Blood pressure sensor systems with user assessment and error correction

Abstract

Systems and methods are disclosed for reducing error in the measurement of a user's blood pressure with a physiological monitoring device that includes a sensor assembly with a PPG module and a pressure sensor module. Exemplary methods include the steps of placing a finger on the physiological monitoring device such that the finger is in contact with the sensor assembly, instructing the user to apply a range of pressures to the pressure sensor module during a measurement cycle, creating a measured oscillometric curve based on the PPG data and pressure sensor data retrieved during the measurement cycle, and determining whether the measured oscillometric curve is based on unreliable or incorrect data before calculating the user's blood pressure from the measured oscillometric curve.

Description

BLOOD PRESSURE SENSOR SYSTEMS WITH USER ASSESSMENT AND ERROR CORRECTIONRELATED APPLICATIONS

[0001] This application claims the benefit of United States Provisional Patent Application Serial No. 63 / 617,979 filed January 5, 2024 entitled. "User Assessment Methods for Blood Pressure Measurement,” and United States Provisional Patent Application Serial No. 63 / 674,260 filed July 22. 2024 entitled, ‘"Blood Pressure Sensor Systems with Error Correction,” the disclosures of which are herein incorporated by reference.FIELD OF THE INVENTION

[0002] This invention generally relates to measuring blood pressure and, more particularly, but not by way of limitation, to a sensor package that permits multiple methods of obtaining blood pressure measurements.BACKGROUND OF THE INVENTION

[0003] There is a growing recognition of the importance of enabling people to take greater control of their health. Notwithstanding this growth of emphasis on personal health management, there is a shortage of physiological measurement devices that are accurate, affordable, easy to use, and readily available to the public. Integrating the functionality for physiological measurement and monitoring into a portable and widely available product, such as a key fob or cellphone, would greatly enhance the ability of people to manage their health.

[0004] Blood pressure, for example, is a fundamental diagnostic parameter that is used throughout the world to assess health. The basic measurements for this vital sign are diastolic blood pressure, the lowest pressure observed during the pulse cycle, and systolic blood pressure, the highest pressure observed during the pulse cycle. At least three methods have been established for measuring absolute arterial blood pressure without inserting a measurement device into the artery" auscultatory’, oscillometric andvolume clamp methods. There are also relative measurement methods that detect changes or trends in blood pressure, but these methods require calibration for each user.

[0005] With reference to traditional oscillometric methods for blood pressure measurement, automatic sphygmomanometers such as an inflatable cuff are often used to occlude blood flow in an artery, usually the brachial (arm) or radial (wrist) artery. The cuff is then deflated to allow blood to begin to flow again. During deflation, the flow is detected by observing small pressure fluctuations introduced into the cuff by the pulse.

[0006] To enhance user functionality, alternatives to the traditional cuff have been developed to determine blood pressure by measuring photoplethysmography (PPG) signals from a body part (e.g., a finger) until arterial occlusion is achieved. These alternative devices differ from automatic blood pressure cuffs, which rely on Korotkoff sounds (auscultatory) or cuff pressure fluctuations representative of volume changes (oscillometry) rather than PPG signals to estimate blood pressure. In most PPG-based measuring systems, one or more light emitting diodes (LEDs) or other photoemitters emit light into a vascular structure while one or more photoreceptors (e.g., photodiodes) measure the resultant reflection from or transmission through tissue of light produced by the photoemitter. To successfully estimate blood pressure using a PPG approach, it is crucial to obtain a high-quality PPG signal from the user. The user’s pulse can be evaluated by measuring the alternating current (AC) signal attributable to the cyclical pulse, while limiting the impact of the less-cyclical direct current (DC) signal attributable to baseline blood flow and tissues within the target vascular structure.

[0007] Some blood pressure measurement systems combine a PPG sensor with a pressure sensor. The PPG sensor is configured to measure changes in blood flow volume as part of an oscillometric measurement, while the pressure determines how much force is being applied to the subject’s artery. For example, United States Patent Nos. 10,342,493and 11,129,575 (both incorporated by reference) disclose sensor packages for measuring blood pressure that include a combination of a PPG sensor and a pressure sensor.

[0008] Although the use of these sensor packages for measuring blood pressure is well documented, these systems suffer from several deficiencies. First, a small portion of the population has conditions that frustrate efforts to obtain accurate blood pressure readings from digital arteries. These conditions may not be apparent to the user prior to utilizing a finger-based blood pressure measurement device. Disqualifying conditions may include, for example, lack of suitable visuomotor skills, lack of finger dexterity, insufficient perfusion, smoking or other tobacco use, and arterial stiffness. A need exists, therefore, for systems and methods to automatically identify' the presence of disqualifying conditions to exclude people who are incapable of obtaining accurate blood pressure measurements.

[0009] Second, because the user is providing the external pressure required to occlude the artery, the quality of the pressure application administered by the user must be quantified and evaluated to determine whether the measurement can be trusted for further processing. Third, because the blood volume pulsations are being measured optically (via PPG) rather than through the pressure sensor in the cuff, the user’s physiological characteristics at the peripheral arteries being interrogated must be quantified dynamically and used to both assess the quality of the measurement and mitigate error sources in the measurement through corrections. Fourth, because the user holds the device in the hand while performing the measurements, and because the user must apply pressure uniformly and smoothly to track the guide presented to them, the movements and tilt angles of the sensor platform must be quantified to both trust the measurement and to mitigate these errors through correction. Fifth, because the usermust place their finger accurately on the sensor, the device must be able to detect misplacement of the finger and in some cases correct for misplacement through internal algorithms. Sixth, because the measurement of blood volume pulsation is optical (PPG), the perfusion of the peripheral vessels from which such recordings are obtained must be quantified. The embodiments described herein pertain to sensors, algorithms, and approaches used to address these key challenges.

[0010] Thus, pressure-PPG sensor packages are vulnerable to sensor errors caused by excessive extraneous motion, inaccurate or inconsistent application of pressure to the pressure sensor, unexpected pathology7, and from other unpredicted sources. To ensure blood pressure and other physiological parameters are only measured using acceptable data, a need exists for systems and methods for identifying and discarding error-prone data. The present disclosure is directed to these and other deficiencies in the prior art.SUMMARY OF THE INVENTION

[0011] In some embodiments, the present disclosure is directed to a method for measuring a user’s blood pressure with a physiological monitoring device that includes a sensor assembly with a PPG module and a pressure sensor module. The method includes the steps of placing a body part on the physiological monitoring device such that the body part is in contact with the sensor assembly, conducting one or more user assessment tests, and measuring the user’s blood pressure with the physiological monitoring device if the user passes the user assessment test. The one or more user assessment tests may include a finger dexterity test, a perfusion test, and an arterial stiffness test.

[0012] In other embodiments, the present disclosure is directed to a method for measuring a user’s blood pressure with a physiological monitoring device that includes a sensor assembly with a PPG module and a pressure sensor module. The method includes the steps of placing a finger on the physiological monitoring device such that the finger isin contact with the sensor assembly, instructing the user to apply a range of pressures to the pressure sensor module during a measurement cycle, creating a measured oscillometric curve based on the PPG data and pressure sensor data retrieved during the measurement cycle, and determining whether the measured oscillometric curve is based on unreliable or incorrect data before calculating the user's blood pressure from the measured oscillometric curve. The step of determining whether the measured oscillometric curve is based on unreliable or incorrect data may include using machine learning to compare a measured oscillometric curve from the user against a library of oscillometric curves of known quality.

[0013] In yet other embodiments, the present disclosure is directed to a method for measuring a user’s blood pressure that begins with the step of providing a sensor assembly that includes a PPG module with a first pair of photoemitters and photoreceptors, a second pair of photoemitters and photoreceptors, and a third pair of photoemitters and photoreceptors, and a pressure sensor module in a central location between the second pair of photoemitters and photoreceptors. The method continues with the steps of placing a finger of the user on the physiological monitoring device such that the finger is in contact with the PPG module and the pressure sensor module, instructing the user to apply a range of pressures to the pressure sensor module during a measurement cycle, simultaneously generating a first oscillometric curve from the first pair of photoemitters and photoreceptors, a second oscillometric curve from the second pair of photoemitters and photoreceptors, and a third oscillometric curve from the third pair of photoemitters and photoreceptors, and determining if the user’s finger is centrally located over the pressure sensor module to permit an accurate blood pressure measurement by comparing the first, second and third oscillometric curves.BRIEF DESCRIPTION OF THE DRAWINGS

[0014] FIGS. 1A-1B are side perspective views of various embodiments of a PPG-based physiological monitoring device configured for engagement by a finger and connection to a mobile computing device.

[0015] FIG. 2A and 2B are top views of embodiments of the physiological monitoring device of FIGS. 1A-1B.

[0016] FIG. 3 is a side cross-sectional view of the sensor assembly of the physiological monitoring device of FIGS. 1 and 2.

[0017] FIG. 4 depicts an oscillometric curve resulting from data obtained by the physiological monitoring device of FIGS. 1 and 2.

[0018] FIG. 5 is a process flow diagram for a method for obtaining a blood pressure measurement employing a user assessment step.

[0019] FIGS. 6A-6D are process flow diagrams for various embodiments of user assessment routines.

[0020] FIG. 7 shows oscillometric curves resulting from data obtained by the physiological monitoring device of FIGS. 1 and 2 for two different users with normal arterial compliance (solid black lines) and two different users with low arterial compliance (dotted black lines).

[0021] FIGS. 8A-8C depict correct and incorrect positioning of the user's finger on the physiological monitoring device of FIG. 1.

[0022] FIGS. 9A-9C depict oscillometric curves produced by the correct and incorrect finger positioning illustrated in FIGS. 8A-8C, respectively.

[0023] FIGS. 10A-10B depict high quality and low quality oscillometric curves, respectively.

[0024] FIG. 11 is a process flow diagram for a quality of curves classifier method.

[0025] FIG. 12 is a process flow diagram for a motion monitoring classifier method.

[0026] FIG. 13 is a process flow diagram for a pressure tracking classifier method.

[0027] FIG. 14 is a process flow diagram for a multi-classifier method for ensuring accuracy from digital oscillometric measurements.DETAILED DESCRIPTION

[0028] Turning to FIGS. 1-3, shown therein is a physiological monitoring device 100, which is well-suited for measuring blood pressure, pulse, blood oxygenation, or other physiological parameters. In the embodiment depicted in FIG. 1A, the physiological monitoring device 100 includes a body 102 that includes a finger trough 104 and a sensor assembly 106. The finger trough 104 is designed to accurately and precisely locate the user’s fingertip on top of the sensor assembly 106. In the embodiment depicted in FIG. IB, the finger trough 104 has been omitted in favor of a flush-mounted sensor assembly 106 on the upper surface of the body 102. In both embodiments, the body 102 is puck-shaped to facilitate the placement of the user’s thumb on the bottom of the body 102 so the user can comfortably exert a compressive force on the sensor assembly 106 with the user’s finger by squeezing the physiological monitoring device 100 between the thumb and finger. It will be appreciated that, in various embodiments, the body 102 is configured in an alternative size or shape suitable for the user to exert a compressive force on the sensor assembly 106. Although the depicted embodiments present the sensor assembly 106 incorporated within the body 102. it will be appreciated that the sensor assembly 106 can also be incorporated into other devices or form factors, including computing devices, tablets and mobile phones.

[0029] The sensor assembly 106 includes one or more photoemitters 108, one or more photoreceptors 110 and a pressure sensor module 112. The photoemitters 108 and photoreceptors 110 together present a PPG module 114. In exemplary embodiments, the photoemitters 108 are light emitting diodes (LEDs) configured to output light (e.g.,green, red, infrared) at a selected and controllable intensity (amplitude) based on a command signal from control circuits 124. In the same exemplary embodiments, the photoreceptors 110 are photodiodes configured to output a current or voltage signal to the control circuits 124 in response to the detection of light. The strength of the signal produced by the photoreceptors 110 can be tuned or adjusted to increase or decrease the sensitivity and output of the photoreceptors 110. The photoemitters 108 and photoreceptors 110 each optionally include an optical glass or optical glue (e.g., transparent epoxy or other curable compound) on their upper surface to protect against moisture.

[0030] The PPG module 114 can be configured or adapted to operate in a reflectance mode in which light emitted by the photoemitters 108 is reflected by the user’s fingertip back to the photoreceptors 110. The PPG module 114 can also be configured or adapted to operate in a transmissive mode in which light emitted by the photoemitters 108 is measured by the photoreceptors 110 after the light has passed through the user’s fingertip. Any number and arrangement of the photoemitters 108 and photoreceptors 1 10 is contemplated as falling within the scope of the embodiments disclosed herein.

[0031] The pressure sensor module 112 is configured to measure the force applied by the fingertip to the physiological monitoring device 100. In the depicted embodiment, the pressure sensor module 112 is centrally located between the photoemitters 108 and photoreceptors 110. FIG. 3 depicts a cross-sectional side view of the sensor assembly 106, with one photoemitter 108, one photoreceptor 110 and the pressure sensor module 112 visible within a common sensor housing 116. In other embodiments, the pressure sensor module 112 and PPG module 114 are located in one or more separate housings. The pressure sensor module 112 includes a well 118 filled with a pressure transmitting medium 120, such as a flexible epoxy, silicone, or elastomer, that covers a forcedetector or pressure sensor 122. such as a membrane-based microelectromechanical systems (MEMS) device. The pressure transmitting medium 120 is filled to the upper surface of the well 118 of the sensor assembly 106. A profilometer can be used to ensure that the pressure transmitting medium 120 is flat and flush with the upper surface of the well 118, as depicted in FIG. 3. In the depicted embodiment, the upper surface of the pressure transmitting medium 120 is also flush with the upper surfaces of the photoemitter 108 and photoreceptor 110. In embodiments where the photoemitter 108, the photoreceptor 110, or both are protected by an optical glass or optical glue, the pressure transmitting medium 120 may be flush with the applicable protective layer. The term “flush” is herein defined to refer to a height difference of less than 250 micrometers (pm). The pressure sensor module 112 is configured for direct engagement with the user’s fingertip such that the application of force by the user’s fingertip on the surface of the sensor assembly 106 is transferred to the force detector or pressure sensor 122 through the pressure transmiting medium 120.

[0032] The pressure sensor module 112 and PPG module 114 are connected to control circuits 124 located in the housing 116 or on a printed circuit board (PCB) 126. The physiological monitoring device 100 also includes a batery 128 and onboard electronics 130. The control circuits 124 interface with the onboard electronics 130 to adjust the operation of the PPG module 114 and receive data from the PPG module 114 and pressure sensor module 112. The onboard electronics 130 are configured for processing signals generated by the sensor assembly 106 and exchanging data with a computing device 200 (e.g., a mobile phone, tablet, laptop or desktop computer) through a wired or wireless (e.g., Bluetooth or Wi-Fi) connection. The computing device 200 provides visual or audio instructions to the user. These instructions may include, but are not limited to, directions to adjust the position of the user’s fingertip onthe sensor assembly 106, to increase the force or pressure applied by the user’s fingertip on the pressure sensor module 112, to decrease the force or pressure applied by the user’s fingertip on the pressure sensor module 112, to warm the user’s fingertip, to increase circulation through the user’s fingertip, to change the finger that is used to contact the sensor assembly 106, to perform breathing exercises or other maneuvers to reduce the user’s stress, or to retake a force or pressure measurement. The computing device 200 is also adapted to display the results of the measurements made by the physiological monitoring device 100 and to store or transfer those results to other computer systems.

[0033] The physiological monitoring device 100 optionally includes a movement sensor 132. The movement sensor 132 can be an accelerometer or inertial measurement unit (IMU) which is configured to quantify the movement of the physiological monitoring device 100 during the measurement. The movement sensor 132 is designed to detect and report smaller movements including tremors, tilting and rotating, in addition to larger gross movements from the user. The movement data is provided to the computing device 200 for processing through a data connection.

[0034] The measurements made by the sensor assembly 106 can be used to generate an oscillometric curve by plotting the pulsative signals produced by the PPG module 114 on the y-axis as a function of pressure signals received by the pressure sensor module 112 on the x-axis. The pressure signals can be increased and decreased as the user follows instructions provided by the computing device 200 to modulate the force applied by the user’s fingertip to the pressure sensor module 112. The oscillometric graph can be analyzed and processed with suitable algorithms by the physiological monitoring device 100 or computing device 200 to determine the user’s diastolic and systolic blood pressures. Methods for determining blood pressure measurements, bloodoxygenation, or other physiological measurements from a combination of PPG and pressure signals are disclosed in United States Patent Nos. 10,265,002, 10,342,493, 11,129,575, 11,363,973, 11,412,987, and 11,517,265, and in United States Patent Application Publication Nos. 2015 / 0374249, 2021 / 0236013, and 2023 / 0034358, the disclosures of which are herein incorporated by reference as if fully set forth in this disclosure.

[0035] In the embodiment depicted in FIG. 2A, the PPG module 114 includes a pair of photoemitters 108a, 108b and a corresponding pair of photoreceptors 110a, 110b. In the embodiment depicted in FIG. 2B, three photoemitters 108a, 108b and 108c are presented in a staggered formation with three photoreceptors 110a, 110b and 110c on opposite sides of the pressure sensor module 112. A single photoemitter 108b is surrounded by two photoreceptors 110a, 110c above the pressure sensor module 112, while a single photoreceptor 110b is located between two photoemitters 108a, 108c below the pressure sensor module 112. The three pairs of photoemitters 108 and photoreceptors 1 10 are each capable of generating separate, multiple oscillometric curves, which can be used to determine if the finger is misplaced on the physiological monitoring device 100, or if the user rolls the finger forward-to-backward or side-to- side during the measurement.

[0036] Turning to FIG. 5, shown therein is a method 300 for carrying out a blood pressure measurement with the physiological monitoring device 100 and computing device 200. At step 302. the computing device 200 instructs the user to participate in a user assessment. If the user passes the user assessment at step 302, the method moves to step 304, and the user’s blood pressure measurement or other physiological analysis is earned out. Once the user has passed the user assessment 302. the physiological monitoring device 100 and computing device 200 can be configured to bypasssubsequent applications of the user assessment at step 302, or to periodically apply the user assessment at step 302, or to only return to the user assessment at step 302 if subsequent applications of the blood pressure measurement at step 304 are determined to yield unsatisfactory results. If, however, the user fails the user assessment at step 302, the process moves to step 306, and the blood pressure measurement test is aborted. The computing device 200 can be configured to provide the user with suggestions for passing subsequent attempts at the user assessment at step 302. For example, the user can be instructed to warm the user’s fingertip, increase circulation, or change the finger that is used to contact the sensor assembly 106.

[0037] Turning to FIGS. 6A-6D, shown therein are various embodiments of the user assessment identified as step 302 in FIG. 5. Generally, the user assessment includes one or more tests intended to identify disqualifying conditions before the user is permitted to proceed with the blood pressure or other measurement using the physiological monitoring device 100. As noted above, the disqualifying conditions may be based on certain physiological characteristics of the user, such as stiffness in the peripheral arteries, which can lead to low qualify measurements and thereby introduce unacceptable errors in the blood pressure estimation. Disqualifying conditions may include, but are not limited to, lack of suitable visuomotor skills, lack of finger dexterity, insufficient perfusion, smoking or other tobacco use, and arterial stiffness.

[0038] The user assessment includes one or more tests for the following conditions: (1) finger dexterity and visuomotor skills required to accurately track the pressure targets provided by the computing device 200 (a "‘finger dexterity” test); (2) perfusion to the arteries in the user’s finger (a “perfusion” test); (3) arterial stiffness (also referred to as compliance, which is the inverse of stiffness) in the arteries of the finger (an “arterial stiffness” test); and (4) peripheral vasoconstriction, including vasoconstriction arisingfrom smoking or psychological stress. It will be appreciated that these tests can be used alone, as depicted in FIG. 6A (a single test at step 308), or in any order in combination with one another, as depicted in FIG. 6B (two tests at steps 308 and 310), FIG. 6C (three tests at steps 308, 310 and 312), and FIG. 6D (more than three tests at steps 308, 310, 312 and 314).

[0039] The finger dexterity test determines whether the user can reliably and consistently exert the amount of force or pressure required for the blood pressure measurement at step 304. This user assessment test may require the user to follow instructions presented on the computing device 200 to increase the force or pressure applied by the finger on the pressure sensor module 112 to a target force or pressure level and then maintain the force applied by the user’s finger at or near the target force or pressure level for a specific time. The process may be repeated for a plurality of target force or pressure levels that approximate the ty pes of forces that will be needed for an accurate estimation of the user’s blood pressure. This assessment test may exclude users who have arthritis, Parkinson’s disease, or other diseases or conditions that adversely impact the user’s ability to effectively track the target force or pressure level with their finger.

[0040] The perfusion test ensures that the perfusion of the arteries in the finger is sufficiently high to allow for accurate measurement of the blood volume pulse waveform (PPG waveform) to be obtained using the PPG module 114 in the physiological monitoring device 100. The perfusion test is designed to identify users with Raynaud’s disease or other circulatory disorders, users with peripheral vascular disease, users with very cold hands, or users who otherwise have low perfusion to their extremities. The perfusion test includes adjusting the intensity of the light emitted by the photoemitters 108 to determine if the light received by the photoreceptors 110 is sufficient to obtain accurate measurements of blood flow through the digital arteries in the user’s fingertip.

[0041] The arterial stiffness test determines if the user’s arterial compliance in the finger is sufficiently high to allow for an accurate oscillometric blood pressure curve to be obtained. Long-time smokers and users with arteriosclerosis or other conditions that affect the stiffness of their peripheral arteries may not be suitable candidates for accurate blood pressure measurements that rely on user-applied forces for occluding the digital arteries in the user’s finger. The arterial stiffness test can require the user to increase the force applied by the finger on the pressure sensor module 112 until suitable occlusion of the digital artery is detected by the PPG module 114. If the PPG module 114 does not detect an appropriate extent of occlusion as the forces or pressures applied by the user’s fingertip reach specified levels, the test may result in the identification of a disqualifying condition. Additionally, if the oscillometric curve does not reflect changes in the blood volume pulsation (i.e., PPG amplitude) as the user presses the finger harder, thus increasing the externally applied pressure to the arterial wall, the test may identify a disqualifying condition due to arterial stiffness being too high for accurate measurements to be obtained.

[0042] FIG. 7 depicts oscillometric curves obtained with the physiological monitoring device 100 show n in FIGS. 1 and 2 for four different users. The first and second users produced oscillometric curves shown in solid black lines. The first and second users had normal healthy arterial stiffness values. For these users, as the externally applied pressure by the finger increased during the measurement period, the PPG amplitude (representing the blood volume pulse amplitude in the tissue volume being illuminated) first increased until the pressure applied was approximately equal to the mean arterial pressure, at which point the curve reached a maximum value, and then decreased as the externally applied pressure then exceeded the user’s systolic blood pressure and the artery began to occlude. The third and fourth users produced oscillometric curvesshown in dashed black lines. The third and fourth users had stiff arteries, which may have resulted from many years of smoking, arteriosclerosis, or other conditions leading to arterial stiffening. For the third and fourth users, as the pressure applied to the pressure sensor module 112 by the users’ fingers increased, there was only a small to moderate increase in PPG amplitude followed by a gradual decline in the PPG amplitude. Because of the lack of arterial compliance (i.e., high arterial stiffness), the changes in external pressure applied to the arterial wall did not make a large impact on the pulsatility of the artery' with each heartbeat. This presents an oscillometric curve with a flatter signature compared to the oscillometric curve with a narrower, taller signature expected from tests conducted on arteries that do not exhibit high arterial stiffness.

[0043] To automatically identify a normal or abnormal oscillometric curve signature, the physiological monitoring device 100 or connected computing device 200 is configured to calculate an arterial compliance amplitude ratio, which relates the maximum value of the oscillometric curves (all normalized to unity for FIG. 7) to the initial value at a low pressure. For example, for the first and second users with normal arterial stiffness, the arterial compliance amplitude ratio would be approximately 5 for the first user and 2.5 for the second user. In contrast, for the third and fourth users with high arterial stiffness, the corresponding arterial compliance ratios would be approximately 1.4 and 1.7, respectively. If the arterial compliance amplitude ratio of maximum blood volume pulse (PPG) amplitude to minimum is less than a threshold, such as 2, the user’s arterial compliance is considered insufficient to allow for accurate blood pressure measurements to be obtained at the finger. It will be appreciated that other thresholds are suitable for the arterial stiffness test in various embodiments. In some embodiments. data-driven methods are employ ed to determine the optimal threshold for thephysiological monitoring device 100, the user’s specific set of conditions, or both. In some embodiments, the threshold for the arterial compliance amplitude ratio is automatically adjusted based on the results of other user assessment tests.

[0044] Although the arterial stiffness test set forth herein is well-suited for use as a qualifying assessment for digital artery7blood pressure measurements, it will be appreciated that the same arterial stiffness test can be used as a standalone protocol for the non-invasive identification of arterial stiffness. Thus, the physiological monitoring device 100 can be used to identify stiff arteries, which may indicate other underlying health conditions such as arteriosclerosis or peripheral vascular disease.

[0045] Referring back to FIG. 2B, in exemplary embodiments, the main oscillometric curv e used for blood pressure estimation is derived from the blood volume pulsation (PPG) measurements obtained using the centralfy located photoemitter 108b and centrally located photoreceptor 110b. Simultaneously, oscillometric curves are derived from photoemitter 108a and photoreceptor 110a and photoemitter 108c and photoreceptor 110c from the lateral portions of the finger (i.e. one curve from the combination of photoemitter 108a and photoreceptor 1 10a, and another curve from the combination of photoemitter 108c and photoreceptor 110c). These additional curves from the sides of the finger can be used in processing to determine if the finger is misplaced to one side or the other side of the device, and thus be used to reject certain measurements where the misplacement of the finger will lead to erroneous blood pressure values. These additional curves may also be used in tandem with the main oscillometric curve (from photoemitter 108b and photoreceptor 110b) to correct for misplacement of the finger, leading to more accurate blood pressure determinations for the device. Additionally, the oscillometric curves derived from the photoemitter-photoreceptor pairs that are adjacent to one another (i.e., photoemitter 108b to photoreceptor 110a, photoemitter108b to photoreceptor 110c, photoemitter 108a to photoreceptor 110b, and photoemitter 108c to photoreceptor 110b) are measured and used to determine if the forwardbackward placement of the finger is appropriate. If not, these additional curves can be used to either reject the measurement as inaccurate or correct the measurement in software.

[0046] Thus, using the oscillometric curves generated by the various pairs of photoemitters 108 and photoreceptors 110, the physiological monitoring device 100 and computing device 200 can determine whether the user’s finger was properly placed on the sensor assembly 106. FIGS. 8A-8C depict correct and incorrect positioning of the user’s finger on the sensor assembly 106, while FIGS. 9A-9C provide oscillometric curves generated by the correct and incorrect finger positioning. The proper placement of the finger on the sensor assembly 106 in FIG. 8 A produced three resulting oscillometric curves from the pairs of photoemitters 108 and photoreceptors 110, as depicted in FIG. 9A. The three oscillometric curves are coherent and consistent, which demonstrates accurate finger placement. In contrast the finger is angled forward in FIG. 8B, which produced inconsistent PPG-pressure data, as illustrated by the offset oscillometric curves in FIG. 9B. Similarly, FIG. 8C demonstrates an incorrect finger placement in which the distal portion of the finger is not making good contact with the sensor assembly 106, which likewise produced the inconsistent oscillometric curves illustrated in FIG. 9C. Note that the depictions of incorrect finger placement in FIGS. 8B and 8C are exaggerated. In some instances, it may be difficult to visually observe incorrect finger placement, which could otherwise lead to undetected errors in the data obtained from the sensor assembly 106.

[0047] The multiple pairs of photoemitters 108 and photoreceptors 110 are thusly used to assess the uniformity with which the finger presses downward on the device. Bylooking for incoherence or excess variability between the oscillometric curves produced by the multiple pairs of photoemitters 108 and photoreceptors 110, the physiological monitoring device 100 or computing device 200 can either reject measurements due to non-uniform application of finger pressure, or apply a correction factor to the blood pressure or other measurements generated by the physiological monitoring device 100.

[0048] The quality of the oscillometric curve can also be quantified based on machine learning algorithms to determine whether the blood pressure outputted from such a curve can be reliable or not. An oscillometric curve derived from a properly performed measurement using the physiological monitoring device 100 has a particular shape that includes characteristics that can be learned by an algorithm based on ground truth labeling of existing data by experts in the field. An oscillometric curve with the proper shape indicates that the sensor assembly 106 of the physiological monitoring device 100 accurately detected the arterial pulse information that captures uniform pressure- induced occlusion of vessels within the volume of tissue being interrogated.

[0049] The shape of the oscillometric curve itself can therefore be used as a “diagnostic” standard to determine if measurements determined from the oscillometric curve are likely to be accurate. In this way, the shape of the resulting oscillometric curve can be used as a classifier to exclude low quality curves that w ould otherwise produce errors in blood pressure determination based on this finger-pressing oscillometric curve generation methodology. A machine learning algorithm can be trained on existing datasets of oscillometric curves that are labeled as “acceptable” and “unacceptable” by experts in the field. Additionally, certain features of the oscillometric curve that are determined to be important markers of “high” versus “low” quality curves are identified and used to assess the quality of the curve. For example, a flat oscillometric curve is determined to be one where the user’s arterial compliance is not sufficiently high toallow for a high quality determination of blood pressure to occur at the finger. Additionally, the value of the blood volume pulse at the highest pressure values of the oscillometric curve are quantified and it is determined if the value is low enough to reflect that the arteries were properly occluded. Additionally, the nature of the peak of the oscillometric curve is assessed to determine if multiple vessels within the tissue volume were occluded at different pressures, suggesting non-uniform application of pressure by the user. Examples of “high” and “low” quality oscillometric curves are shown in FIGS. 10A and 10B, respectively.

[0050] FIG. 11 provides a process flow diagram for a method 400 of using a classifier based on the quality of the oscillometric curves produced by the physiological monitoring device 100. The classifier is used to examine the oscillometric curve and determine whether it is of sufficiently high quality to proceed with blood pressure determination. The classifier type can be a tree-based model, such as extreme Gradient Boosting (XGBoost), though many other models could be used to produce similarly reliable results. The process to optimize, test, and deploy the classifier involves developing a dataset at step 402 based on previously obtained oscillometric curves that have been labeled with reference blood pressures and quality labels by experts in the field. The hyperparameters (maximum depth of a tree and the number of trees) of the classifier can be optimized using five-fold cross validation with non-overlapping users to ensure generalizability to unseen users. Specifically, the parameters of the classifier can be trained using the quality labels using the held-in training set. Next, the standard deviation of the SBP errors was computed from the reference and the determined SBP in the held-out test set. The hyperparameter set with the lowest test error was selected as the optimal set. Eventually, the final classifier deployed was optimized using the optimal hyperparameter set and the whole dataset collected.

[0051] Once the dataset or model has been developed at step 402, the deployment of the classifier continues to step 404 when the measured oscillometric curve is obtained. At step 406, the measured oscillometric curve is evaluated against the model or dataset developed at step 402. The automated comparison can then determine if the measured oscillometric curve sufficiently matches the dataset, i.e., is an acceptable quality7oscillometric curve. If the oscillometric cun e is determined to be unacceptable, i.e., a low quality7oscillometric curve, then the low quality7oscillometric curve is discarded at step 408 without providing the basis for a blood pressure or other physiological measurement. The trained dataset of known acceptable and unacceptable oscillometric curves can be updated with the comparison oscillometric curves.

[0052] In this way, the oscillometric curves produced by the physiological monitoring device 100 can be evaluated to determine if the measurement data underlying the oscillometric curve is sufficiently accurate and reliable to serve as the basis for blood pressure measurements. Insufficient coherence between multiple oscillometric curves obtained by the multiple pairs of photoemitters 108 and photoreceptors 110 indicates improper finger placement on the physiological monitoring device 100. If the measured oscillometric curve has a shape that cannot be matched through machine learning with a trained dataset of acceptable, high quality oscillometric curves, the measured cun e can be discarded to avoid erroneous physiological calculations based on the low quality curve.

[0053] As noted in FIG. 10B, unwanted shaking or other movements during the measurement process can also lead to low quality oscillometric curves. Unlike conventional brachial cuffs, the physiological monitoring device 100 requires the user to apply variable pressures to the sensor assembly 106 to partially or completely occlude arteries in the user’s finger. For most users, this requires holding the physiological monitoring device100 in one hand (non-dominant hand) and pressing the finger from the other hand (dominant hand) onto the physiological monitoring device 100 to perform the measurement. This means that any movements of the physiological monitoring device 100 during the measurement can contaminate the measured signals and lead to erroneous data. As noted above, the physiological monitoring device 100 includes one or more movement detectors 132 that are configured to track changes in the position and orientation of the physiological monitoring device 100 during measurement.

[0054] FIG. 12 provides a method 410 of detecting movement-based errors in the measurement data obtained by the physiological monitoring device 100. At step 412, the movement detector 132 collects motion and orientation data for the physiological monitoring device 100 during a measurement. The motion data is compared against threshold acceptable values for movement of the physiological monitoring device 100. If the detected motion exceeds the threshold acceptable value for movement, the measurements are discarded at step 414 without serving as the basis for blood pressure or other calculations. If the motion data is present but within an acceptable range, the motion data can be used as the basis for determining a correction factor at step 416 that can be applied to the oscillometric curve or to the measurement of blood pressure or other health parameters determined from the oscillometric curve to account for the influence of the motion data.

[0055] Another potential source of data errors arises from the inconsistent or inaccurate application of pressure by the user to the pressure sensor module 112. FIG. 10B includes an oscillometric curves that were generated from inconsistent application of finger pressure on the sensor assembly 106 and poor pressure tracking. The ability of the user to generate a uniform pressure that accurately tracks the instructed value provided on the screen of the computing device 200 is important in ensuring thataccurate blood pressure measurements are obtained by the physiological monitoring device 100. Unlike a traditional cuff that can be inflated to exert a relatively constant pressure, the physiological monitoring device 100 relies on the user carefully applying pressure to the physiological monitoring device 100 in accordance with the instructions provided by the computing device 200 to occlude the arteries contained in the tissue volume.

[0056] The physiological monitoring device 100 or computing device 200 includes application-enabled processes to assess the quality of the pressure tracking of the user and to make determinations if this pressure tracking is not performed with sufficient accuracy for subsequent blood pressure determination. If the pressure tracking is insufficiently accurate, the physiological monitoring device 100 or computing device 200 can be configured to reject data from certain segments of time during a measurement or data from the entire measurement.

[0057] The pressure tracking behavior of the user is quantified by several metrics. First, the amount of time during the measurement where the user does not track the pressure within a given error bound (e.g., 5 mmHg) is quantified, and if quantified time exceeds a threshold (e.g., 30% of the overall measurement time) the measurement is determined to be too noisy to proceed. Second, the size of pressure deviations from the target value are quantified and compared to a threshold value (e.g., a maximum deviation of 20 mmHg) to determine if the measurement is too noisy to proceed. Third, the number of times that the user-applied pressures cross a boundary that is shown to the user is compared against a threshold. The boundary may be. for example, a box that is depicted on the same screen as a graphic or symbol that represents the amount of real-time pressure applied by the user, where the graphic or symbol remains within the box when the pressure applied by the user is within a suitable range and the graphic or symbolmoves beyond the box when the pressure applied by the user is outside of a suitable range). Fourth, the errors made by the user in tracking can be weighted differently when at critical times of the measurement (e.g., surrounding the peak of the oscillometric curve) as compared to other times that are less critical (e.g., when the arteries are already occluded or when the pressures are so low that the main portions of the oscillometric curve are not defined by the values that are corrupted). Fifth, the segments of time when the user’s pressure tracking is not sufficiently close to the target value can be discarded and the remaining segments can be used to derive the oscillometric curve.

[0058] FIG. 13 provides a simplified method 418 for monitoring the accuracy of pressure applied by the user to the physiological monitoring device 100. At step 420, the physiological monitoring device 100 or computing device 200 monitors the application of pressure during the measurement to determine whether the applied pressures adequately track with the instructed pressures. If the applied pressures deviate from the instructed pressures beyond a cumulative amount for the entire measurement cycle or beyond discrete levels for certain periods of the measurement cycle, the erroneous data can be discarded at step 422.

[0059] The physiological parameter monitoring system formed by the combination of the physiological monitoring device 100 and the computing device 200 is subject to various errors that can be addressed through a variety of methods disclosed herein. It will be appreciated that these various methods can be used alone or in various combinations depending on the user and the errors introduced during the measurement cycle. For example. FIG. 14 presents a method 424 for ensuring accuracy from digital oscillometric measurements. The method 424 beings at step 426 when a determination is made (by the physiological monitoring device 100 or computing device 200) whether the measured curve is of sufficiently high quality. The measured oscillometric curvecould lack sufficient quality based on a number of factors, including inaccurate finger position. The shape or coherence of the measured oscillometric curve can be compared against a library' of curves of known quality to determine if the measured oscillometric curve is acceptable. If the quality of the measured oscillometric curve is insufficient, the method moves to step 428, and the measurement data is discarded.

[0060] If the measured oscillometric curve demonstrates sufficient quality at step 426, the method progresses to step 430 in which the movement of the physiological monitoring device 100 or finger during the measurement cycle is evaluated. It will be appreciated that excess movement during the measurement cycle may also impact the analysis of the shape or quality of the curve a step 426, but a separate quantitative determination can be made at step 430 for the movement of the physiological monitoring device 100 during the measurement cycle. If the movement of the physiological monitoring device 100 at discrete times during the measurement cycle or during the entire measurement cycle exceeds an acceptable threshold, the method 424 moves to step 428, and the data is discarded.

[0061] If the measured data falls within the acceptable range of movement data at step 430, the method moves to step 432 in which the data is evaluated for compliance with the pressure tracking standards. As explained above, it is important to accurately follow the pressure application instructions to ensure accurate findings from the measured oscillometric curve. If the measurement data reveals good compliance with the instructed pressures, the method moves to step 434 and the measured oscillometric curve is used as the basis for determining the user's blood pressure or other physiological parameter. If the measurement data reveals an insufficient level of accuracy for matching the instructed pressures, the data can be discarded at step 428 or used as the basis for a correction factor applied to the measured oscillometric curve orthe findings produced from the measured oscillometric curve. If will be understood that the various steps outlined in FIG. 14 are non-limiting and exemplary embodiments include methods 424 in which the order of these steps is changed or various steps are omitted or combined.

[0062] In the foregoing specification, the invention has been described with reference to specific embodiments thereof. However, it will be evident that various modifications and changes can be made thereto without departing from the broader scope of the invention as set forth in the appended claims. Accordingly, the specification is to be regarded in an illustrative rather than a restrictive sense. For example, different photoemitters, initial pressures, pressure targets, physiological monitoring devices, optical sensors, and electronic circuits not specifically identified or described in this disclosure or not evaluated in a particular embodiment are still expected to be within the scope of this invention.

[0063] The present invention may suitably comprise, consist of, or consist essentially of the elements disclosed and may be practiced in the absence of an element not disclosed. As used herein, the singular forms ‘'a,” '‘an,” and “the” are intended to include the plural forms as well, unless the context clearly indicates otherwise. As used herein, the term “about” in reference to a given parameter is inclusive of the stated value and has the meaning dictated by the context (e.g., it includes the degree of error associated with measurement of the given parameter). As used herein, the term “and / or” includes any and all combinations of one or more of the associated listed items.

Claims

It is claimed:

1. A method for measuring a user’s blood pressure with a physiological monitoring device that includes a sensor assembly with a PPG module and a pressure sensor module, the method comprising the steps of: placing a body part on the physiological monitoring device such that the body part is in contact with the sensor assembly; conducting a user assessment comprising one or more user assessment tests; and measuring the user’s blood pressure with the physiological monitoring device if the user passes the user assessment.

2. The method of claim 1, wherein the one or more user assessment tests are selected from the group consisting of a finger dexterity test, a perfusion test, and an arterial stiffness test.

3. The method of claim 2, wherein the step of conducting the user assessment comprises conducting a single user assessment test selected from the group consisting of a finger dexterity test, a perfusion test, and an arterial stiffness test.

4. The method of claim 2, wherein the step of conducting the user assessment comprises conducting two user assessment tests selected from the group consisting of a finger dexterity test, a perfusion test, and an arterial stiffness test.

5. The method of claim 2, wherein the step of conducting the user assessment comprises conducting three user assessment tests selected from the group consisting of a finger dexterity' test, a perfusion test, and an arterial stiffness test.

6. The method of claim 2, wherein the step of conducting the user assessment comprises conducting more than three user assessment tests selected from the group consisting of a finger dexterity test, a perfusion test, and an arterial stiffness test.

7. The method of claim 1, wherein the one or more user assessment tests comprise an arterial stiffness test comprising the steps of placing a finger on the physiological monitoring device such that the finger is in contact with the sensor assembly; instructing the user to apply a range of pressures to the pressure sensor module during a measurement cycle; creating a measured oscillometric curve based on PPG data and pressure sensor data retrieved during the measurement cycle; determining a maximum value of the oscillometric curve; determining an initial value of the oscillometric curve when the user is applying a pressure; calculating an arterial compliance amplitude ratio that relates the maximum value of an oscillometric curve to the initial value of the oscillometric curve; and determining if the arterial compliance amplitude ratio is less than a predetermined threshold for identifying arterial stiffness that disqualifies accurate use of the physiological monitoring device.

8. The method of claim 1, wherein the one or more user assessment tests comprise an arterial stiffness test comprising the steps of: placing a finger on the physiological monitoring device such that the finger is in contact with the sensor assembly;instructing the user to apply a range of pressures to the pressure sensor module during a measurement cycle; creating a measured oscillometric curve based on PPG data and pressure sensor data retrieved during the measurement cycle; determining a maximum value of the oscillometric curve; determining an initial value of the oscillometric curve; calculating an arterial compliance amplitude ratio that relates the maximum value of an oscillometric curve to the initial value of the oscillometric curve; and determining if the arterial compliance amplitude ratio is less than a predetermined threshold for identifying arterial stiffness that disqualifies accurate use of the physiological monitoring device.

9. A method for measuring a user’s blood pressure with a physiological monitoring device that includes a sensor assembly with a PPG module and a pressure sensor module, the method comprising the steps of: placing a finger on the physiological monitoring device such that the finger is in contact with the sensor assembly; instructing the user to apply a range of pressures to the pressure sensor module during a measurement cycle; creating a measured oscillometric curve based on PPG data and pressure sensor data retrieved during the measurement cycle; and determining whether the measured oscillometric curve is based on unreliable or incorrect data before calculating the user’s blood pressure from the measured oscillometric cune.

10. The method of claim 9, wherein the step of determining whether the measured oscillometric curve is based on unreliable or incorrect data comprises the step of comparing the measured oscillometric curve to a library of oscillometric curves of known quality7.

11. The method of claim 9, wherein the step of determining whether the measured oscillometric curve is based on unreliable or incorrect data comprises the steps of: detecting motion of the physiological monitoring device during the measurement cycle; and determining if the detected motion exceeds a permitted threshold.

12. The method of claim 9, wherein the step of determining whether the measured oscillometric curve is based on unreliable or incorrect data comprises the steps of: monitoring the application of the range of pressure during the measurement cycle; and determining if the applied pressures deviate by more than a permitted threshold from the range of instructed pressures.

13. A method for measuring a user's blood pressure comprising the steps of: providing a sensor assembly that comprises: a PPG module with a first pair of photoemitters and photoreceptors, a second pair of photoemitters and photoreceptors, and a third pair of photoemitters and photoreceptors; and a pressure sensor module in a central location between the second pair of photoemitters and photoreceptors; placing a finger of the user on the physiological monitoring device such that the finger is in contact with the PPG module and the pressure sensor module;instructing the user to apply a range of pressures to the pressure sensor module during a measurement cycle; simultaneously generating a first oscillometric curve from the first pair of photoemitters and photoreceptors, a second oscillometric curve from the second pair of photoemitters and photoreceptors, and a third oscillometric curve from the third pair of photoemitters and photoreceptors; and determining if the user’s finger is centrally located over the pressure sensor module to permit an accurate blood pressure measurement by comparing the first, second and third oscillometric curves.

14. The method of claim 13. further comprising the step of measuring the user’s blood pressure if the user’s finger is centrally located over the pressure sensor module.

15. The method of claim 13, further comprising the step of applying a correction factor to the measurement of the user’s blood pressure if the user’s finger is not centrally located over the pressure sensor module.

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