Monitoring blood pressure using haptic devices

Abstract

A system, a computer implemented method, and a mobile computing device for monitoring blood pressure using haptic devices. For instance, a system includes a biometric sensor of a mobile computing device, the biometric sensor generating biometric data indicative of blood flow of a user as the user contacts the mobile computing device proximate the biometric sensor. The system further includes a haptic device for generating vibrations. Additionally, the system includes a computing system that controls the haptic device to generate the vibrations at varying frequencies while the haptic device is held proximate the user to vary pressure applied via the user at the biometric sensor. The computing system receives the biometric data generated by the biometric sensor while the vibrations are applied at the varying frequencies, and determines a blood pressure of the user based at least in part on the biometric data and the varying frequencies.

Description

[0001] MONITORING BLOOD PRESSURE USING HAPTIC DEVICES

[0002] FIELD OF THE INVENTION

[0003] [1] The present disclosure relates generally to monitoring blood pressure of a user using haptic devices. More particularly, the present disclosure relates to monitoring blood pressure of a user based on sensor data obtained from one or more biometric sensors of a mobile computing device while a haptic device held proximate the user generates vibrates at varying frequencies as a user contacts the mobile computing device proximate the biometric sensor, where the vary ing frequencies vary the pressure applied via the user at the biometric sensor.

[0004] BACKGROUND

[0005] [2] In general, blood pressure is a measure of the pressure or force in arteries as a heart pumps. Blood pressure is usually provided as a combination of systolic blood pressure, which is a measure of the pressure inside the arteries when the heart beats, and diastolic blood pressure, which is a measure of the pressure inside the arteries when the heart rests between beats. Traditional blood pressure cuffs are often used to apply pressure to a peripheral artery (e.g., in the arm or wrist) in a controlled manner for determining blood pressure. For instance, the pressure applied by the cuff at which blood flow in the peripheral artery is momentarily stopped is the systolic blood pressure, and the pressure at which blood flows again without turbulence in the peripheral artery as the pressure from the cuff is released is indicative of the diastolic blood pressure. Traditional manual methods with a pressure cuff require a facilitator to listen to the blood flow (e.g., using a stethoscope) to determine when blood flow stops (or restarts after stopping) and when blood flow is normal again, where such flows are associated with particular sounds (e.g.. Korotkoff sound phases). Some automated pressure cuffs similarly utilize an audio sensor to monitor the blood flow, however some automated pressure cuffs additionally, or alternatively, use pressure transducers to generate oscillometric pulsation waveforms indicative of blood pressure for determining the blood pressure.

[0006] [3] There are several issues with traditional blood pressure cuffs. For instance, traditional blood pressure cuffs require user training for accurately measuring blood pressure.

[0007] Moreover, if a user needs to take multiple blood pressure measurements a day, they may need to travel with their blood pressure cuff (and reader, for automated devices), which may be cumbersome. These issues lead to poor user adoption and monitoring compliance. As such, cuffless approaches for implementing blood pressure sensing on portable electronic devices to help improve adoption and compliance is a top industry challenge. Some cuffless approaches include using pulse wave analysis (PWA), with or without pulse arrival time (PAT), on data from biometric sensors, such as photoplethysmography (PPG) sensors, to determine blood pressure. However, current cuffless methods do not meet clinical accuracy requirements and are inconsistent across demographics.

[0008] [4] As such, a need exists for systems and methods for accurately monitoring blood pressure without a traditional cuff.

[0009] SUMMARY OF THE INVENTION

[0010] [1] Aspects and advantages of embodiments of the present disclosure will be set forth in part in the following description, or can be learned from the description, or can be learned through practice of the embodiments.

[0011] [2] In one aspect, the present subject matter is directed to a system for determining blood pressure. The system may include a biometric sensor of a mobile computing device configured to generate biometric data indicative of blood flow of a user as the user contacts the mobile computing device proximate the biometric sensor. The system may further include a haptic device configured to generate vibrations. Additionally, the system may include a computing system configured to control the haptic device to generate the vibrations at varying frequencies while the haptic device is held proximate the user to vary pressure applied via the user at the biometric sensor. The computing system may further be configured to receive the biometric data generated by the biometric sensor while the vibrations are applied at the vary ing frequencies. Additionally, the computing system may be configured to determine a blood pressure of the user based at least in part on the biometric data and the varying frequencies.

[0012] [3] In one more aspect, the present subject matter is directed to a computer-implemented method that is capable of conducting the functionality7described above with respect to the computing system.

[0013] [4] In another aspect, the present subject matter is directed to a mobile computing device. The mobile computing device may include a biometric sensor configured to generate biometric data indicative of blood flow of a user as the user contacts the mobile computing device proximate the biometric sensor. The mobile computing device may further include a haptic device configured to generate vibrations. Additionally, the mobile computing device may include a computing system configured to control the haptic device to generate the vibrations at varying frequencies while the haptic device is proximate the user to vary pressure applied via the user at the biometric sensor. Moreover, the mobile computing device may be configured to receive the biometric data generated by the biometric sensor while the vibrations are applied at the varying frequencies. The computing device may additionally be configured to determine a blood pressure of the user based at least in part on the biometric data and the varying frequencies.

[0014] [5] These and other features, aspects, and advantages of various embodiments of the present disclosure will become better understood with reference to the following description and appended claims. The accompanying drawings, which are incorporated in and constitute a part of this specification, illustrate example embodiments of the present disclosure and, together with the description, serve to explain the related principles.

[0015] BRIEF DESCRIPTION OF THE DRAWINGS

[0016] [6] Detailed discussion of embodiments directed to one of ordinary skill in the art is set forth in the specification, which makes reference to the appended figures, in which:

[0017] [7] FIG. 1 illustrates a system having one or more example mobile computing devices for monitoring blood pressure of a user according to example aspects of the present disclosure;

[0018] [8] FIG. 2 illustrates an example of a user using a mobile computing device for monitoring blood pressure in accordance with aspects of the present disclosure;

[0019] [9] FIG. 3 illustrates an example of a biometric sensor positioned relative to pressure sensors of a mobile computing device in accordance with aspects of the present disclosure;

[0020]

[0010] FIG. 4 illustrates various components of an example computing system that can be utilized according to one embodiment of the present disclosure;

[0021]

[0011] FIG. 5 illustrates a schematic diagram of an example set of devices of the computing system that are able to communicate according to one embodiment of the present disclosure;

[0022]

[0012] FIGS. 6A-6C illustrate graphs evaluating PPG sensor data and pressure sensor data during a blood pressure monitoring event with the disclosed system according to an example embodiment of the present disclosure; and

[0023]

[0013] FIG. 7 illustrates a flow diagram of an example, non-limiting computer-implemented method for monitoring blood pressure using haptic devices according to example embodiments of the present disclosure.

[0024]

[0014] Reference numerals that are repeated across plural figures are intended to identify the same features in various implementations. DETAILED DESCRIPTION

[0025]

[0015] Reference will now be made in detail to embodiments of the invention, one or more examples of which are illustrated in the drawings. Each example is provided by way of explanation of the invention, not limitation of the invention. In fact, it will be apparent to those skilled in the art that various modifications and variations can be made in the present invention without departing from the scope or spirit of the invention. For instance, features illustrated or described as part of one embodiment can be used with another embodiment to yield a still further embodiment. Thus, it is intended that the present invention covers such modifications and variations as come within the scope of the appended claims and their equivalents.

[0026]

[0016] Generally, the present subject matter is directed to using haptic feedback hardware existing in consumer devices (e.g., phone, watch, tablet, etc.) when taking a blood pressure measurement with a biometric sensor to provide a more accurate blood pressure reading based on the biometric sensor data. For instance, the present subject matter is directed to using haptic devices to apply vibrations to the user at known frequencies to vary the pressure applied via the user at the biometric sensor in a controlled manner. The known frequencies may be accounted for in blood pressure analysis based on the biometric sensor readings and, optionally with pressure sensor readings, to determine the blood pressure reliably and repeatably without a traditional blood pressure cuff.

[0027]

[0017] As described above, blood pressure is a measure of the pressure or force in arteries as a heart pumps. Using a traditional blood pressure cuff requires user training for accurately measuring blood pressure. Moreover, if a user needs to take multiple blood pressure measurements a day, they may need to travel with their blood pressure cuff (and reader, for automated devices), which may be cumbersome. These issues lead to poor user adoption and monitoring compliance. As such, cuffless approaches for implementing blood pressure sensing on portable electronic devices to help improve adoption and compliance is atop industry challenge. However, current cuffless approaches on data from optical sensors do not meet clinical accuracy requirements and are inconsistent across demographics.

[0028]

[0018] Using optical sensors in combination with pressure sensors provides a more reliable cuffless method for detecting blood pressure. For instance, a user may press (e.g., with their finger, arm, etc.) at an optical biometric sensor (e.g., PPG sensor, ultrasonic sensor, etc.) with increasing pressure, where the pressure associated with the arteries proximate the biometric sensor closing (e.g., as determined based on biometric data from the biometric sensor) is indicative of systolic pressure. A user may then reduce the pressure at the biometric sensor until it is detected that the arteries have reopened to confirm the pressure associated with the systolic pressure. A diastolic pressure may be determined (e.g., retroactively) based on the systolic pressure and the mean arterial pressure (MAP) determined from the biometric data. The pressure applied by the user at the biometric sensor during such measurement operation may be determined by one or more pressure sensors. However, a user’s applied force or pressure is variable and inconsistent between subsequent measurements, which can result in different blood pressure readings. Moreover, it may be difficult for some users to apply sufficient force for the measurement.

[0029]

[0019] As such, haptic devices can be used to apply vibrations to the user at known frequencies as the user contacts a mobile computing device proximate an optical, biometric sensor to vary the pressure applied via the user at the optical, biometric sensor for generating data indicative of blood pressure. In general, higher frequencies cause increased deflection of the user, and thus, increased pressure applied at the optical sensor. The known vibration frequencies may be accounted for when determining the user's blood pressure based on the data generated by the biometric sensor and, optionally, based at least in part on the data from the pressure sensor, to determine the blood pressure reliably and repeatably without a traditional cuff. Additionally, by using haptic feedback and optical sensing devices in commonly adopted mobile consumer devices, blood pressure monitoring compliance is improved. In some instances, the haptic device hardware may be in the same device as and / or in a different device from the biometric sensor.

[0030]

[0020] With reference now to the figures, example embodiments of the present disclosure will be discussed in further detail.

[0031]

[0021] Referring now to the drawings, FIGS. 1-3 illustrate aspects of a system having one or more mobile computing devices for monitoring blood pressure using haptic devices in accordance with aspects of the present subject matter. For instance, FIG. 1 illustrates a system 100 having one or more example mobile computing devices for monitoring blood pressure of a user, FIG. 2 illustrates an example of a user using a mobile computing device for monitoring blood pressure, and FIG. 3 illustrates an example of a biometric sensor positioned relative to pressure sensors of a mobile computing device in accordance with aspects of the present disclosure.

[0032]

[0022] In particular, as shown in FIG. 1, a system 100 for monitoring blood pressure may include one or more mobile computing devices, such as one or more wearable computing devices, such as a watch 102, a ring 130, earbuds 140 (FIG. 5), and / or the like, and / or one or more other computing devices, such as a mobile phone(s) 120, a tablet device(s) 150 (FIG. 5), a laptop (not shown), a standalone blood pressure monitoring device (not shown), and / or the like. For example, the system 100 may include the wearable computing device 102 worn on a user or wearer’s forearm 101 like a wristwatch. Thus, as shown, the wearable computing device 102 may include a wristband 103 for securing the wearable computing device 102 to the user or w earer’s forearm 101. However, it should be appreciated that the wearable computing device 102 may be worn at any other suitable location by a user, such as, for example, on an ankle. It should be further appreciated that the wearable computing device 102 can include a ring (e.g., the ring 130), band, earring, necklace, or any other suitable w earable computing device known by one of skill in the art.

[0033]

[0023] In addition, the w earable computing device 102 has a housing 104 that defines an interior volume for containing electronics associated with the wearable computing device 102. Moreover, the wearable computing device 102 has an outer covering 105 on an upper side for enclosing the interior volume. In an embodiment, the outer covering 105 may be constructed of glass, polycarbonate, acrylic, or similar. Further, as show n in FIG. 1, the wearable computing device 102 includes an electronic display screen 106 arranged within the housing 104 and viewable through the outer covering 105. The electronic display screen 106 may cover an electronics package (not shown), which may also be housed within the housing 104. The display 106 may be any suitable display, such as a touch screen, organic light emitting diode (OLED), or liquid crystal display (LCD). Moreover, as shown, the wearable computing device 102 may also include one or more buttons 108 that may be implemented to provide a mechanism to activate various mechanisms and / or sensors of the wearable computing device 102, such as to collect certain health data of the user. The housing 104 of the wearable computing device 102 further defines a lower side configured to contact a user (e.g., a dorsal wrist) when being worn by the user.

[0034]

[0024] The wearable computing device 102 may include one or more motion sensors contained within the housing 104 of the w-earable computing device 102 for generating motion data, which can be used, inter alia, to calculate step count, pulse, etc. The motion sensor(s) can include one or more accelerometers for sensing movement data. In some embodiments, the motion sensor(s) can include one or more accelerometers for sensing acceleration or other movement data in each of, for example, three directions (x, y, and z), which may be orthogonal. For instance, the accelerometer can be a triaxial accelerometer. The motion sensor(s) additionally can include one or more gyroscopes for sensing rotation data. In some embodiments, the motion sensor(s) can include one or more gyroscopes for sensing rotation about each of, for example, three axes, which may be orthogonal. The motion sensor(s) additionally can include one or more altimeters, such as a pressure or barometric altimeter. In one or more instances, the motion sensor(s) may include an inertial measurement unit (IMU), which may include a combination of accelerometers and gyroscopes, and / or the like. In some instances, one or more motion sensors (e.g., strain gauges, accelerometers, and / or the like) may be configured as a ballistocardiogram (BCG) sensor for monitoring movement or displacement due to ballistic forces caused by movement of blood with each heartbeat.

[0035]

[0025] Moreover, while not shown in particular detail, the wearable computing device 102 may also include a plurality of sensor electrodes. For instance, the wearable computing device 102 includes one or more pairs of sensor electrodes on the lower side of the housing 104 so as to maintain skin contact with the user when being worn by the user and configurable to measure, at least, electrical impedance of the user at a location of the skin contact (e.g., on the dorsal wrist), which is associated with electrodermal activity data, and / or the like. In some instances, one or more sensor electrodes may be positioned elsewhere on the wearable computing device 102 for selective biometric measurements.

[0036]

[0026] In one or more instances, while not shown, the electrodes of the wearable computing device 102 may also include at least one pair of electrodes on the upper side of the wearable computing device 102 for active or on-demand measurement of biometrics (e.g., electrocardiogram (ECG), electrodermal activity (EDA), etc.) of the user wearing the wearable computing device 102. For instance, in some implementations, the user can contact (e.g., touch) the electrodes on the upper side of the wearable computing device 102 where the electrodes on the upper side of the wearable computing device 102 in combination with data from the electrodes on the lower side of the wearable computing device 102 act as an ECG sensor to obtain an on-demand electrocardiogram reading. Alternatively, or additionally, the user can contact (e.g. touch) the electrodes on the upper side of the wearable computing device 102, where the data from the electrodes on the upper side of the wearable computing device 102 is used alone as an EDA sensor to obtain an on-demand electrodermal activity7reading. In some implementations, the electrodes on the upper side of the wearable computing device 102 are spaced apart from one another. In some instances, the electrodes on the upper side of the wearable computing device 102 are positioned on an upper surface of the cover 105 and / or wrap around a perimeter of the cover 105. Alternatively, or additionally, the sensor electrodes are positioned at any other suitable location on the wearable computing device 102 such that the sensor electrodes are able to be selectively (e.g., “actively’’) contacted by a user while wearing the wearable computing device 102 for taking an active measurement.

[0037]

[0027] In some embodiments, the wearable computing device 102 may also include one or more temperature sensors (such as an ambient temperature sensor or a skin temperature sensor), a humidity sensor, an ambient light sensor, a microphone, a distance sensor, and / or the like.

[0038]

[0028] Further, in accordance with aspects of the present subject matter, the wearable computing device 102 includes one or more optical biometric sensors, such as one or more photoplethysmography (PPG) sensors 110. The PPG sensor(s) 110 has one or more emitters 110E (FIGS. 2 and 3), such as one or more light-emitting diodes (LEDs), for emitting controlled pulses of light and has one or more detectors HOD (FIGS. 2 and 3), such as photodiodes, to generate data indicative of the detected, returned light. Some PPG technologies rely on detecting light at a single spatial location, adding signals taken from two or more spatial locations, or an algorithmic combination thereof. Both of these approaches result in a single spatial measurement from which the heart rate (HR) estimate, blood pressure, or other physiological metrics is determined. In some embodiments, the PPG sensor(s) 110 employs a single emitter 1 10E associated with a single detector HOD (i.e.. a single light path). Additionally, or alternatively, the PPG sensor(s) 110 may employ multiple emitters 110E coupled to a single detector 110D or multiple detectors 110D (i.e., two or more light paths). In other embodiments, the PPG sensor(s) 110 may additionally, or alternatively, employ multiple detectors HOD coupled to a single light emitter 110E or multiple emitters

[0039] 1 10E (i.e., two or more light paths).

[0040]

[0029] One or more PPG sensors 110 may be disposed proximate the lower side of the housing 104 of the wearable computing device 102 so as to make and maintain skin contact with the user when being worn on the wrist by the user for passively measuring biometrics, such as pulsatihty and heart rate, resting heart rate, interbeat interval, heart rate variability, and / or the like. In some instances, one or more PPG sensors 110 may additionally, or alternatively, be positioned elsewhere on the wearable computing device 102, such as on a perimeter of the wearable computing device 102, on an upper surface of the wearable computing device 102. proximate the outer covering 105 (e.g., below the outer covering 105), and / or the like, for a user to actively participate in gathering biometric data (e g., by touching the PPG sensor(s) 110). A processor (e.g., of the wearable computing device 102) controls the emitter(s) 110E to emit photons, which reflect off the skin, tissue, bones, blood, etc. of a wearer for detection by detectors 110D, and converts the analog current received from the detector(s) HOD into a digital PPG signal. Signal changes associated with peripheral perfusion, due to contraction of the heart, enable the wearable computing device to measure the wearer’s pulsatility and heart rate, resting heart rate, interbeat interval, heart rate variability, blood pressure, etc. using the PPG signal.

[0041]

[0030] The PPG sensor(s) 110 can be configured for use at various light wavelengths, such as green (centered at 528 nanometers (nm)), red (centered at 660 nm), and infrared (centered at 940 nm), where the amplitude of the reflected light for the green, red, and infrared wavelengths changes with every heartbeat. Typically, the peak to peak amplitude for green PPG signals is greater than the peak to peak amplitude for red PPG signals and infrared PPG signals when there is a clear pulsatile signal such as that associated with a heartbeat. In some cases, a PPG sensor 110 may employ a single light source 110E and two or more light detectors 110D each configured to detect a specific wavelength or wavelength range. In some cases, each detector 110D is configured to detect a different wavelength or wavelength range from the other detectors 110D. In other cases, two or more detectors HOD are configured to detect the same wavelength or wavelength range. In yet another case, one or more detectors 110D is configured to detect a specific wavelength or wavelength range different from one or more other detectors 1 10D). In embodiments employing multiple light paths, the PPG sensor(s) 1 10 may determine an average of the signals resulting from the multiple light paths before determining an HR estimate or other physiological metrics. In any event, the PPG sensor(s) 110 is usable to generate non-invasive biometric data related to resting heart rate, heart rate variability, interbeat interval, blood pressure, etc.

[0042]

[0031] In accordance with aspects of the present subject matter, the PPG sensor(s) 1 10 may be used to determine a user’s blood pressure. For instance, a user may contact (e.g., their finger, arm, temple, etc. proximate an artery) the wearable computing device 102 proximate (e.g., at) the PPG sensor(s) 110 and press with increasing pressure while the data from the PPG sensor(s) 110 is monitored. The PPG data generated by the PPG sensor(s) 110 may indicate when blood flow through the artery of the user proximate the PPG sensor(s) 110 has stopped, restarted, and / or fully resumed, where the pressures at the PPG sensor(s) 110 corresponding with the blood flow through the artery stopping, restarting, and / or fully resuming is indicative of the user’s blood pressure. As such, the pressure applied at the PPG sensor(s) 1 10 may be measured or otherwise detected. It should be appreciated that instead of, or in addition to the PPG sensor(s) 110, another type of optical biometric sensor may be used, such as an ultrasonic sensor.

[0043]

[0032] Thus, in some instances, the wearable computing device 102 further includes one or more pressure sensors 112 configured to generate data indicative of pressure applied at one or more of the PPG sensor(s) 110. The pressure sensor(s) 112 is generally positioned proximate the PPG sensor(s) 110 for generating pressure data indicative of the pressure or force applied at the PPG sensor(s). The pressure sensor(s) 112 may be configured as any suitable pressure sensors capable of measuring changes in applied pressure at the one or more PPG devices 110, such as a piezoelectric sensor(s), a piezoresistive sensor(s), a strain gauge(s), a capacitive sensor(s), optical pressure sensor(s), and / or the like. In some embodiments, the pressure sensor(s) 112 is positioned directly adjacent to (e.g.. above, below, to the side of, and / or the like) the PPG sensor(s) 110. For instance, as shown in FIG. 3, the PPG sensor 110 is at least partially surrounded by the pressure sensors 112. More particularly, in some embodiments, the PPG sensor 110 is positioned between at least one pair of pressure sensors 112. In some instances, the PPG sensor 110 is positioned between at least two pairs of pressure sensors 112. In one instance, the pressure sensors 112 on opposite sides of a PPG sensor 110 are spaced apart by a greater distance than a distance between the pressure sensors 112 on a common side of the PPG sensor 110. However, in some instances, the pressure sensors 112 are evenly spaced apart from each other to form a grid or array at a common distance from the contact surface (e.g., upper surface of the device), where the PPG sensor(s) 110 are spaced between the pressure sensors 112. It should be appreciated that any suitable number of PPG sensor(s) 110 and / or any suitable number of pressure sensor(s) 112 may be used.

[0044]

[0033] In some instances, the PPG sensor(s) 110 and the pressure sensor(s) 112 are supported by a common support 113, such as a mounting board or circuit board, within the computing device with a pressure transfer surface 113S positioned over the PPG sensor(s) 110 and the pressure sensor(s) 112. such that when a user presses the pressure transfer surface 113S, the pressure is transmitted by the pressure transfer surface 113S onto the PPG sensor(s) 110 and the pressure sensor(s) 112, such that the pressure sensor(s) 112 may determine the pressure applied at the PPG sensor(s) 110. In some instances, the pressure transfer surface 113S may be configured to apply the pressure from the user to the PPG sensor(s) 110 and the pressure sensor(s) 112 while maintaining variation similar to a user’s varying stiffness (e.g.. at the user’s fingers, arms, temples, ears. etc.). For instance, in one embodiment, the pressure transfer surface 113S may be formed from an elastomer with similar stiffness as a user’s skin (e.g., average for users fingers, arms, temples, ears, etc.), such as an elastomer with a Shore Hardness value of 00-30 (e.g., Ecoflex™). However, in one or more instances, the pressure transfer surface 113S may be configured to evenly apply the pressure from the user equally across the PPG sensor(s) 1 10 and the pressure sensor(s) 112. Moreover, the PPG sensor(s) 110 may be configured to emit and detect light through the pressure transfer surface 113S.

[0045]

[0034] The pressure transfer surface 113S may be positioned at the surface of the computing device, such as at the upper surface of the wearable computing device 102, such that the pressure transfer surface 113S forms part of the outer housing of the computing device. For example, the housing 104 of the computing device may include a cutout, opening, or recess, in which the pressure transfer surface 113S is at least partially received or at least through which the pressure transfer surface 113S is contactable by a user, and through which the PPG device(s) 110 may generate data indicative of blood pressure within the user’s arteries. In some instances, the pressure transfer surface 113S is planar and level with the housing 104 of the computing device. However, in some instances, the pressure transfer surface 113S may be contoured to help a user index the proper placement for measuring blood pressure. For instance, the pressure transfer surface 113S may be curved and extend at least partially into the interior volume of the housing 104.

[0046]

[0035] It should be appreciated that, for the wearable computing device 102, the PPG sensor(s) 110 may be on the upper side or perimeter of the computing device 102 for measuring the blood flow within the user’s finger 107, or may be on the lower side for measuring blood flow within the user’s wrist, where the pressure sensor(s) 112 may be correspondingly positioned depending on where blood flow is monitored.

[0047]

[0036] The other computing devices may similarly include one or more PPG sensor(s) 110 and associated pressure sensor(s) 112. For example, a wearable device, such as the ring 130 may similarly include PPG sensor(s) 110 on an upper or outer side to measure blood pressure at a location aside from the finger 107 wearing the ring 130 and / or on a lower or inner, user facing side to measure blood pressure at the finger wearing the ring. The pressure sensor(s) 112 of the ring 130 may be positioned along the inner and / or outer side of the ring 130, while being proximate the PPG sensor(s) 110 (e.g., proximate the same circumferential location) to measure the pressure applied at the PPG sensor(s) 110. Moreover, one or more of the earbuds 140 may have PPG sensor(s) 110 facing a user's ear canal when worn and / or facing where a user may contact with a finger on earbud 140 when worn, where the pressure sensor(s) 112 of the earbud(s) 140 may be suitably positioned proximate the PPG sensor(s)

[0048] 110 to measure the pressure applied at the PPG sensor(s) 110. The mobile computing device 120 may similarly include PPG sensor(s) 110 and pressure sensor(s) 112 positioned within the housing 104 of the mobile computing device 120 below a screen 106 such that the user contacts the screen 106 for taking blood pressure measurements with the PPG sensor(s) 110 and pressure sensor(s) 112. However, in one or more instances, the PPG sensor(s) 110 and pressure sensor(s) 112 are positioned within the housing 104 of the mobile computing device 120 and positioned proximate another surface of the housing 104, such as a rear surface and / or a side of the housing 104, such that the user contacts the rear surface and / or the side of the housing 104 for taking blood pressure measurements with the PPG sensor(s) 110 and pressure sensor(s) 112. A tablet device (e.g., tablet 150), a laptop, a standalone blood pressure monitoring device, and / or the like may have a similar sensor arrangement of PPG sensor(s) 110 and pressure sensor(s) 112 for taking blood pressure.

[0049]

[0037] In the example shown in FIG. 2, the user contacts a surface of the computing device 102, 120, 130, 140, 150 with their finger 107 proximate the PPG sensor(s) 110 proximate. The PPG sensor(s) 110 generates data indicative of blood flow through an artery of the user proximate the PPG sensor(s) 110, while the pressure sensor(s) 112 generates data indicative of the pressure applied at the PPG sensor(s) 110. A user may increasingly apply pressure, as discussed above, where a first pressure determined from the pressure sensor(s) 112 is associated with when blood flow through the artery is determined to stop based on the PPG data and is correlated with the systolic blood pressure, and where a second pressure determined from the pressure sensor(s) 112 is associated with the maximum in the PPG data and is correlated with the mean arterial pressure, where the first pressure associated with the systolic pressure is higher than the second pressure associated with the mean arterial pressure. The diastolic pressure may be calculated based on the systolic pressure and mean arterial pressure (e.g., based at least in part on the first and second pressures).

[0050]

[0038] However, as discussed above, a user’s applied force or pressure at the PPG sensor(s)

[0051] 110 is variable and inconsistent between subsequent blood pressure measurements, which can result in different blood pressure readings. Moreover, it may be difficult for some users to apply sufficient force or a suitable gradient in force for the blood pressure measurement. Thus, in accordance with aspects of the present subject matter, one or more of the computing devices of the disclosed system 100 may further include one or more haptic devices 114 configured to generate vibrations. The haptic devices 114 may be existing haptic devices within computing devices (e g., within wearable computing device 102, mobile phone device 120, ring 130, earbud(s) 140, tablet 150. etc.) for generating vibrations as feedback to users (e.g., in response to interactions such as taps, clicks, and / or the like) and / or notifications to users (e.g., notifications of calls, messages, alarms, and / or the like, etc.). The haptic devices 114 may be used to generate vibrations at vary ing, known frequencies while the computing device with the haptic device 114 is held proximate (e.g., against) the user to vary the pressure applied via the user at or on the optical sensor(s) as the user contacts a computing device having the optical sensor(s), the optical sensor(s) being used for taking biometric data indicative of blood pressure (e.g., the PPG sensor(s) 110). In general, higher vibration frequencies cause increased deflection of the user at the PPG sensor(s) 110, and thus, increased pressure applied via the user at the PPG sensor(s) 1 10. As an example, the haptic device(s) 114 may be tuned to displace the user's skin (e.g., of their finger, leg, etc.) up to several millimeters, such as by at least one to two millimeters.

[0052]

[0039] For instance, if a user touches their finger 107 on the upper surface of the wearable device 102 with substantially constant contact (e.g., with essentially constant pressure), the haptic device(s) 114 of the wearable device 102 may be controlled to vibrate with varying frequency to change the force applied via the user on the wearable device 102. For example, in some instances, the haptic device(s) 114 are controlled according to a predetermined vibration pattern, such as to increase vibration frequency from zero to a certain vibration frequency over a certain period of time and / or at a particular rate. However, in some instances, the haptic device(s) 114 is additionally, or alternatively, controlled to increase by a particular pattern or rate until the data from the PPG sensor(s) 110 of the wearable device 102 is indicative of a certain blood flow, such as the blood flow at the PPG sensor(s) 110 stopping or significantly decreasing (e g., indicative of the systolic pressure).

[0053]

[0040] It should be appreciated that, in some instances, the same computing device is used to generate the biometric data and generate the vibrations at vary ing frequencies. In such instances, the haptic device(s) 114 may be supported with the biometric sensor(s) (e.g., PPG sensor(s) 1 10) and / or the pressure sensor(s) 1 12 within the same mobile computing device, such as on the common support. Additionally, or alternatively, in such instances, the haptic device(s) 114 may be supported separately of the biometric sensor(s) (e.g., PPG sensor(s) 110) and / or the pressure sensor(s) 112 within the same mobile computing device. However, in some instances, one computing device may be used to generate the biometric data indicative of the blood flow (e.g., with the PPG sensor(s) 110), while the haptic device(s) 114 of one or more other computing devices may be used to generate the varying pressure. For instance, if a user places their finger 107 on the upper surface of the wearable device 102 or at the PPG sensor(s) 110 on the mobile phone 120, the haptic device(s) 114 of the ring 130 may be used to vibrate the user’s finger 107 to vary the pressure applied via the user’s finger 107 at the measuring computing device 102, 120. Similarly, if a user places their finger 107 at the PPG sensor(s) 110 on the mobile phone 120, haptic device(s) 114 of the wearable computing device 102 may be used to vibrate the user’s finger 107 to vary the pressure applied via the user’s finger 107 at the mobile phone 120. It should be appreciated that any suitable combination of devices may be used.

[0054]

[0041] In some instances, the haptic devices 114 of multiple devices may be used together to vary the pressure applied via the user at a measuring computing device. For instance, if the user places their finger 107 at the PPG sensor(s) 110 on the mobile phone 120, the haptic device(s) 114 of the wearable watch computing device 102 and the haptic device(s) 114 of the ring computing device 130 may be used together to vary the pressure applied via the user’s finger 107 at the mobile phone 120. In some instances, the haptic devices 114 of one or more devices may be used together with the haptic device(s) 114 of the measuring computing device to vary the pressure applied via the user at the measuring computing device. For example, if the user places their finger 107 at the PPG sensor(s) 110 on the mobile phone 120. the haptic device(s) 114 of the wearable watch computing device 102 and / or the haptic device(s) 114 of the ring computing device 130 may be used together with the haptic device(s) 114 of the mobile phone 120 to vary the pressure applied via the user’s finger 107 at the mobile phone 120. By using the haptic device(s) 114 of multiple devices, the vibration frequency range for applying pressure may be varied. For instance, given the relative size of the devices, the haptic device(s) 114 of the ring 130 and / or earbuds 140 may only be capable of a small frequency or force range, while the haptic device(s) 114 of the wearable computing device 102 may be capable of a larger frequency or force range, and the haptic device(s) 114 of the mobile computing device 120 may be capable of an even larger frequency or force range, and so on. As such, the haptic device(s) 114 of the different computing devices of the system 100 may be used in series to apply varying frequencies of vibrations to the user. In some instances, the haptic device(s) 114 of the different computing devices of the system 100 may be used in parallel, however, communication between the devices may be required to avoid destructive interference.

[0055]

[0042] The known vibration frequencies applied by the haptic device(s) 114 may be accounted for when determining the user’s blood pressure based on the data generated by the biometric sensor (e.g., the PPG sensor(s) 110) and, optionally based at least in part on the data from the pressure sensor(s) 112, to determine the blood pressure reliably and repeatably without a traditional cuff. Additionally, by using haptic feedback and optical sensing devices (e.g., PPG sensor(s) 110) in commonly adopted mobile consumer devices, blood pressure monitoring compliance is improved.

[0056]

[0043] Referring now to FIG. 4, components of an example computing system 200 that can be utilized in accordance with various embodiments are illustrated. In particular, as shown, the computing system 200 may include at least a first mobile computing device, such as one of the computing device(s) 102, 120, 130, 140, 150 of the system 100 as described above. The first mobile computing device may include at least one processor 204 communicatively coupled to different parts of the first mobile computing device, such as the display 106, the optical sensor(s) (e.g., the PPG sensor(s) 110 having the emitter(s) 110E and the detector(s) HOD), pressure sensor(s) 112, optional haptic device(s) 114, any other sensors present (not shown), one or more power components (not shown), and / or the like. The processor(s) 204 may include a central processing unit (CPU) or graphics processing unit (GPU) for executing instructions that can be stored in one or more memory devices 206, such as flash memory or DRAM, among other such options. For example, in an embodiment, the memory device(s) 206 may include RAM, ROM, FLASH memory, or other non-transitory digital data storage, and may include a control program comprising sequences of instructions which, when loaded from the memory device(s) 206 and executed using the processor(s) 204, cause the processor(s) 204 to perform the functions that are described herein. As would be apparent to one of ordinary skill in the art, the first mobile computing device may include many types of memory, data storage, or computer-readable media, such as data storage for program instructions for execution by any suitable processor. The same or separate storage can be used for images or data, a removable memory can be available for sharing information with other devices, and any number of communication approaches can be available for sharing with other devices.

[0057]

[0044] The first mobile computing device may also include a communications interface 208, such as one or more wireless components, operable to allow the first mobile computing device to communicate with one or more other electronic devices of the system 200 within a communication range of the particular wireless channel. The wireless channel can be any appropriate channel used to enable devices to communicate wirelessly, such as Bluetooth, cellular, NFC, Ultra-Wideband (UWB), or Wi-Fi channels. It should be understood that the first mobile computing device can have one or more conventional wired communications connections as known in the art.

[0058]

[0045] The first mobile computing device may be configured to receive inputs from the display 106 (e.g., when the display 106 is a touch screen) and / or to control the display 106 to convey information, although devices might convey information via other means, such as through audio speakers, projectors, or casting the display or streaming data to another device, such as a mobile phone, wherein an application on the mobile phone displays the data. In further embodiments, the first mobile computing device can also include at least one additional input-output (I / O) component able to receive conventional input from a user. This conventional input can include, for example, a push button, touch pad, touch screen, wheel, joystick, keyboard, mouse, keypad, or any other such device or element whereby a user can input a command to the first mobile computing device. In another embodiment, the I / O component(s) may be connected by a wireless infrared or Bluetooth or other link as well in some embodiments. In some embodiments, the first mobile computing device may also include a microphone or other audio capture element that accepts voice or other audio commands. For example, in particular embodiments, the first mobile computing device may not include any buttons at all, but might be controlled only through a combination of visual and audio commands, such that a user can control the first mobile computing device without having to be in contact therewith.

[0059]

[0046] It should be appreciated that, the emitters 110E and detectors 110D of the PPG sensor(s) 1 10 may be coupled to the processor 204 directly or indirectly using driver circuitry by which the processor 204 may control the emitters 110E to emit light and obtain signals from the detectors HOD.

[0060]

[0047] In some instances, the computing system 200 further includes one or more second mobile computing devices, such as one or more of the computing device(s) 102, 120, 130. 140, 150 of the system 100 as described above. In some instances, the second mobile computing device(s) may similarly have one or more processors 204, one or more memory' devices 206, and one or more communications interfaces 208, where the processor(s) 204 of the second mobile computing device is communicatively coupled to different parts of the respective, second mobile computing device, such as the display 106 (if present), the optional, optical sensor(s) (e.g., the PPG sensor(s) 110 having the emitter(s) 110E and the detector(s) HOD), pressure sensor(s) 112 (if present), haptic device(s) 114, any other sensors present (not shown), one or more power components (not shown), and / or the like.

[0061]

[0048] Additionally, the computing system 200 may include a server computing system 202. The server computing system 202 may similarly have one or more processors 204, one or more memory7devices 206, and one or more communications interfaces 208, where the server computing system 202 can communicate with its communications interface(s) 208 via one or more networks 210, which may include one or more local area networks, wide area networks, UWB, and / or internetworks using any of terrestrial or satellite links. In some embodiments, the server computing system 202 executes control programs and / or application programs that are configured to perform some of the functions described herein. Moreover, the network(s) 210 may allow one or more other devices(s) to communicate with the first mobile computing device, the second mobile computing device(s), and / or one or more external data source(s) 212 (e.g.. for providing additional user data, and / or the like).

[0062]

[0049] For instance, referring now to FIG. 5, a schematic diagram of an environment in which aspects of various embodiments can be implemented is illustrated. In particular, as shown, a user might have a number of different devices that are able to communicate using at least one wireless communication protocol. For example, as shown, the user might have the wearable computing device 102. such as a smartwatch or fitness tracker, which the user would like to be able to communicate with another device, such as the smartphone 120, the smart ring 130, earbuds 140, the tablet computer 150, one or more external data sources 212 (e.g., a thermometer for measuring core body temperature, a scale for measuring weight, a health records system, etc.), and / or the like. The ability to communicate with multiple devices can enable a user to view and share information across the devices, such as from the smartwatch 102, e.g., data captured using a sensor on the smartwatch 102, and any other linked source (e.g., external data source 212) using an application installed on the smartwatch 102, the smartphone 120, the tablet computer 150, and / or the like. The user may also want the data generating computing devices 102, 120, 130, 140, 150 to be able to communicate with the server computing system 202 of the service provider, or other such entity, which is able to obtain and process data from the smartw atch 102 and / or any other suitable device or source (e.g., the mobile phone 120, the ring 130, the earbuds 140, the tablet 150, the external data source(s) 212) to provide functionality that may not otherwise be available on a single device (e.g., the smartwatch 102 or the applications installed on the individual devices). In addition, as showar, the data generating computing devices 102, 120, 130, 140, 150 and the external data source 212 may be able to communicate with the server computing system 202 of the service provider through the at least one network 210, such as the Internet or a cellular network, or may communicate over a wireless connection such as Bluetooth® to one of the individual devices, which can then communicate over the at least one network.

[0063]

[0050] There may be a number of other types of, or reasons for, communications in various embodiments. For instance, a user or wearer may w ant to allow' the system 200 to access health data from an external health records system (e.g., for a health provider). For instance, the health data can include pre-existing health data of the user or wearer in the form of electronic health records that can include biomarker data, age, pre-existing health conditions, etc. Biomarker data could have been previously collected in an invasive or non-invasive manner and can include biomarkers from blood testing, and this data can be related to a complete blood count, a comprehensive metabolic panel, an insulin level, a blood glucose level, a total cholesterol level, an HDL cholesterol level, an LDL cholesterol level, a triglyceride level, an HbAlc level, a high-sensitivity C-reactive protein level, a gammaglutamyl transferase level, a testosterone level, a blood urea nitrogen level, a creatinine level, an Estimated Glomerular Filtration Rate (eGFR), a sodium level, a potassium level, a chloride level, a carbon dioxide level, a calcium level, a total protein level, an albumin level, a globulin level, an albumin / globulin ratio, a total bilirubin level, an alkaline phosphatase (ALP) level, an aspartate aminotransferase (AST) level, an alanine aminotransferase (ALT) level, or a combination thereof.

[0064]

[0051] In addition to being able to communicate, a user or wearer may also want the devices to be able to communicate in a number of ways or with certain aspects. For example, the user or wearer may want communications between the devices to be secure, particularly where the data may include personal health data or other such communications. The device or application providers may also be required to secure this information in at least some situations. The user may want the devices to be able to communicate with each other concurrently, rather than sequentially. This may be particularly true where pairing may be required, as the user may prefer that each device be paired at most once, such that no manual pairing is required. The user may also desire the communications to be as standards-based as possible, not only so that little manual intervention is required on the part of the user but also so that the devices can communicate with as many other types of devices as possible, which is often not the case for various proprietary formats. A user may thus desire to be able to walk in a room with one device and have such device automatically communicate with another target device with little to no effort on the part of the user. In various conventional approaches, a device will utilize a communication technology' such as Wi-Fi to communicate with other devices using wireless local area networking (WLAN). Smaller or lower capacitydevices, such as many Internet of Things (loT) devices, instead utilize a communication technology such as Bluetooth®, and in particular Bluetooth Low Energy (BLE) which has very low power consumption.

[0065]

[0052] In further embodiments, the environment illustrated in FIG. 5 enables data to be captured, processed, and displayed in a number of different ways. For example, data may be captured using sensors on the smartwatch 102, but due to limited resources on the smartwatch 102, the data may be transferred to the smartphone 120 or the server computing system 202 of the service provider (or a cloud resource) for processing, and results of that processing may then be presented back to that user on the smartwatch 102, smartphone 120, and / or another such device associated with that user, such as the tablet computer 150. In at least some embodiments, a user may also be able to provide input such as health data from an external data source using an interface on any of these devices, which can then be considered when making that determination.

[0066]

[0053] Referring back to FIG. 4, the data collected from the PPG sensor(s) 110 and the pressure sensor(s) 112 of the first mobile computing device(s) can be utilized in order to detect a user's blood pressure. More particularly, data generated by the PPG sensor(s) 110 and the pressure sensor(s) 112 of the first mobile computing device(s) positioned at a peripheral location (e.g.. wrist, leg, finger, temple, ear, etc.) may be monitored while haptic device(s) 114 of the first mobile computing device(s) and / or of the second mobile computing device(s) are used to apply varying frequencies of vibrations to the user.

[0067]

[0054] For instance, referring now to FIGS. 6A-6C. graphs evaluating PPG sensor data and pressure sensor data during a blood pressure monitoring event with the disclosed system 200 are illustrated according to example embodiments of the present disclosure. For instance, the graph 300 in FIG. 6A illustrates the amplitude 302 or “maximum envelope” of the PPG data over time (measured in seconds) during a blood pressure monitoring event, the graph 304 in FIG. 6B illustrates the pressure 306, 308, 310. 312 measured (e.g., in millimeters of mercury [mmHg]) by four, respective pressure sensors 112 (e.g.. the four pressure sensors 1 12 from FIG. 3) with respect to time (measured in seconds) during the blood pressure monitoring event, and the graph 314 in FIG. 6C plots the amplitude 316, 318, 320, 322 of the PPG data from FIG. 6A with respect to the different pressures 306, 308, 310, 312 from FIG. 6B during the blood pressure monitoring event.

[0068]

[0055] Generally, the pressure 306, 308, 310, 312 applied via a user at the PPG sensor(s) 110 is steadily increased during the blood pressure monitoring event, as seen in FIG. 6B. As described above, a user contacts a mobile computing device proximate PPG sensor(s) 110, the pressure applied via the user at the PPG sensor(s) 110 is increased by applying vibrations of increasing frequency to the user via haptic device(s) 114, with greater frequencies of vibrations being associated with greater displacement of the user, and thus, greater pressure applied via the user at the PPG sensor(s) 110. As such, it should be appreciated that the range of pressure shown in FIGS. 6B and 6C correspond to vibration frequency ranges.

[0069]

[0056] During the blood pressure monitoring event, the amplitude 302 of the PPG data in FIG. 6A generally increases to a maximum amplitude MX1 until the artery at the PPG sensor(s) 110 begins to close at time tl, where the amplitude 302 of the PPG data subsequently begins to decrease from the maximum amplitude MX1 with increasing applied pressure. At point in time t2 (after time tl), the amplitude 302 of the PPG data in FIG. 6A is almost equal to the starting amplitude and the PPG data ceases to be collected. The first pressures Pl, P2, P3, P4 associated with point in time tl and the second pressures P5, P6, P7, P8 associated with point in time t2 in FIG. 6B may be analyzed to determine the mean arterial pressure and the systolic pressure, respectively. For instance, the positioning of the pressure sensors 112 relative to the PPG sensor(s) 110 in the sensor array and / or the measured pressures may be used to determine a pressure distribution, where the pressure distribution may be used as an input in one or more models with the pressure values at points in time tl, t2 for calculating mean arterial pressure and the systolic pressure. For example, based at least in part on the first pressures Pl, P2, P3, P4 associated with the point in time tl, the mean arterial pressure of the user is determined to be 92 mmHg. Similarly, based at least in part on the second pressures P5, P6, P7, P8 in FIG. 6B associated with the point in time t2, the systolic blood pressure of the user is determined to be 110 mmHg. Similarly in FIG. 6C, the amplitude 316, 318, 320, 322 of the PPG data is plotted against the pressure applied via a user at the PPG sensor(s) 110 and detected by the pressure sensor(s) 112. Based at least in part on the pressures Pl, P2, P3, P4 in FIG. 6C sensed at the maximum amplitude MX1 of the PPG amplitude, the mean arterial pressure is again determined to be 92 mmHg. Based at least in part on the pressures P5, P6. P7. P8 in FIG. 6C sensed at the end El of the PPG amplitude readings, the systolic pressure is again determined to be 110 mmHg. Generally, the higher the user’s blood pressure, the higher the pressure sensor readings will be for both mean arterial and systolic blood pressure measurements.

[0070]

[0057] Once the mean arterial pressure and systolic blood pressure measurements are determined, the diastolic blood pressure may be determined. For instance, the formula for determining diastolic blood pressure based on mean arterial pressure and systolic blood pressure measurements is as follows: where diastolic blood pressure is DBP, mean arterial pressure is MAP, and systolic blood pressure is SBP. In the example provided in FIGS. 6A-6C, the diastolic pressure is calculated as 83 mmHg.

[0071]

[0058] As such, by using a combination of PPG data from PPG sensor(s) 110 and pressure data from pressure sensor(s) 112 while applying varying pressure via haptic device(s) 114. as described herein, blood pressure of the user may be detected without the use of a blood pressure cuff, which can increase compliance with measurement frequency and improve accuracy of measurements without extensive training. Moreover, the blood pressure measurements taken with varying pressure applied by haptic device(s) 114 as described herein can be repeated quickly. For example, a cycle of the haptic device may increase the generated vibrations, and thus, the applied pressure to detect the mean arterial and systolic pressures, over a span of two seconds to five seconds. As such, the haptic device(s) 114 may be controlled, for example, to perform a first cycle where vibrations are generated at increasing frequencies (e.g., according to one or more predetermined intervals and / or rates), then controlled to repeat the cycle one or more additional times. The blood pressure measurements and calculations across multiple iterations of the cycle may be averaged to reduce errors in measurements and increase the accuracy of the blood pressure estimation, which is vital for clinical certification. For instance, the computing system 200 may be configured to determine the blood pressure of the user based at least in part on the first frequency associated with the systolic blood pressure and the second frequency associated with the mean arterial pressure for each iteration of the cycle, where the first frequency is higher than the second frequency. Additionally, because the frequency and pattern of the haptic vibrations throughout the blood pressure measurement event is precisely controlled, the received signals from the pressure sensors 112 may be demodulated according to the controlled haptic vibrations, which can improve motion artifact rejection and thus, further improve the accuracy of the blood pressure measurement.

[0072]

[0059] In one or more instances, the blood pressure measurements may be established based on the frequencies of the vibrations and the PPG data from the PPG sensor(s) 110 without the additional pressure data from the pressure sensor(s) 112. For instance, the displacement associated with each vibration frequency may be correlated to a particular applied pressure. However, the accuracy of the blood pressure measurements may be better with the use of the pressure data from the pressure sensor(s) 112.

[0073]

[0060] In some instances, the data from the PPG sensor(s) 110 and the pressure sensor(s) 112 may be used together or with further data when determining blood pressure to improve the accuracy of the blood pressure measurement. For instance, the data from the PPG sensor(s) 110 and the pressure sensor(s) 112 may be used with impedance data, motion data, temperature data, and / or the like to determine further indicators of health conditions. For example, if a user has just performed an exercise, their blood pressure is likely to be higher than if they were sedentary. Similarly, if a user is determined to be sitting up, their blood pressure is likely to be higher than if they were laying down. As another example, if a user is stressed (has a higher impedance reading), the user likely has a higher blood pressure than if they were not experiencing stress. Moreover, vasoconstriction may occur when a user is exposed to a cold environment and vasodilation may occur when a user is exposed to a warm environment, among other things, which may affect the blood pressure measurement. Thus, data from an environment and / or skin temperature sensor (e.g., temperature sensor of the wearable computing device 102) may be used to determine whether a user is exposed to a change in environmental temperature that may be affecting the blood pressure measurement. For instance, if a change in the skin temperature of the user within a certain time is above a threshold change, it may be determined that environment exposure may affect the accuracy’ of the results. Depending on the degree of severity’ of the change in skin temperature relative to the change in environment temperature, certain conditions, like Raynaud’s, may be present, which may require multiple blood pressure readings (e.g., at multiple fingers) to provide a more accurate blood pressure measurement.

[0074]

[0061] The blood pressure measurement described herein may be initiated upon one of the computing devices of the system 200 receiving a user input indicative of a request to take a blood pressure measurement. For instance, a user may interact with one or more input devices of the computing devices of the system 200, such as the screen 106 of the wearable computing device 102. the screen 106 of the mobile phone 120. a screen of the tablet 150, and / or the like, with a microphone of one or more of the computing devices of the system 100, a button of one or more of the computing devices of the system 200, and / or the like to request that a blood pressure measurement be taken with the one or more of the computing devices of the system 200. Subsequent to receiving the user input indicative of the request to take the blood pressure measurement, the haptic device(s) 114 may be controlled to generate the vibrations at the varying frequencies and the optical biometric sensors (e.g., PPG sensor(s) 110 and / or ultrasonic sensors) may be controlled to generate the data indicative of blood flow.

[0075]

[0062] In some instances, as described above, the same computing device is used to generate the vibrations at the varying frequencies and to generate the data (e.g., PPG data and / or ultrasonic data) indicative of blood flow. In one or more instances, the same computing device is also used to receive the input from the user indicative of initiating the blood pressure measurement.

[0076]

[0063] In some instances, as described above, one computing device may' be used to generate the data indicative of blood flow while one or more other devices may be used to additionally, or alternatively, generate the vibrations at the vary ing frequencies. In such instances, the computing device(s) used by a user to input the request to take the blood pressure measurement may be used to determine other devices associated with the user, where haptic device(s) 1 14 of the other devices associated with the user may be controllable to provide the varying vibrations and / or generate optical biometric data indicative of blood flow, if necessary. For instance, if a user inputs the request to take a blood pressure measurement at the wearable computing device 102, the wearable computing device 102 may determine if another device associated with the user (e.g., mobile phone 120, ring 130, etc.) is connected or within communication distance of the wearable computing device 102. If one or more other devices are determined to be nearby and / or connected, then the haptic device(s) 114 of the other device(s) associated with the user may be controlled (e.g., directly or indirectly) to generate vibrations at varying frequencies and / or the optical sensor(s) of the other device(s) associated with the user may be controlled to generate data. For example, the wearable computing device 102 may receive the input from the user indicative of initiating a blood pressure measurement, then determine that the ring 130 is in communication with the wearable computing device 102, the wearable computing device 102 may then be used to generate the biometric data indicative of blood flow while the haptic device(s) 114 of another computing device (e.g., ring 130) are controlled to generate the vibrations for varying the pressure applied via the user at the wearable computing device 102. In some instances, sensors associated with the other device may be used to determine if the other device is being held against the user before the haptic device(s) 114 of the other device associated with the user is controlled to generate vibrations at varying frequencies.

[0077]

[0064] In some instances, subsequent to receiving the input from the user indicative of a request to take a blood pressure measurement, a user interface (e.g., screen, speaker, haptic device, etc.) may be controlled to guide a user through the blood pressure measurement. For instance, the user may be guided to contact the computing device that has the optical biometric sensor (e.g., PPG sensor 110 and / or ultrasonic sensor) to be used to generate the data indicative of blood flow with substantially constant pressure throughout the blood pressure measurement. In some instances, the user may be guided to readjust their placement of contact on the computing device that has the optical biometric sensor (e.g., PPG sensor 110 and / or ultrasonic sensor) such that a clear biometric reading of blood flow can be taken. For instance, if the data from the optical biometric sensor does not clearly indicate a maximum, as described, after one or more blood pressure measurements, the user may need to move where they contact the computing device with the optical biometric sensor. In some instances, the user may be guided to contact the mobile computing device having the biometric sensor with less or greater pressure at the biometric sensor based on the biometric data to improve the clarity of the biometric readings, such as before the varying vibration frequencies are applied to the user.

[0065] Once the blood pressure measurement is determined based at least in part on the PPG data and the pressure data from the sensor(s) 110, 112, the blood pressure may be provided to a user, such as via a notification on the display 106 and / or through another output device on one or more of the computing devices so the wearer can be educated and / or make lifestyle, diet, and / or other changes. For instance, notifications to the user may indicate a given blood pressure measurement, a history of blood pressure measurements, potential indicators of changes in blood pressure (e.g., exercise, fitness level, posture, stress estimation, etc.), recommendations to talk with physician if blood pressure is outside of a range, and / or the like. In some instances, a user may interact with a conversational interface (e.g., chatbot), which may have access to an artificial intelligence (Al) model (e.g., a machine learned, large language model, and / or the like), via one or more user interfaces (e.g., of the wearable computing device 102, mobile phone 120, the tablet 150, a laptop, and / or the like) for a user to ask questions regarding blood pressure measurements and receive feedback from the interface. In instances where an Al model is accessible, the feedback may be more personalized based on the user’s personal metrics depending on user permission settings.

[0078]

[0066] In some instances, a notification may request a user take a new blood pressure measurement. For instance, a user may be reminded to take blood pressure measurements at regular intervals (e.g., daily, weekly, monthly, etc.) at a particular frequency (e.g., once, twice, three times). In some instances, the interval and frequency may be selectable by a user. In one or more instances, a user may be requested to take a new blood pressure measurement if another biometric reading (e.g., heart rate, impedance, etc.) is out of range. As such, the user’s blood pressure measurements may be more useful than random spotchecking by a user.

[0079]

[0067] Referring now to FIG. 7. a flow diagram of one embodiment of a method 400 for determining blood pressure using haptic devices is provided. In general, the method 400 is described herein with reference to the computing system 200 described in FIGS. 1-5 and the graphs of FIGS. 6A-6C. However, it should be appreciated that the disclosed method 400 may be implemented with any other suitable computing system having any other suitable configurations. In addition, although FIG. 7 depicts steps performed in a particular order for purposes of illustration and discussion, the methods discussed herein are not limited to any particular order or arrangement. One skilled in the art, using the disclosures provided herein, will appreciate that various steps of the methods disclosed herein can be omitted, rearranged, combined, added, and / or adapted in various ways without deviating from the scope of the present disclosure.

[0068] At step (402), the method 400 may include controlling a haptic device to generate vibrations at varying frequencies while the haptic device is held proximate to a user. For instance, as discussed above, a haptic device 114 may be controlled by a computing system (e.g., computing system 200) to generate vibrations at varying frequencies while the haptic device 114 is held proximate to a user. For example, the haptic device 114 may be controlled directly by the processor 204 of the computing device having the haptic device 114 or indirectly by a processor 204 of another computing device of the system 200. such as another computing device in communication with the computing device having the haptic device 114, to generate vibrations at varying frequencies.

[0080]

[0069] The method 400 may further include, at step (404), receiving biometric data generated by a biometric sensor of a mobile computing device while the user contacts the mobile computing device proximate to the biometric sensor and the vibrations are applied by the haptic device to the user at the varying frequencies which vary a pressure applied via the user at the biometric sensor. For instance, as described above, biometric data is generated by a biometric sensor (e.g., the PPG sensor(s) 110 and / or ultrasonic sensor(s)) of a mobile computing device (e.g., wearable computing device 102, mobile computing device 120, and / or the like) while the user contacts the mobile computing device proximate the biometric sensor and while the vibrations are applied by the haptic device(s) 114 to the user at the varying frequencies, where each of the varying frequencies is associated with a different pressure applied via the user at the biometric sensor. For example, higher frequencies of vibration are associated with higher pressures applied via the user at the biometric sensor. The biometric data may be received by the computing system 200, such as one or more of the processors 204 of the system 200.

[0081]

[0070] Additionally, the method 400 may further include, at step (406), determining a blood pressure of the user based at least in part on the biometric data and the varying frequencies. For instance, as described above, a blood pressure of the user may be determined by the computing system 200 (e.g., by one or more of the processor(s) 204) based at least in part on the biometric data and the varying frequencies. For example, the vibration frequency associated with the maximum value in the biometric data (e.g., maximum amplitude MX1 in FIG. A) may be associated with the mean arterial pressure, while the vibration frequency associated with the end of the biometric data (e.g., at time t2 in FIG. 6A) may be associated with the systolic blood pressure measurement. In some instances, pressure data generated by the pressure sensor(s) 112 may be used in combination with the biometric data and the varying frequencies to determine the blood pressure measurements. Additional Disclosure

[0082]

[0071] The technology discussed herein makes reference to servers, databases, software applications, and other computer-based systems, as well as actions taken and information sent to and from such systems. The inherent flexibility of computer-based systems allows for a wide variety of possible configurations, combinations, and divisions of tasks and functionality between and among components. For instance, processes discussed herein can be implemented using a single device or component or multiple devices or components working in combination. Databases and applications can be implemented on a single system or distributed across multiple systems. Distributed components can operate sequentially or in parallel.

[0083]

[0072] In addition, although the figures and description depict and describe steps performed in a particular order for purposes of illustration and discussion, the methods discussed herein are not limited to any particular order or arrangement. One skilled in the art, using the disclosures provided herein, will appreciate that various steps of the methods disclosed herein can be omitted, rearranged, combined, added, and / or adapted in various ways without deviating from the scope of the present disclosure.

[0084]

[0073] Further to the descriptions above, a user or w earer may be provided w ith controls allowing the user or wearer to make an election as to both if and when systems, programs, or features described herein may enable collection of user information (e.g.. information about a user’s health data, activities, social network, social actions, profession, a user’s preferences, or a user’s current location, etc.), and if the user is sent content or communications from a server. In addition, certain data may be treated in one or more ways before it is stored or used, so that personally identifiable information is removed. For example, a user’s identity may be treated so that no personally identifiable information can be determined for the user, or a user’s geographic location may be generalized where location information is obtained (such as to a city, ZIP code, or state level), so that a particular location of a user cannot be determined. Thus, the wearer or user may have control over what information is collected about the user, how that information is used, and what information is provided to the user.

[0085]

[0074] While the present subject matter has been described in detail with respect to various specific example embodiments thereof, each example is provided by way of explanation, not limitation of the disclosure. Those skilled in the art, upon attaining an understanding of the foregoing, can readily produce alterations to, variations of, and equivalents to such embodiments. Accordingly, the subject disclosure does not preclude inclusion of such modifications, variations and / or additions to the present subject matter as would be readily apparent to one of ordinary skill in the art. For instance, features illustrated or described as part of one embodiment can be used with another embodiment to yield a still further embodiment. Thus, it is intended that the present disclosure covers such alterations, variations, and equivalents.

Claims

WHAT IS CLAIMED IS:

1. A system for determining blood pressure, the system comprising: a biometric sensor of a mobile computing device configured to generate biometric data indicative of blood flow of a user as the user contacts the mobile computing device proximate the biometric sensor; a haptic device configured to generate vibrations; and a computing system configured to: control the haptic device to generate the vibrations at varying frequencies while the haptic device is held proximate the user to vary pressure applied via the user at the biometric sensor; receive the biometric data generated by the biometric sensor while the vibrations are applied at the varying frequencies; and determine a blood pressure of the user based at least in part on the biometric data and the varying frequencies.

2. The system of claim 1, wherein the computing system is configured to control the haptic device to generate the vibrations at the varying frequencies by controlling the haptic device to perform a cycle where the haptic device is controlled to generate the vibrations at increasing frequencies, wherein the computing system is configured to determine the blood pressure of the user based at least in part on a first frequency of the varying frequencies associated with the biometric data being indicative of the blood flow of the user at the biometric sensor stopping and a second frequency of the varying frequencies associated with a maximum in the biometric data, the first frequency being higher than the second frequency.

3. The system of claim 2, wherein the computing system is configured to control the haptic device to repeat the cycle, wherein the computing system is configured to determine the blood pressure of the user based at least in part on the first frequency and the second frequency for each iteration of the cycle.

4. The system of claim 2. wherein the computing system is configured to control the haptic device to generate the vibrations at the increasing frequencies by controlling the haptic device to generate the vibrations at the increasing frequencies according to one or more predetermined intervals.

5. The system of claim 1, further comprising a pressure sensor configured to generate pressure data indicative of the pressure applied via the user at the biometric sensor,wherein the computing system is further configured to receive the pressure data, wherein the computing system is configured to determine the blood pressure of the user further based at least in part on the pressure data.

6. The system of claim 1 , wherein the mobile computing device further comprises the haptic device.

7. The system of claim 6, wherein the mobile computing device comprises a mobile phone or a wearable computing device.

8. The system of claim 1, further comprising a further mobile computing device, the further mobile computing device comprising the haptic device, the further mobile computing device being separate from the mobile computing device.

9. The system of claim 8, wherein the mobile computing device is a mobile phone and the further mobile computing device is a wearable computing device.

10. The system of claim 1, wherein the biometric sensor is a photoplethysmography (PPG) sensor or an ultrasonic sensor.

11. A mobile computing device, comprising: a biometric sensor configured to generate biometric data indicative of blood flow of a user as the user contacts the mobile computing device proximate the biometric sensor; a haptic device configured to generate vibrations; and a computing system configured to: control the haptic device to generate the vibrations at varying frequencies while the haptic device is proximate the user to vary pressure applied via the user at the biometric sensor; receive the biometric data generated by the biometric sensor while the vibrations are applied at the varying frequencies; and determine a blood pressure of the user based at least in part on the biometric data and the varying frequencies.

12. A method for monitoring blood pressure, the method comprising: controlling, with a computing system, a haptic device to generate vibrations at varying frequencies while the haptic device is held proximate a user; receiving, with the computing system, biometric data generated by a biometric sensor of a mobile computing device while the user contacts the mobile computing device proximate the biometric sensor and the vibrations are applied by the haptic device to the user at the varying frequencies which vary a pressure applied via the user at the biometric sensor; anddetermining, with the computing system, a blood pressure of the user based at least in part on the biometric data and the varying frequencies.

13. The method of claim 12, further comprising receiving, with the computing system, a user input indicative of a request to take a blood pressure measurement, wherein controlling the haptic device to generate the vibrations at the varying frequencies comprises controlling the haptic device to generate the vibrations at the varying frequencies subsequent to receiving the user input.

14. The method of claim 12, wherein controlling the haptic device to generate the vibrations at the vary ing frequencies comprises controlling the haptic device to perform a cycle where the haptic device is controlled to generate the vibrations at increasing frequencies, wherein determining the blood pressure of the user comprises determining the blood pressure of the user based at least in part on a first frequency of the varying frequencies associated with the biometric data being indicative of the blood flow of the user at the biometric sensor stopping and a second frequency of the varying frequencies associated with a maximum in the biometric data, the first frequency being higher than the second frequency.

15. The method of claim 14, further comprising controlling the haptic device to repeat the cycle, wherein determining the blood pressure of the user comprises determining the blood pressure of the user based at least in part on the first frequency and the second frequency for each iteration of the cycle.

16. The method of claim 14, wherein controlling the haptic device to generate the vibrations at the increasing frequencies comprises controlling the haptic device to generate the vibrations at the increasing frequencies according to one or more predetermined intervals.

17. The method of claim 12, further comprising receiving, with the computing system, pressure data generated by a pressure sensor and indicative of the pressure applied via the user at the biometric sensor, wherein determining the blood pressure of the user further comprises determining the blood pressure of the user based at least in part on the pressure data.

18. The method of claim 12, further comprising controlling, with the computing system, a user interface to indicate the blood pressure of the user.

19. The method of claim 12, wherein controlling the haptic device comprises controlling the haptic device to generate the vibrations at the varying frequencies while the mobile computing device comprising the haptic device is held against the user.

20. The method of claim 12, wherein controlling the haptic device comprises controlling the haptic device to generate the vibrations at the varying frequencies while a first mobile computing device comprising the haptic device is held against the user, the first mobile computing device being separate from the mobile computing device.

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