light beam 12 towards the addressed body area facing which the light source is positioned. The incident light beam 12 propagates towards the body area 5 along a propagation axis Z. Photons from the incident light beam 12 penetrate the body area 5, and some of them are backscattered, for example, along a direction parallel to the propagation axis Z, in the opposite direction to the latter. The backscattered photons constitute backscattered radiation 14. The backscattered radiation 14 can be detected by a photodetector 20, positioned opposite a surface 5s of the body area.The photodetector 20 can be configured to detect backscattered radiation emanating from the body area at a distance d, called the backscattering distance, generally non-zero and less than a few millimeters, typically less than 15 mm or 10 mm. The photodetector 20 allows the intensity of the backscattered radiation to be measured.

[0039] The light source 10 can be a light-emitting diode (LED) whose emission spectral band extends into the visible or infrared range. Preferably, the emission spectral band width is less than 100 nm. The photodetector 20 can be a photodiode. The signal detected by the photodetector is a photoplethysmography (PPG) signal.

[0040] Figure 1B schematically illustrates the main components of device 1 in a plane perpendicular to the surface 5s of the body area. The curved dashed arrow represents an optical path of photons emitted by the light source in the analyzed body area.

[0041] The optical device 1 includes a processing unit 30 configured to process a signal detected by the photodetector 20. The processing unit 30 is connected to a memory 32, in which instructions for implementing the process described below are stored. The processing unit may include a microprocessor.

[0042] According to an alternative, shown in [Fig. 1C], the body area 5 extends between the light source 10 and the photodetector 20. In this configuration, known as the transmission configuration, the photodetector 20 measures the intensity of the photons that have passed through the body area 5. This configuration assumes that the body area is sufficiently thin so that a sufficient quantity of photons emanates from the medium and is detected by the photodetector. For example, it could be an earlobe or a finger.

[0043] Regardless of the embodiment, the photodetector 20 is arranged to measure the intensity of a beam of light formed by photons that have propagated through the body zone 5: these are either backscattered photons or photons that have passed through the body zone. In the following description, we will refer to the reflection configuration shown in [Fig. 1B].

[0044] Each module 2 of the device is applied simultaneously to a proximal body area 5i and a distal body area 52, as shown in [Fig. 2]. The proximal body area extends to a first distance from the heart. The distal body area extends to a second distance from the heart, the second distance being greater than the first. Thus, the proximal body area 5i is closer to the heart than the distal body area 52. Preferably, the difference between the first and second distances is greater than 10 cm, or even 20 cm, or even 30 cm. This yields a proximal measurement at the proximal body area 5i and a distal measurement at the distal body area 52.

[0045] Preferably, the proximal zone is located near the heart, for example at the level of the aorta or the carotid artery. Thus, the proximal zone corresponds to the neck or torso of the user.

[0046] The distal area can be located on a limb, for example at the wrist, shoulder, thigh, or foot. Preferably, the distal area is located at the extremity of a limb, for example at the ankle or wrist.

[0047] Figure 3 illustrates the principle on which the invention is based. Figure 3 shows a theoretical time evolution of the intensity of a PPG signal (ordinate axis - arbitrary unit), exhibiting a monotonically increasing portion over the duration of the systolic rise, measured by a device as described in connection with Figures IA to IC. The abscissa axis represents time. Under the effect of a change in blood volume during systole, the signal detected by the sensor increases until it reaches an intensity corresponding to the systolic pressure. Figure 3 shows the signals measured respectively at the proximal zone (carotid artery - curve a) and the distal zone (radial artery at the wrist - curve b), corresponding to the same heartbeat. A time lag dt is observed between the onset of each peak, which is due to the difference between the first and second distances.

[0048] In [Fig. 3], the systolic rise times Ati and At2, determined respectively at the proximal and distal zones, are shown. Each rise time corresponds to the increase in pressure under the effect of systole. It is observed that At2 < Atb. The invention takes advantage of the observation made by the inventors, The time difference between the two rise times, VDMS = Atl - At2, depends on the user's blood pressure. VDMS stands for Variation in Systolic Rise Time.

[0049] Indeed, the higher the mean arterial pressure, the stiffer an artery is, and the higher the pulse wave velocity. Consequently, the pulse wave velocity is higher at high pressure than at low pressure. During a cardiac cycle, the high pressure, which corresponds to the end of systole, propagates faster than the low pressure, which corresponds to the beginning of systole. As a result, the time interval between the beginning and end of each systolic peak tends to decrease with the distance of pulse wave propagation. It is therefore smaller when moving away from the heart. For the same reasons, the slope of the systolic peak increases with moving away from the heart. The higher the arterial pressure, the lower the mean arterial pressure (MAP). By arterial pressure, we mean here the mean arterial pressure (MAP).

[0050] Fig. 4 shows the main steps of a method for determining a user's blood pressure.

[0051] Step 100: Application of a measuring device against the user's body, a first module 2 being applied to a proximal body area and a second module being applied to a distal body area as previously described. The measuring device is, for example, a device as described in connection with Figures IA and IB, although it may be another type of device, as described later.

[0052] Step 110: measurement of a parameter dependent on a volume of arterial blood, at the level of the proximal 5p zone. The parameter can be an intensity of a backscattered or transmitted light beam through the artery, or an intensity of an acoustic wave reflected by the artery, or a pressure variation measured at the skin level or an electrical impedance measured at the skin level.

[0053] Step 120: measurement of a parameter dependent on a volume of arterial blood at the level of the distal zone 5i. Preferably, the parameter measured at the level of the distal zone is of the same nature as the parameter measured at the level of the proximal zone, but this condition is not necessary.

[0054] Steps 110 and 120 are repeated at an acquisition frequency preferably greater than a minimum frequency defined subsequently.

[0055] Step 130: Determination of a characteristic of the systolic rise in each body zone. The characteristic can be the systolic rise time Ati and At2 in the proximal and distal body zones, respectively. Other characteristics of the systolic rise can be determined, for example, the slope of the systolic peak. This step is implemented by the processing unit 30, based on the measurements resulting from steps 110 and 120. Preferably the Steps 110, 120, and 130 are implemented in different successive beats. During each systole, each measurement exhibits a rising or falling edge due to the increase in blood volume in the artery. The systolic peak is identified by filtering the signal noise (e.g., low-pass filtering), then using a classic peak detection algorithm, for example, one based on a sign change of the derivative. The systolic peak is easily identified because it is the peak with the greatest amplitude and occurs at a regular interval. A characteristic of the systolic peak, such as the rise time, can be determined during each beat from the parameter measured by the distal and proximal measurements.

[0056] Figure 5A is an example of a PPG-type measurement (wavelength of 810 ±2 nm), the ordinate axis representing the intensity of the backscattered signal measured by the photodetector (arbitrary unit), and the abscissa axis representing time (unit: seconds). Curve a) corresponds to a measurement at the proximal zone (aorta) and curve b corresponds to a measurement at the distal zone (wrist). The rise time Atl at the proximal body zone is 69 ms, while the rise time At2 at the distal body zone is 59 ms.

[0057] The determination of each rise time can be carried out using fiducial points located on each curve representing the evolution of a measurement as a function of time. The following fiducial points are shown in [Fig. 5B]: - a minimum of the measurement during each period, each period corresponding to a heartbeat: this allows us to define the beginning of systole: point D. The beginning of systole can also correspond to an intersection between a tangent to the curve, for example at the point where the slope is maximum, and a minimum of the curve (point A). - a maximum of the measurement during each period, each period corresponding to a heartbeat: this allows us to define the end of systole: point B. The end of systole can also correspond to an intersection between a tangent to the curve and a maximum of the curve (point E). - a point at which the slope is maximum, between the beginning and the end of systole: point C - an intersection of a tangent at the point where the slope is maximum with a line parallel to the x-axis passing through the maximum of the measurement during the period considered: point E; - a point determined so that a straight line, passing through the minimum of the measure (point A) and said point separates the curve corresponding to a beat into two parts of equal area point F.

[0058] In [Fig.5B], the x-axis corresponds to time (unit second) and the y-axis corresponds to a modeled pressure (unit mm Hg)

[0059] Eta pe 140: comparison

[0060] During this step, the characteristics determined by the proximal measurement and the distal measurement are compared. By comparison, we mean a difference or a ratio.

[0061] When the characteristic considered is the rise time, the comparison can be a difference in rise times, corresponding to the VDMS described above. In the example given in connection with [Fig. 5A], the VDMS is 10 ms.

[0062] Step 150: confrontation with a model

[0063] During this step, the comparison resulting from step 140 is compared to a model in order to estimate blood pressure. The model can be an analytical function resulting from modeling and / or experimental calibration. The definition of the model is carried out in step 90 prior to step 150. In one possibility, the model is a supervised learning artificial intelligence algorithm, for example, a neural network.

[0064] Figure 6A represents a first calibration model, allowing the estimation of mean arterial pressure (ordinate axis - unit mmHg) as a function of mean arterial pressure (MAP). It can also be observed that mean arterial pressure is a monotonic and decreasing function of MAP. A quantity other than MAP can be used, for example, a ratio or a difference between the slopes of the systolic peaks resulting from the distal and proximal body areas, provided that mean arterial pressure follows a monotonic function of this quantity. Figure 6A shows modeling points (curve a) as well as a polynomial interpolation (curve b). The modeling was performed based on a cardiovascular model, allowing the calculation of arterial pressures and deformations at different points (Bednarek X. et al., "PPG sensor modelling for cardiovascular parameter estimation." Virtual Physiological Human Conference 2022).Local variations in pressure and in vessel diameters allow the duration of the systolic rise to be calculated at several points.

[0065] In Figure 6A, the mean arterial pressure MAP is related to the VDMS by a polynomial of degree 2: PAM - - 0.062 VDMS2 + 0.796VDMS + 119. (1)

[0066] Applying the model to the VDMS allows us to estimate the mean arterial pressure:

[0067] AM = f(VDMS) (2)

[0068] Figure 6B represents a second calibration model, allowing the estimation of mean arterial pressure (ordinate axis - unit mmHg) as a function of the difference between the slopes of the systolic peaks resulting from the distal and proximal body areas. As in Figure 6A, Figure 6B shows modeling points (curve a) as well as a polynomial interpolation (curve b).

[0069] Figure 6B shows a difference in mean slopes over the systolic rise. Instead of the mean slope, a maximum slope or a combination of local slopes could also be considered. Furthermore, it can be observed that the mean arterial pressure is a monotonic and increasing function of this slope variation.

[0070] The model used depends on each individual, as well as on the position of each measurement point on the individual. It is possible to define an average model, based on modeling and / or experimental data, for a population. Such a model, called a population model, can be used to obtain an initial assessment of blood pressure. The population model can be individualized according to the individual's physiological characteristics: height, weight, sex, etc. The model can also be calibrated for each individual by comparing blood pressure measurements obtained from a reference method with measurements of the VDMS (volume of blood pressure measured in meters per second).

[0071] Acquisition frequency.

[0072] The measurements, in each body area, are performed at a sufficiently high acquisition frequency to detect a low VDMS, with a value of VDMSmin. For example, based on a VDMS of 1 ms, the acquisition frequency F is such that:

[0073] F> ...... 4 ...... (3)

[0074] Where p denotes the desired measurement accuracy.

[0075] For example, if VDMSmin = 1 ms etp = 0.05 (5%), F > 80 kHz.

[0076] If VDMS)nin = 10 ms etp = 0.05 (5%), F > 8kHz.

[0077] The parameter measurements are preferably taken during several successive heartbeats. It is then possible to determine, for different measurements in the same body area, a mean (or median) rise time A and A'F. From these mean rise times, an estimate of the mean VDMS, denoted VDMS, is obtained. Figure 7A represents such an embodiment. Curves a) and b) correspond respectively to the systolic rise times (ordinate axis) from proximal and distal measurements, with the abscissa axis representing time. VDMS can be estimated from values ​​of A' and A'F obtained by moving averages.

[0078] It is noted that the implementation of the method does not require synchronization between measurements, as required by certain methods implementing a determination of blood pressure based on a measurement of pulse wave velocity.

[0079] Figure 7B shows an embodiment in which different systolic rise times have been determined in the proximal and distal body areas. Each measured rise time corresponds to a cross on each curve. Interpolations can then be performed between each measured rise time. Such an embodiment is suitable when two successive rise times are measured between a predetermined number of beats. Interpolation can be used to determine the rise times between two measurements. In Figure 7B, each interpolation is represented by a circle.

[0080] Figure 7C represents an embodiment in which, based on curves showing the evolution over time of rise times measured respectively in the proximal and distal zones, the measurement points are marked by a cross. It is possible to match points located on each curve to identify points corresponding to the same heartbeat. This matching can be performed by determining the closest points on each curve. This is a simplified interpolation: the systolic rise time at time t is estimated to be equal to the previously measured time. The signal can then be processed by simpler electronics, reducing the computation time, memory, and energy requirements.

[0081] Although described in connection with a device 1, based on an optical sensor, the invention can be applied to other types of detectors, for example an acoustic detector, particularly in the field of ultrasound. It is known that cardiac ultrasound can also provide access to information relating to pulsatile variations in blood volumes. The invention can be applied using an ultrasound signal, for example, a Doppler ultrasound. The device comprises at least one ultrasound source and at least one acoustic sensor. In practice, transducers acting as both source and detector are generally used.

[0082] The invention can also be applied to fetal ultrasound. In this case, each ultrasound source and detector is applied against the fetus, but not directly in contact with it, but against the mother's abdomen, the latter forming a propagation medium between the device and the fetus.

[0083] The invention can also be applied to a tonometer-type device comprising a pressure sensor applied in contact with a body area.

[0084] The invention can also be applied, more generally, to a measurement of any parameter varying periodically under the effect of cardiac or respiratory activity.

Claims

Demands

1. A method for determining a user's arterial pressure (MAP) by measuring a parameter following a monotonic variation during a systole, the method comprising: - a) during at least one cardiac cycle, proximal measurement of the parameter at a first distance from the heart and distal measurement of the parameter at a second distance from the heart, the second distance being greater than the first distance; - b) from each measurement, estimation (Atb At2) of a characteristic representative of the variation of the parameter during systole at each distance; - c) comparison of each characteristic (VDMS); - d) determination of the arterial pressure (MAP), as a function of the comparison (VDMS) resulting from step c), using a calibration model (f).

2. Method according to claim 1, wherein the characteristic representing the variation of the parameter during systole includes a duration (Ati At2) of the monotonic variation of the parameter during systole.

3. Method according to claim 1, wherein the characteristic representing the variation of the parameter during systole includes a slope of the monotonic variation of the parameter during systole.

4. A method according to any one of the preceding claims, wherein: - steps a) and b) are carried out during several heartbeats; - the characteristic representing the variation of the parameter during systole includes an average duration (At1? Ât^) of the monotonic variation of the parameter during the systole of said heartbeats.

5. A method according to any one of claims 1 to 3, wherein: - steps a) and b) are carried out during several heartbeats; - the representative characteristic of the variation of the parameter during systole includes an average or maximum slope of the monotonic variation of the parameter during the systole of said heartbeats.

6. A method according to any one of the preceding claims, wherein the parameter is chosen from: - an intensity of light backscattered or transmitted by an artery; - an intensity of acoustic wave reflected by an artery; - a vibration induced by systole; - an electrical impedance induced by systole.

7. A method according to any one of the preceding claims, wherein step d) involves the use of an analytical calibration model.

8. A method according to any one of claims 1 to 6, wherein the calibration model is a supervised artificial intelligence algorithm.

9. A method according to any one of the preceding claims, wherein each measurement is carried out by applying a sensor (20) to the face or against the user's body.

10. Device (1) for estimating a user's blood pressure, comprising: - two sensors (20), configured to be applied opposite an artery of the user, and configured to measure a user parameter, the parameter following a monotonic variation during a systole; - a processing unit (30), intended to carry out steps b), c) and d) of a method according to any one of the preceding claims from the parameter measured by each sensor (20).

11. Device according to claim 10, wherein each sensor is selected from: an acoustic sensor, an optical sensor, a tonometric sensor or an electrical impedance sensor, or an electromechanical sensor.

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