A technique for determining blood pressure based on the relative timing of pulse waves.

Abstract

Methods, systems, and devices for determining blood pressure based on the relative timing of pulse waves are described. In some implementations, the system may include one or more wearable devices configured to measure heart rate at different locations on the user's body. Different locations may be different physiological locations (e.g., chest and fingers / wrists) and / or different penetration depths at the same physiological location. The system may use components of the wearable devices to acquire physiological data and observe one or more heart rates of the user over a period of time. The system may compare pulse wave observation times observed at different locations and determine the user's blood pressure index based on the relative timing of heart rate observations at different locations.

Description

Technical Field

[0001] [Cross - Reference] This application claims the benefit of U.S. Non - Provisional Application No. 18 / 189,888, entitled "TECHNIQUES FOR DETERMINING BLOOD PRESSURE BASED ON A RELATIVE TIMING OF PULSES", filed on March 24, 2023, by Rantanen et al., which has been assigned to the assignee of this application and is hereby incorporated by reference in its entirety.

[0002] [Technical Field] The following relates to wearable devices and data processing, including techniques for determining blood pressure based on the relative timing of pulse waves.

Background Art

[0003] Some wearable devices may be configured to collect data related to blood pressure from a user. However, a wearable device may not be able to accurately indicate a user's blood pressure. That is, a wearable device may not be able to accurately perform blood pressure measurements due to signal processing limitations or the lack of appropriate techniques in the wearable device's hardware to enable it to indicate a user's blood pressure. In some aspects, a user may obtain blood pressure measurements in a clinical setting (e.g., a doctor's appointment) using a blood pressure device (e.g., a sphygmomanometer, a blood pressure cuff, a blood pressure monitor). However, the size and shape of a blood pressure device can be inconvenient for daily use, and in some cases, a user may not be able to consistently obtain blood pressure measurements using the blood pressure device. As a result, if blood pressure measurements are rarely taken for a user, the user may not notice specific conditions or diseases associated with high or low blood pressure measurements.

Brief Description of the Drawings

[0004] [[ID=2,6]] [Figure 1]This figure shows an example of a system that supports a technique for determining blood pressure based on the relative timing of pulse waves, according to aspects of this disclosure.

[0005] [Figure 2] This figure shows an example of a system that supports a technique for determining blood pressure based on the relative timing of pulse waves, according to aspects of this disclosure.

[0006] [Figure 3] This figure shows an example of a multi-wearable device system that supports a technique for determining blood pressure based on the relative timing of pulse waves, according to aspects of this disclosure.

[0007] [Figure 4] This figure shows an example of a wearable device system that supports a technique for determining blood pressure based on the relative timing of pulse waves, according to aspects of this disclosure.

[0008] [Figure 5] An example of a timing diagram supporting a technique for determining blood pressure based on the relative timing of pulse waves, as described in this disclosure, is shown.

[0009] [Figure 6] The figure shows an example of a graphical user interface (GUI) that supports a technique for determining blood pressure based on the relative timing of pulse waves, according to aspects of this disclosure.

[0010] [Figure 7] A block diagram of a device supporting a technique for determining blood pressure based on the relative timing of pulse waves, as described in this disclosure, is shown. [Figure 8] A block diagram of a device supporting a technique for determining blood pressure based on the relative timing of pulse waves, as described in this disclosure, is shown.

[0011] [Figure 9] A block diagram of a wearable device manager supporting a technique for determining blood pressure based on the relative timing of pulse waves, as described in this disclosure, is shown.

[0012] [Figure 10] This is a diagram of a system including a device that supports a technique for determining blood pressure based on the relative timing of pulse waves, as depicted in this disclosure. [Modes for carrying out the invention]

[0013] Traditionally, blood pressure could only be measured in a clinical setting, meaning users could only measure their blood pressure a few times a year when visiting their doctor's office. Home blood pressure devices have made it possible for users to measure their blood pressure at home. However, conventional blood pressure devices rely on bulky arm cuffs that are not (or are not) comfortable to wear consistently.

[0014] Some wearable devices have attempted to use light-based measurements to measure blood pressure. However, wearable devices that attempt to use light to acquire the physiological data necessary to determine blood pressure may be unable to perform blood pressure measurements due to limitations in signal processing. In addition, a lack of information about the relationship between blood pressure and photoplethysmography (PPG) waveform characteristics may prevent wearable devices from acquiring blood pressure measurements. Therefore, a system that conveniently measures blood pressure on a consistent basis (e.g., daily, hourly) could be beneficial to the user's overall health.

[0015] Accordingly, aspects of this disclosure relate to systems that utilize one or more wearable devices (e.g., wearable ring devices, watches and bracelets, necklaces, chest-worn wearable devices, headbands or straps, limb monitors) to determine one or more blood pressure indices (e.g., measurements) of a user. In particular, the systems described herein may enable a wearable device consistently worn by the user to determine blood pressure based on the relative timing of the user's pulse wave (e.g., heart rate pulse wave). In some examples, blood pressure changes and can propagate pulse waves at different speeds to different parts of the body. For example, higher blood pressure may propagate heartbeats at a faster speed throughout the body, and lower blood pressure may propagate heartbeats at a slower speed throughout the body. Accordingly, a system may use one or more wearable devices positioned at relative locations on the user to measure heart rate at different locations to determine the pulse wave conduction time associated with the heart rate pulse wave, and to determine the user's blood pressure index based on the pulse wave conduction time. In other words, an aspect of this disclosure is that a user's blood pressure can be determined by evaluating how quickly (or slowly) the heart rate wave propagates throughout the body.

[0016] In some implementations, the system may use multiple wearable devices positioned at different locations on the body (e.g., chest, fingers, wrists, ankles, etc.) to determine the user's blood pressure index. For example, a first wearable device at the user's first physiological location (e.g., chest) and a second wearable device at the user's second physiological location (e.g., wrists, fingers) may acquire physiological data from the user. The physiological data may represent the first pulse wave observation time of the user's heartbeat at the first physiological location, a second pulse wave observation time of the heartbeat, additional heartbeats of the user, or both. Furthermore, the system may compare the first pulse wave observation time with the second pulse wave observation time to determine the pulse wave time associated with the heartbeat (e.g., the pulse wave time difference). Thus, the system may determine the user's blood pressure index based on the pulse wave time.

[0017] Furthermore, or alternatively, the system may use a single wearable device to determine a user's blood pressure index based on when the pulse wave reaches different layers of tissue. For example, a single wearable device may include one or more light-emitting components (e.g., one or more light-emitting diodes (LEDs)) and a photodetector for receiving light from one or more light-emitting components. The light-emitting components and photodetector may be coupled to a controller to transmit light associated with one or more wavelengths. In addition, the wearable device may use the light received by the photodetector to obtain first physiological data from the user. In some examples, the first physiological data may indicate the first pulse wave observation time of the user's heartbeat at a first tissue penetration depth (e.g., epidermis). The wearable device may also obtain second physiological data from the user, which may indicate a second pulse wave observation time of the heartbeat, an additional heartbeat of the user, or both, at a second tissue penetration depth (e.g., dermis, subcutaneous tissue). In some cases, a wearable device may determine that a pulse wave arrives in one or more capillaries located in the first layer (e.g., the tissue layer closest to the user's skin) faster than a pulse wave in one or more arteries located in the second layer (e.g., a deeper tissue layer further from the user's skin). Therefore, the system may determine pulse wave durations associated with a heartbeat, an additional heartbeat, or both, based on a comparison of the duration of the first pulse wave observation with the duration of the second pulse wave observation. In addition, the system may use pulse wave durations to determine the user's blood pressure index. Thus, the system may use the time it takes for a pulse wave to reach different layers of tissue (e.g., the first, second, and third layers) to determine the user's blood pressure.

[0018] Aspects of this disclosure will first be described in the context of a system that supports the collection of physiological data from users via wearable devices. Aspects of this disclosure will be further illustrated and described with reference to apparatus diagrams, system diagrams, and flowcharts relating to techniques for determining blood pressure based on the relative timing of pulse waves.

[0019] FIG. 1 shows an example of a system 100 that supports a technique for determining blood pressure based on the relative timing of pulse waves, according to an aspect of the present disclosure. System 100 includes a plurality of electronic devices (e.g., wearable device 104, user device 106) that can be worn and / or operated by one or more users 102. System 100 further includes a network 108 and one or more servers 110.

[0020] The electronic devices can include any electronic device known in the art, including wearable device 104 (e.g., ring wearable device, watch wearable device, etc.), user device 106 (e.g., smartphone, laptop, tablet). The electronic device associated with each user 102 can include one or more of the following functions: 1) measuring physiological data, 2) storing the measured data, 3) processing the data, 4) providing an output to the user 102 based on the processed data (e.g., via a GUI), and 5) communicating data with each other and / or with other computing devices. Different electronic devices can perform one or more of the functions.

[0021] Exemplary wearable devices 104 may include wearable computing devices such as a ring-type computing device configured to be worn on the user 102's finger (hereinafter, "ring"), a wrist computing device configured to be worn on the user 102's wrist (e.g., a smartwatch, fitness band, or bracelet), and / or a head-mounted computing device (e.g., glasses / goggles). Wearable devices 104 may also include bands, straps (e.g., flexible or non-flexible bands or straps), adhesive sensors, etc., which may be placed in other locations such as bands around the head (e.g., a forehead headband), arms (e.g., forearm bands and / or bicep bands), and / or legs (e.g., thigh or calf bands), behind the ears, under the armpits, etc. Wearable devices 104 may be attached to or incorporated into clothing. For example, wearable devices 104 may be incorporated into clothing pockets and / or pouches. As another example, the wearable device 104 may be clipped and / or pinned to clothing, or otherwise maintained within the vicinity of the user 102. Examples of clothing include, but are not limited to, hats, shirts, gloves, trousers, socks, outerwear (e.g., jackets), and underwear. In some implementations, the wearable device 104 may be included with other types of devices, such as training / sports devices used during physical activity. For example, the wearable device 104 may be attached to or included with bicycles, skis, tennis rackets, golf clubs, and / or training weights.

[0022] Much of the present disclosure may be described in the context of the ring wearable device 104. Thus, the terms "ring 104", "wearable device 104", and similar terms may be used interchangeably herein unless otherwise described. However, the use of the term "ring 104" should not be considered limiting, and aspects of the present disclosure are contemplated herein to be performed using other wearable devices (e.g., wristwatch-type wearable devices, necklace wearable devices, bracelet wearable devices, earring wearable devices, anklet wearable devices, etc.).

[0023] In some aspects, the user device 106 may include handheld mobile computing devices such as smartphones and tablet computing devices. The user device 106 may also include personal computers such as laptop and desktop computing devices. Other exemplary user devices 106 may include server computing devices that can communicate with other electronic devices (e.g., via the Internet). In some implementations, the computing device may include medical devices such as external wearable computing devices (e.g., Holter monitors). Medical devices may also include implantable medical devices such as pacemakers and defibrillators. Other exemplary user devices 106 may include home computing devices such as Internet of Things (IoT) devices (e.g., IoT devices), smart TVs, smart speakers, smart displays (e.g., video call displays), hubs (e.g., wireless communication hubs), security systems, smart home appliances (e.g., thermostats and refrigerators), and fitness devices.

[0024] Some electronic devices (e.g., wearable device 104, user device 106) may measure the physiological parameters of each user 102, such as photoplethysmography waveforms, continuous skin temperature, pulse wave waveforms, respiratory rate, heart rate, heart rate variability (HRV), actigraphy, electrodermal response, pulse oximetry, blood oxygen saturation (SpO2), blood glucose levels (e.g., glucose index), and / or other physiological parameters. Some electronic devices that measure physiological parameters may also perform some / all of the calculations described herein. Some electronic devices may not measure physiological parameters but may perform some / all of the calculations described herein. For example, a ring (e.g., wearable device 104), a mobile device application, or a server computing device may process the received physiological data measured by other devices.

[0025] In some implementations, user 102 may operate or be associated with multiple electronic devices, some of which may measure physiological parameters, and some of which may process the measured physiological parameters. In some implementations, user 102 may have a ring (e.g., wearable device 104) for measuring physiological parameters. User 102 may also have or be associated with a user device 106 (e.g., a mobile device, smartphone), and the wearable device 104 and user device 106 are coupled to communicate with each other. In some cases, user device 106 may receive data from wearable device 104 and perform some / all of the calculations described herein. In some implementations, user device 106 may also measure physiological parameters described herein, such as motion / activity parameters.

[0026] For example, as shown in Figure 1, a first user 102-a (user 1) may operate or be associated with a wearable device 104-a (e.g., a ring 104-a) and a user device 106-a, which may operate as described herein. In this example, the user device 106-a associated with user 102-a may process / store physiological parameters measured by the ring 104-a. In comparison, a second user 102-b (user 2) may be associated with the ring 104-b, a wristwatch-type wearable device 104-c (e.g., a watch 104-c), and a user device 106-b, and the user device 106-b associated with user 102-b may process / store physiological parameters measured by the ring 104-b and / or the watch 104-c. Furthermore, an nth user 102-n (user N) may be associated with an arrangement of electronic devices (e.g., a ring 104-n, user device 106-n) as described herein. In some respects, wearable devices 104 (e.g., ring 104, watch 104) and other electronic devices can be communicably coupled to the user devices 106 of each user 102 via Bluetooth®, Wi-Fi, and other radio protocols.

[0027] In some implementations, the ring 104 of system 100 (e.g., wearable device 104) may be configured to collect physiological data from each user 102 based on arterial blood flow in the user's finger. In particular, the ring 104 may collect physiological data based on arterial blood flow in the user's finger by utilizing one or more light-emitting elements, such as LEDs (e.g., red LEDs, green LEDs), that emit light on the palm side of the user's finger. Generally, the terms light-emitting elements, light-emitting elements, and similar terms may include, but are not limited to, LEDs, micro-LEDs, mini-LEDs, laser diodes (LDs) (e.g., vertical-cavity surface-emitting lasers (VCSELs)), etc.

[0028] In some cases, system 100 may be configured to collect physiological data from each user 102 based on blood flow diffused into the microvascular bed of the skin having capillaries and arterioles. For example, system 100 may collect PPG data based on the measured amount of blood diffused into the microvascular system of capillaries and arterioles. In some implementations, ring 104 may acquire physiological data using a combination of both green and red LEDs. Physiological data may include, but are not limited to, temperature data, accelerometer data (e.g., motion data), heart rate data, HRV data, blood oxygen saturation data, or any combination thereof, any physiological data known in the art.

[0029] Red and green LEDs have been shown to have distinct advantages of their own, such as when acquiring physiological data through different parts of the body under different conditions (e.g., light / dark, active / inactive), so the use of both green and red LEDs may offer several advantages over other solutions. For example, green LEDs have been shown to perform better during exercise. Furthermore, using multiple LEDs (e.g., green and red LEDs) dispersed around the ring 104 has been shown to perform better than wearable devices that utilize LEDs placed close together, such as in a wristwatch-type wearable device. In addition, the blood vessels in the fingers (e.g., arteries, capillaries) are more accessible via LEDs than the blood vessels in the wrist. In particular, the arteries in the wrist are located at the bottom of the wrist (e.g., the palm side of the wrist), which means that only capillaries are accessible at the top of the wrist (e.g., the back of the wrist), where wearable watch devices and similar devices are typically worn. Therefore, it has been found that utilizing LEDs and other sensors within the ring 104 results in superior performance compared to wearable devices worn on the wrist, as the ring 104 has greater access to arteries (compared to capillaries), thereby potentially yielding stronger signals and more valuable physiological data.

[0030] Electronic devices of system 100 (e.g., user device 106, wearable device 104) can be communicatively coupled to one or more servers 110 via wired or wireless communication protocols. For example, as shown in Figure 1, an electronic device (e.g., user device 106) can be communicatively coupled to one or more servers 110 via network 108. Network 108 may implement a transport control protocol such as the Internet and the Internet Protocol (TCP / IP), or it may implement other network 108 protocols. Network connections between network 108 and each electronic device can facilitate the transport of data via email, the web, text messages, postal mail, or any other suitable form of interaction within the computer network 108. For example, in some implementations, a first user 102-a associated with ring 104-a may be communicatively coupled to user device 106-a, and user device 106-a is communicatively coupled to server 110 via network 108. In additional or alternative cases, the wearable device 104 (e.g., ring 104, watch 104) may be coupled to the network 108 in a way that allows it to communicate directly with the network.

[0031] System 100 may provide an on-demand database service between a user device 106 and one or more servers 110. In some cases, the server 110 may receive data from the user device 106 via a network 108, and may store and analyze the data. Similarly, the server 110 may provide data to the user device 106 via the network 108. In some cases, the server 110 may be located in one or more data centers. The server 110 may be used for data storage, management, and processing. In some implementations, the server 110 may provide a web-based interface to the user device 106 via a web browser.

[0032] In some aspects, system 100 may detect periods when user 102 is asleep and classify those periods into one or more sleep stages (e.g., sleep stage classifications). For example, as shown in Figure 1, user 102-a may be associated with a wearable device 104-a (e.g., ring 104-a) and a user device 106-a. In this example, ring 104-a may collect physiological data associated with user 102-a, including body temperature, heart rate, HRV, respiratory rate, etc. In some aspects, the data collected by ring 104-a may be input into a machine learning classifier, which is configured to determine the duration of time when user 102-a is asleep (or has been asleep). Furthermore, the machine learning classifier may be configured to classify the duration into different sleep stages, including wakefulness, rapid eye movement (REM) sleep, light sleep (non-REM) sleep, and deep sleep (NREM). In some aspects, the classified sleep stages may be displayed to user 102-a via the GUI of user device 106-a. Sleep stage classification may be used to provide feedback to user 102-a regarding the user's sleep patterns, such as recommended bedtime and recommended wake-up time. Furthermore, in some implementations, the sleep stage classification techniques described herein may be used to calculate scores for each user, such as a Sleep Score and a Readiness Score.

[0033] In some respects, system 100 may leverage features derived from circadian rhythms to further improve physiological data acquisition, data processing procedures, and other techniques described herein. The term circadian rhythm may refer to a natural internal process that regulates an individual's sleep-wake cycle, repeating approximately every 24 hours. In this regard, the techniques described herein may utilize circadian rhythm adjustment models to improve physiological data acquisition, analysis, and data processing. For example, a circadian rhythm adjustment model may be input into a machine learning classifier along with physiological data collected from user 102-a via a wearable device 104-a. In this example, the circadian rhythm adjustment model may be configured to "weight" or adjust the physiological data collected over the user's natural, approximately 24-hour circadian rhythm. In some implementations, the system may initially start with a "baseline" circadian rhythm adjustment model and modify the baseline model using physiological data collected from each user 102 to generate an adjusted, individual circadian rhythm adjustment model specific to each respective user 102.

[0034] In some respects, system 100 may utilize other biological rhythms to further improve the collection, analysis, and processing of physiological data by phase of these other rhythms. For example, if a weekly rhythm is detected within an individual's baseline data, the model may be configured to adjust the “weights” of the data by day of the week. Biological rhythms that may require adjustment to the model in this manner include: 1) ultradian (rhythms faster than 24 hours, including sleep cycles in sleep states and periodic oscillations of less than an hour to several hours in physiological variables measured during wakefulness); 2) circadian rhythms; 3) non-endogenous daily rhythms that are shown to be imposed on top of circadian rhythms, such as in work schedules; 4) weekly rhythms, or other artificial time periodicities that are exogenously imposed (e.g., a 12-day rhythm may be used in a hypothetical culture with a 12-day “week”); 5) multi-day ovarian rhythms in women and spermatogenesis rhythms in men; 6) lunar rhythms (associated with individuals living with little or no artificial light); and 7) seasonal rhythms.

[0035] Biological rhythms are not always stationary. For example, many women experience variability in ovarian cycle length throughout the cycle, and ultradian rhythms are not expected to occur at exactly the same time or with the same periodicity across days, even within a single user. Therefore, the detection of these rhythms can be improved by using signal processing techniques sufficient to quantify the frequency composition while maintaining the temporal resolution of these rhythms in physiological data, assigning the phase of each rhythm to each measured point in time, thereby correcting adjustment models and time interval comparisons. Biological rhythm adjustment models and parameters can be added, as appropriate, in a combination of linear or nonlinear approaches, to more accurately capture the dynamic physiological baseline of an individual or group of individuals.

[0036] In some respects, each device of system 100 may support techniques for determining blood pressure based on the relative timing of pulse waves. That is, system 100 may use one or more wearable devices 104 (e.g., chest-worn wearable devices, wearable ring devices, wearable watches) to determine the blood pressure index of user 102. In other words, system 100 may enable wearable devices 104 worn routinely by user 102 to determine blood pressure based on the relative timing of user 102's pulse waves (e.g., heart rate pulse waves). Thus, aspects of this disclosure may enable more frequent blood pressure measurements, which may provide the user with a more comprehensive picture of their overall health.

[0037] When blood pressure changes, the heart rate wave may propagate to different parts of the body at different speeds. For example, the higher the blood pressure, the faster the heart rate may propagate throughout the body, and the lower the blood pressure, the faster the heart rate may propagate throughout the body. Therefore, system 100 may use one or more wearable devices 104 positioned relative to user 102 to acquire physiological data from one or more wearable devices 104, determine the pulse wave duration associated with the heart rate wave, and determine the blood pressure index of user 102 based on the pulse wave duration.

[0038] In some implementations, system 100 may use multiple wearable devices 104 positioned at different locations on the body (e.g., chest, fingers, wrists, ankles, etc.) to determine the blood pressure index of user 102. For example, a first wearable device 104-a at a first physiological location of user 102 (e.g., chest) and a second wearable device 210-b at a second physiological location of user 102 (e.g., wrists, fingers, ankles) may acquire physiological data from user 102. The physiological data may represent the first pulse wave observation time of user 102's heartbeat at the first physiological location, a second pulse wave observation time of the heartbeat, additional heartbeats of user 102, or both. Furthermore, system 100 may compare the first pulse wave observation time with the second pulse wave observation time to determine the pulse wave time associated with the heartbeat (e.g., pulse wave time difference). Therefore, system 100 can determine the blood pressure index of user 102 based on a comparison of pulse wave durations.

[0039] Furthermore, or alternatively, system 100 may use a single wearable device (e.g., a first wearable device 104-a) to determine the blood pressure index of user 102 based on when the pulse wave arrives in different layers of tissue. For example, wearable device 104-a may include one or more light-emitting components (e.g., one or more LEDs) and a photodetector for receiving light from one or more light-emitting components. The light-emitting components and photodetector may be coupled to a controller to transmit light associated with one or more wavelengths. Wearable device 104-a may also use the light received by the photodetector to obtain first physiological data from user 102. In some examples, the first physiological data may indicate the first pulse wave observation time of user 102's heartbeat at a first tissue penetration depth (e.g., epidermis, subcutaneous tissue). The wearable device 104-a may acquire second physiological data, which may indicate the second pulse wave observation time of the heartbeat at a second tissue penetration depth (e.g., the dermis), the user's additional heartbeats, or both. In some examples, the wearable device 104-a may determine that the heart pulse wave arrives at one or more capillaries located in a first layer (e.g., the tissue layer closest to the user 102's skin) faster than the heart pulse wave at one or more arteries located in a second layer (e.g., a deeper tissue layer further from the user 102's skin). Thus, the system 100 may determine the pulse wave time associated with the heartbeat, the additional heartbeat, or both, based on a comparison of the first pulse wave observation time and the second pulse wave observation time. In addition, the system 100 may use the pulse wave time to determine the user 102's blood pressure index. Thus, the system 100 may use the time it takes for the pulse wave to reach different layers of tissue to determine the user 102's blood pressure.

[0040] Those skilled in the art will understand that one or more aspects of this disclosure may be implemented in System 100 to further, or instead, solve problems other than those described above. Furthermore, aspects of this disclosure may provide technical improvements to the “conventional” systems or processes described herein. However, the description and accompanying drawings only include illustrative technical improvements resulting from implementing aspects of this disclosure and therefore do not represent all of the technical improvements provided in the claims.

[0041] Figure 2 shows an example of a system 200 that supports a technique for determining blood pressure based on the relative timing of pulse waves, according to aspects of this disclosure. System 200 may implement or be implemented by system 100. In particular, system 200 shows an example of a ring 104 (e.g., a wearable device 104), a user device 106, and a server 110, as described with reference to Figure 1.

[0042] In some respects, the ring 104 may be configured to be worn around the user's finger and may determine one or more user physiological parameters when worn around the user's finger. Exemplary measurements and determinations may include, but are not limited to, the user's skin temperature, pulse wave pattern, respiratory rate, heart rate, HRV, blood oxygen saturation, etc.

[0043] The system 200 further includes a user device 106 (e.g., a smartphone) that communicates with the ring 104. For example, the ring 104 may communicate with the user device 106 wirelessly and / or via a wired connection. In some implementations, the ring 104 may transmit measured and processed data (e.g., temperature data, PPG data, motion / accelerometer data, ring input data, etc.) to the user device 106. The user device 106 may also transmit data to the ring 104, such as firmware / configuration updates for the ring 104. The user device 106 may process the data. In some implementations, the user device 106 may transmit the data to the server 110 for processing and / or storage.

[0044] The ring 104 may include a housing comprising an inner housing 205-a and an outer housing 205-b. In some aspects, the housing 205 of the ring 104 may house, or otherwise include, various components of the ring, including, but not limited to, device electronics, power supplies (e.g., battery 210, and / or capacitors), and one or more substrates (e.g., printable circuit boards) interconnecting the device electronics and / or power supplies. The device electronics may include device modules (e.g., hardware / software), such as a processing module 230-a, memory 215, communication module 220-a, power module 225, etc. The device electronics may also include one or more sensors. Exemplary sensors may include one or more temperature sensors 240, a PPG sensor assembly (e.g., a PPG system 235), and one or more motion sensors 245.

[0045] The sensors may include associated modules (not shown) configured to communicate with each component / module of the ring 104 and generate signals associated with each sensor. In some aspects, each component / module of the ring 104 may be coupled to communicate with one another via wired or wireless connections. Furthermore, the ring 104 may include additional and / or alternative sensors or other components configured to collect physiological data from the user, including, for example, light sensors (e.g., LEDs), oxygen meter, etc.

[0046] The ring 104 illustrated and described with reference to Figure 2 is provided for illustrative purposes only. Therefore, the ring 104 may include additional or alternative components, such as those shown in Figure 2. Other rings 104 providing the functions described herein may be manufactured. For example, a ring 104 with fewer components (e.g., sensors) may be manufactured. In a particular example, a ring 104 may be manufactured having a single temperature sensor 240 (or other sensor), a power supply, and device electronics configured to read the single temperature sensor 240 (or other sensor). In another particular example, the temperature sensor 240 (or other sensor) may be attached to the user's finger (e.g., using a clamp, spring clamp, etc.). In this case, the sensor may be wired to another computing device, such as a wrist-worn computing device, that reads the temperature sensor 240 (or other sensor). In another example, a ring 104 including additional sensors and processing functions may be manufactured.

[0047] The housing 205 may include one or more housing 205 components. The housing 205 may include an outer housing 205-b component (e.g., a shell) and an inner housing 205-a component (e.g., a molded part). The housing 205 may include additional components (e.g., additional layers) not explicitly shown in Figure 2. For example, in some implementations, the ring 104 may include one or more insulating layers that electrically insulate the device electronics and other conductive materials (e.g., electrical traces) from the outer housing 205-b (e.g., a metal outer housing 205-b). The housing 205 may provide structural support for the device electronics, battery 210, substrate(s), and other components. For example, the housing 205 may protect the device electronics, battery 210, and substrate(s) from mechanical forces such as pressure and shock. The housing 205 may also protect the device electronics, battery 210, and substrate(s) from water and / or other chemicals.

[0048] The outer housing 205-b may be manufactured from one or more materials. In some implementations, the outer housing 205-b may contain a metal such as titanium, which can provide strength and wear resistance at a relatively light weight. The outer housing 205-b may be manufactured from other materials such as polymers. In some implementations, the outer housing 205-b may be both protective and decorative.

[0049] The inner housing 205-a may be configured to interface with the user's finger. The inner housing 205-a may be formed from a polymer (e.g., a medical-grade polymer) or other material. In some implementations, the inner housing 205-a may be translucent. For example, the inner housing 205-a may be translucent to light emitted by a PPG light-emitting diode (LED). In some implementations, the inner housing 205-a components may be molded onto the outer housing 205-b. For example, the inner housing 205-a may include a polymer molded (e.g., injection-molded) to fit into the outer housing 205-b metal shell.

[0050] The ring 104 may include one or more substrates (not shown). The device electronics and battery 210 may be contained on one or more substrates. For example, the device electronics and battery 210 may be mounted on one or more substrates. Exemplary substrates may include one or more printed circuit boards (PCBs), such as a flexible PCB (e.g., polyimide). In some implementations, the electronics / battery 210 may include surface mount devices (e.g., surface mount technology (SMT) devices) on the flexible PCB. In some implementations, one or more substrates (e.g., one or more flexible PCBs) may include electrical traces that provide electrical communication between the device electronics. The electrical traces may also connect the battery 210 to the device electronics.

[0051] The device electronics, battery 210, and circuit board can be arranged within the ring 104 in various ways. In some implementations, one circuit board containing the device electronics may be mounted along the bottom (e.g., lower half) of the ring 104 so that sensors (e.g., PPG system 235, temperature sensor 240, motion sensor 245, and other sensors) interface with the underside of the user's fingers. In these implementations, the battery 210 may be included along the top portion of the ring 104 (e.g., on another circuit board).

[0052] The various components / modules of ring 104 represent the functions (e.g., circuits and other components) that may be included in ring 104. A module may include any discrete and / or integrated electronic circuit components that implement analog and / or digital circuits capable of generating the functions assigned to the module herein. For example, a module may include analog circuits (e.g., amplifiers, filtering circuits, analog-to-digital converters, and / or other signal conditioning circuits). A module may include digital circuits (e.g., combinational or sequential logic circuits, memory circuits, etc.).

[0053] The memory 215 (memory module) of ring 104 may include any volatile, non-volatile, magnetic, or electrical medium, such as random access memory (RAM), read-only memory (ROM), non-volatile RAM (NVRAM), electrically erasable programmable ROM (EEPROM), flash memory, or any other memory device. The memory 215 may store any of the data described herein. For example, the memory 215 may be configured to store data collected by the respective sensors and PPG system 235 (e.g., motion data, temperature data, PPG data). Furthermore, the memory 215 may include instructions, when executed by one or more processing circuits, that cause the modules to perform various functions assigned to the modules herein. The device electronics of ring 104 described herein are merely illustrative device electronics. Therefore, the types of electronic components used to implement the device electronics may vary depending on design considerations.

[0054] The functions assigned to the modules of ring 104 as described herein may be embodied as one or more processors, hardware, firmware, software, or any combination thereof. The descriptions of different characteristics of the modules are intended to highlight different functional aspects and do not necessarily imply that such modules must be realized by separate hardware / software components. Rather, the functions associated with one or more modules may be performed by separate hardware / software components or integrated within a common hardware / software component.

[0055] The processing module 230-a of ring 104 may include one or more processors (e.g., processing units), which may include a microcontroller, a digital signal processor, a system-on-a-chip (SOC), and / or other processing devices. The processing module 230-a communicates with modules included in ring 104. For example, the processing module 230-a may send data to and receive data from other components of ring 104, such as modules and sensors. As described herein, modules may be implemented by various circuit components. Thus, modules may also be referred to as circuits (e.g., communication circuits and power circuits).

[0056] The processing module 230-a may communicate with memory 215. Memory 215 may contain computer-readable instructions that, when executed by the processing module 230-a, cause the processing module 230-a to perform various functions assigned to the processing module 230-a herein. In some implementations, the processing module 230-a (e.g., a microcontroller) may include additional features associated with other modules, such as communication functions provided by the communication module 220-a (e.g., an integrated Bluetooth® Low Energy transceiver) and / or additional onboard memory 215.

[0057] The communication module 220-a may include circuitry that provides wired and / or wireless communication with the user device 106 (e.g., communication module 220-b of the user device 106). In some implementations, communication modules 220-a and 220-b may include wireless communication circuits such as Bluetooth and / or Wi-Fi circuits. In some implementations, communication modules 220-a and 220-b may include wired communication circuits such as Universal Serial Bus (USB) communication circuits. Using communication module 220-a, the ring 104 and the user device 106 may be configured to communicate with each other. The ring's processing module 230-a may be configured to send / receive data to and from the user device 106 via communication module 220-a. Illustrative data may include, but is not limited to, motion data, temperature data, pulse wave waveform, heart rate data, HRV data, PPG data, and status updates (e.g., charge status, battery charge level, and / or ring 104 configuration settings). The ring processing module 230-a may also be configured to receive updates (e.g., software / firmware updates) and data from the user device 106.

[0058] The ring 104 may include a battery 210 (e.g., a rechargeable battery 210). An exemplary battery 210 may include a lithium-ion or lithium-polymer type battery 210, but a variety of battery 210 options are possible. The battery 210 may be charged wirelessly. In some implementations, the ring 104 may include a power source other than the battery 210, such as a capacitor. The power source (e.g., battery 210 or capacitor) may have a curved shape to conform to the curve of the ring 104. In some aspects, the charger or other power source may be used to collect data in addition to the data collected by the ring 104 itself, or may include additional sensors that complement the data collected by the ring 210 itself. Furthermore, the charger or other power source of the ring 104 may function as a user device 106, in which case the charger or other power source of the ring 104 may be configured to receive data from the ring 104, store and / or process the data received from the ring 104, and communicate data between the ring 104 and the server 110.

[0059] In some aspects, the ring 104 may include a power module 225 that can control the charging of the battery 210. For example, the power module 225 may interface with an external wireless charger that charges the battery 210 when interfaced with the ring 104. The charger may include a reference structure that mates with a reference structure of the ring 104 to make a specific orientation with the ring 104 during charging. The power module 225 may also regulate the voltage of the device electronics, regulate the power output to the device electronics, and monitor the charge state of the battery 210. In some implementations, the battery 210 may include a protection circuit module (PCM) that protects the battery 210 from high-current discharge, overvoltage during charging, and undervoltage during discharging. The power module 225 may also include electrostatic discharge (ESD) protection.

[0060] One or more temperature sensors 240 may be electrically coupled to the processing module 230-a. The temperature sensors 240 may be configured to generate a temperature signal (e.g., temperature data) indicating the temperature read or sensed by the temperature sensors 240. The processing module 230-a may determine the user's body temperature at the location of the temperature sensors 240. For example, in the ring 104, the temperature data generated by the temperature sensors 240 may indicate the user's temperature (e.g., skin temperature) at the user's finger. In some implementations, the temperature sensors 240 may be in contact with the user's skin. In other implementations, a portion of the housing 205 (e.g., the inner housing 205-a) may form a barrier (e.g., a thin thermally conductive barrier) between the temperature sensors 240 and the user's skin. In some implementations, the portion of the ring 104 configured to contact the user's finger may have a thermally conductive portion and an insulating portion. The thermally conductive portion may conduct heat from the user's finger to the temperature sensors 240. The insulating portion can insulate the ring 104 (for example, the temperature sensor 240) from the ambient temperature.

[0061] In some implementations, the temperature sensor 240 may generate a digital signal (e.g., temperature data) that the processing module 230-a can use to determine the temperature. In another example, if the temperature sensor 240 includes a passive sensor, the processing module 230-a (or the temperature sensor 240 module) may measure the current / voltage generated by the temperature sensor 240 and determine the temperature based on the measured current / voltage. An exemplary temperature sensor 240 may include a thermistor such as a negative temperature coefficient (NTC) thermistor, or other types of sensors including resistors, transistors, diodes, and / or other electrical / electronic components.

[0062] The processing module 230-a may sample the user's body temperature over time. For example, the processing module 230-a may sample the user's body temperature according to a sampling rate. The processing module 230-a may be configured to sample the temperature signal at other sampling rates higher or lower than one sample per second, although exemplary sampling rates may include one sample per second. In some implementations, the processing module 230-a may continuously sample the user's body temperature throughout the day and night. Sampling at a sufficient rate throughout the day (e.g., one sample per second) may provide sufficient temperature data for the analysis described herein.

[0063] The processing module 230-a may store the sampled temperature data in memory 215. In some implementations, the processing module 230-a may process the sampled temperature data. For example, the processing module 230-a may determine the average temperature value over a period of time. In one example, the processing module 230-a may determine the average temperature value per minute by summing all the temperature values ​​collected over one minute and dividing by the number of samples over one minute. In a particular example where temperature is sampled at one sample per second, the average temperature might be the sum of all temperatures sampled in one minute divided by 60 seconds. Memory 215 may store the average temperature value over time. In some implementations, memory 215 may store the average temperature (e.g., one per minute) instead of the sampled temperatures to conserve memory 215.

[0064] The sampling rate that can be stored in memory 215 may be configurable. In some implementations, the sampling rate may be the same throughout the day and night. In other implementations, the sampling rate may change throughout the day / night. In some implementations, ring 104 may filter / reject temperature readings such as large temperature spikes that do not indicate physiological changes (e.g., temperature spikes from a hot shower). In some implementations, ring 104 may filter / reject temperature readings that may be unreliable due to other factors such as excessive motion during exercise (e.g., as indicated by motion sensor 245).

[0065] Ring 104 (for example, a communication module) may transmit sampled and / or averaged temperature data to user device 106 for storage and / or further processing. User device 106 may transfer the sampled and / or averaged temperature data to server 110 for storage and / or further processing.

[0066] Although the ring 104 is shown as containing a single temperature sensor 240, the ring 104 may contain multiple temperature sensors 240 in one or more locations, such as positioned along the inner housing 205-a near the user's finger. In some implementations, the temperature sensor 240 may be a standalone temperature sensor 240. Furthermore, or instead, one or more temperature sensors 240 may be included with other components such as an accelerometer and / or a processor (for example, they may be packaged together with the other components).

[0067] The processing module 230-a may acquire and process data from multiple temperature sensors 240 in a similar manner to that described for a single temperature sensor 240. For example, the processing module 230 may individually sample, average, and store temperature data from each of the multiple temperature sensors 240. In other examples, the processing module 230-a may sample the sensors at different rates and average / store different values ​​for different sensors. In some implementations, the processing module 230-a may be configured to determine a single temperature based on the average of two or more temperatures determined by two or more temperature sensors 240 located at different positions on a finger.

[0068] The temperature sensors 240 on the ring 104 can acquire distal temperature at the user's finger (e.g., any finger). For example, one or more temperature sensors 240 on the ring 104 can acquire the user's temperature from the underside of the finger or at different locations on the finger. In some implementations, the ring 104 can acquire distal temperature continuously (e.g., at a certain sampling rate). While this specification describes distal temperature measured by the ring 104 at the finger, other devices may measure temperature at the same / different locations. In some cases, distal temperature measured at the user's finger may differ from temperature measured at the user's wrist or other external location. Furthermore, distal temperature measured at the user's finger (e.g., "shell" temperature) may differ from the user's core temperature. Thus, the ring 104 can provide a useful temperature signal that may not be acquired at other internal / external locations on the body. In some cases, continuous temperature measurement at the finger may capture temperature fluctuations (e.g., small or large fluctuations) that may not be apparent in core body temperature. For example, continuous temperature measurement on the finger can capture minute- or hourly temperature fluctuations, providing additional insights that may not be available through other temperature measurements on other parts of the body.

[0069] The ring 104 may include a PPG system 235. The PPG system 235 may include one or more light transmitters that transmit light. The PPG system 235 may also include one or more light receivers that receive light transmitted by one or more light transmitters. The light receivers may generate a signal (hereinafter, "PPG" signal) indicating the amount of light received by the light receivers. The light transmitters may illuminate an area of ​​the user's fingers. The PPG signal generated by the PPG system 235 may indicate blood perfusion in the illuminated area. For example, the PPG signal may indicate a change in blood volume in the illuminated area caused by the user's pulse pressure. The processing module 230-a may sample the PPG signal and determine the user's pulse waveform based on the PPG signal. The processing module 230-a may determine various physiological parameters, such as the user's respiratory rate, heart rate, HRV, oxygen saturation, and other circulatory parameters, based on the user's pulse waveform.

[0070] In some implementations, the PPG system 235 may be configured as a reflective PPG system 235 in which the optical receiver(s) receive transmitted light reflected through the area of ​​the user's fingers. In some implementations, the PPG system 235 may be configured as a transmissive PPG system 235 in which the optical transmitter(s) and optical receiver(s) are positioned facing each other so that light is sent directly to the optical receiver(s) through a portion of the user's fingers.

[0071] The number and ratio of transmitters and receivers included in the PPG system 235 may vary. Exemplary optical transmitters may include light-emitting diodes (LEDs). Optical transmitters may transmit light in the infrared spectrum and / or other spectra. Exemplary optical receivers may include, but are not limited to, optical sensors, phototransistors, and photodiodes. Optical receivers may be configured to generate a PPG signal in response to wavelengths received from optical transmitters. The positions of the transmitters and receivers may vary. Furthermore, a single device may include reflective and / or transmissive PPG systems 235.

[0072] The PPG system 235 shown in Figure 2 may, in some implementations, include a reflective PPG system 235. In these implementations, the PPG system 235 may include a centrally located optical receiver (e.g., at the bottom of the ring 104) and two optical transmitters located on each side of the optical receiver. In this implementation, the PPG system 235 (e.g., the optical receiver) may generate a PPG signal based on light received from one or both of the optical transmitters. In other implementations, other arrangements, combinations, and / or configurations of one or more optical transmitters and / or optical receivers are contemplated.

[0073] The processing module 230-a may control one or both of the optical transmitters to transmit light while sampling the PPG signal generated by the optical receiver. In some implementations, the processing module 230-a may cause the optical transmitter with a stronger received signal to transmit light while sampling the PPG signal generated by the optical receiver. For example, the selected optical transmitter may continuously emit light while the PPG signal is sampled at a sampling rate (e.g., 250 Hz).

[0074] Sampling the PPG signal generated by the PPG system 235 may yield a pulse wave waveform that may be referred to as "PPG". The pulse wave waveform may show blood pressure over time for multiple cardiac cycles. The pulse wave waveform may include peaks indicating cardiac cycles. Furthermore, the pulse wave waveform may include respiration-induced fluctuations that can be used to determine respiratory rate. In some implementations, the processing module 230-a may store the pulse wave waveform in memory 215. The processing module 230-a may process the pulse wave waveform, both when it was generated and / or from memory 215, to determine the user physiological parameters described herein.

[0075] The processing module 230-a may determine the user's heart rate based on the pulse waveform. For example, the processing module 230-a may determine the heart rate (e.g., beats per minute) based on the time between peaks in the pulse waveform. The time between peaks may be referred to as the heart rate interval (IBI). The processing module 230-a may store the determined heart rate value and IBI value in the memory 215.

[0076] The processing module 230-a can determine HRV over time. For example, the processing module 230-a can determine HRV based on fluctuations in IBI. The processing module 230-a can store HRV values ​​over time in memory 215. Furthermore, the processing module 230-a can determine the user's respiratory rate over time. For example, the processing module 230-a can determine the respiratory rate based on frequency modulation, amplitude modulation, or baseline modulation of the user's IBI value over a period of time. The respiratory rate can be calculated as breaths per minute or other respiratory rates (e.g., breaths per 30 seconds). The processing module 230-a can store the user's respiratory rate over time in memory 215.

[0077] The ring 104 may include one or more motion sensors 245, such as one or more accelerometers (e.g., 6-D accelerometers) and / or one or more gyroscopes (gyro). The motion sensors 245 may generate motion signals indicating the motion of the sensors. For example, the ring 104 may include one or more accelerometers that generate acceleration signals indicating the acceleration of the accelerometers. As another example, the ring 104 may include one or more gyro sensors that generate gyro signals indicating angular motion (e.g., angular velocity) and / or changes in orientation. The motion sensors 245 may be included in one or more sensor packages. An exemplary accelerometer / gyro sensor is the Bosch BMI160 inertial microelectromechanical system (MEMS) sensor, which can measure angular velocity and acceleration on three vertical axes.

[0078] The processing module 230-a may sample the motion signal at a sampling rate (e.g., 50 Hz) and determine the motion of the ring 104 based on the sampled motion signal. For example, the processing module 230-a may sample the acceleration signal to determine the acceleration of the ring 104. As another example, the processing module 230-a may sample the gyro signal to determine the angular motion. In some implementations, the processing module 230-a may store the motion data in memory 215. The motion data may include the sampled motion data, as well as motion data calculated based on the sampled motion signals (e.g., acceleration values ​​and angular values).

[0079] The ring 104 can store various types of data as described herein. For example, the ring 104 can store temperature data such as raw sampled temperature data and calculated temperature data (e.g., mean temperature). As another example, the ring 104 can store PPG signal data such as pulse wave waveforms and data calculated based on the pulse wave waveforms (e.g., heart rate values, IBI values, HRV values, and respiratory values). The ring 104 can also store motion data such as sampled motion data showing linear and angular motion.

[0080] The ring 104 or other computing device may calculate and store additional values ​​based on sampled / calculated physiological data. For example, the processing module 230 may calculate and store various metrics such as sleep metrics (e.g., sleep score), activity metrics, and readiness metrics. In some implementations, these additional values / metrics may be referred to as “derived values.” The ring 104, or other computing / wearable device, may calculate various values / metrics related to motion. Exemplary derived values ​​for motion data may include, but are not limited to, motion count values, regularity values, intensity values, metabolic equivalents (METs: metabolic equivalence of task values), and orientation values. Motion count, regularity values, intensity values, and METs may indicate the amount of user movement over time (e.g., velocity / acceleration). Orientation values ​​may indicate how the ring 104 is oriented on the user’s finger and whether the ring 104 is worn on the left or right hand.

[0081] In some implementations, motion counts and regularity values ​​may be determined by counting the number of acceleration peaks within one or more time periods (e.g., one or more periods of 30 seconds to 1 minute). Intensity values ​​may indicate the number of movements and the associated intensity of the movements (e.g., acceleration values). Intensity values ​​may be classified as low, medium, and high depending on the associated threshold acceleration value. METs may be determined based on the intensity of the movements during a period (e.g., 30 seconds), the regularity / irregularity of the movements, and the number of movements associated with different intensities.

[0082] In some implementations, the processing module 230-a may compress the data stored in memory 215. For example, the processing module 230-a may perform calculations based on sampled data and then delete the sampled data. As another example, the processing module 230-a may average the data over a longer period to reduce the number of values ​​stored. In a particular example, if the average user temperature over one minute is stored in memory 215, the processing module 230-a may calculate and store the average temperature over a five-minute period and then erase the one-minute average temperature data. The processing module 230-a may compress the data based on various factors such as the total amount of memory 215 used / available and / or the elapsed time since ring 104 last sent data to the user device 106.

[0083] The user's physiological parameters may be measured by sensors included on the ring 104, but other devices may also measure the user's physiological parameters. For example, the user's body temperature may be measured by the temperature sensor 240 included on the ring 104, but other devices may also measure the user's body temperature. In some examples, other wearable devices (e.g., wrist devices) may include sensors for measuring the user's physiological parameters. Furthermore, medical devices such as external medical devices (e.g., wearable medical devices) and / or implantable medical devices may measure the user's physiological parameters. One or more sensors on any type of computing device may be used to implement the techniques described herein.

[0084] Physiological measurements may be obtained continuously throughout the day and / or night. In some implementations, physiological measurements may be obtained between the daytime and / or nighttime portions. In some implementations, physiological measurements may be obtained in response to the user determining that they are in a particular state, such as active, resting, and / or sleeping. For example, ring 104 may perform physiological measurements in the resting / sleeping state to obtain a cleaner physiological signal. In one example, ring 104 or other device / system may detect when the user is resting and / or sleeping and obtain physiological parameters (e.g., temperature) of that detected state. The device / system may use resting / sleeping physiological data and / or other data when the user is in other states in order to implement the technology of this disclosure.

[0085] In some implementations, as described herein, the ring 104 may be configured to collect, store, and / or process data, and may transfer any of the data described herein to the user device 106 for storage and / or processing. In some aspects, the user device 106 includes a wearable application 250, an operating system (OS), a web browser application (e.g., a web browser 280), one or more additional applications, and a GUI 275. The user device 106 may further include other modules and components, such as sensors, audio devices, and haptic feedback devices. The wearable application 250 may include examples of applications (e.g., “Apps”) that can be installed on the user device 106. The wearable application 250 may be configured to take data from the ring 104, store the acquired data, and process the acquired data as described herein. For example, a wearable application 250 includes a user interface (UI) module 255, an acquisition module 260, a processing module 230-b, a communication module 220-b, and a storage module (e.g., a database 265) configured to store application data.

[0086] The various data processing operations described herein may be performed by the ring 104, the user device 106, the server 110, or any combination thereof. For example, in some cases, data collected by the ring 104 may be preprocessed and sent to the user device 106. In this example, the user device 106 may perform some data processing operations on the received data, send the data to the server 110 for data processing, or both. For example, in some cases, the user device 106 may perform processing operations that require relatively low processing power and / or operations that require relatively low latency, while the user device 106 may send the data to the server 110 for processing operations that require relatively high processing power and / or operations that allow for relatively high latency.

[0087] In some aspects, the ring 104, user device 106, and server 110 of system 200 may be configured to evaluate the user's sleep patterns. In particular, each component of system 200 may be used to collect data from the user via the ring 104 and to generate one or more scores for the user (e.g., sleep score, readiness score) based on the collected data. For example, as previously stated herein, the ring 104 of system 200 may be worn by the user to collect data from the user, including temperature, heart rate, HRV, etc. The data collected by the ring 104 may be used to determine when the user is sleeping in order to evaluate the user's sleep during a given "sleep day". In some aspects, the score may be calculated for the user for each respective sleep day, such that the first sleep day is associated with a first group of scores, the second sleep day with a second group of scores, and so on. The score may be calculated for each sleep day based on the data collected by the ring 104 during each sleep day. The score may include, but is not limited to, a sleep score, a readiness score, etc.

[0088] In some cases, a “sleep day” may be aligned with a conventional calendar day, such that a given sleep day lasts from midnight to midnight on each calendar day. In other cases, a sleep day may be shifted relative to a calendar day. For example, a sleep day may last from 6:00 pm (18:00) on one calendar day to 6:00 pm (18:00) on the next calendar day. In this example, 6:00 pm may function as a “cutoff time,” where data collected from the user before 6:00 pm is counted for the current sleep day, and data collected from the user after 6:00 pm is counted for the next sleep day. Due to the fact that most individuals sleep most at night, shifting sleep days relative to calendar days may allow system 200 to evaluate the user’s sleep pattern in a way that is consistent with the user’s sleep schedule. In some cases, the user may be able to selectively adjust the timing of sleep days relative to calendar days (e.g., via a GUI) so that the sleep days are aligned with the duration of sleep each user typically experiences.

[0089] In some implementations, each overall score for a user for each respective day (e.g., sleep score, readiness score) may be determined / calculated based on one or more “factors,” “contributing factors,” or “contributing factors.” For example, a user’s overall sleep score may be calculated based on a set of factors including total sleep, efficiency, rest, REM sleep, deep sleep, latency, timing, or any combination thereof. A sleep score may include any number of factors. The “total sleep” factor may refer to the sum of all sleep periods in a sleep day. The “efficiency” factor may reflect the proportion of time spent asleep compared to time awake while in bed and may be calculated using the efficiency average of the longer sleep periods in a sleep day (e.g., main sleep periods), weighted by the duration of each sleep period. The “rest” factor may indicate how restful a user’s sleep is and may be calculated using the average of all sleep periods in a sleep day, weighted by the duration of each period. Relaxation factors may also be based on "wake-up counts" (e.g., the sum of all wake-ups detected during different sleep periods (when the user wakes up)), excessive movement, and "get-up counts" (e.g., the sum of all get-ups detected during different sleep periods (when the user gets out of bed)).

[0090] The "REM sleep" factor may refer to the total duration of REM sleep across all sleep periods in a sleep day that include REM sleep. Similarly, the "deep sleep" factor may refer to the total duration of deep sleep across all sleep periods in a sleep day that include deep sleep. The "latency" factor may indicate how long it takes a user to fall asleep (e.g., average, median, longest) and may be calculated using the average of the longest sleep periods throughout the sleep day, weighted by the duration of each period and the number of such periods (e.g., a given sleep stage or a combination of multiple sleep stages may be a factor in itself or weighted by other factors). Finally, the "timing" factor may refer to the relative timing of sleep periods within a sleep day and / or calendar day and may be calculated using the average of all sleep periods in a sleep day, weighted by the duration of each period.

[0091] As another example, a user's overall readiness score may be calculated based on a set of factors including sleep, sleep balance, heart rate, HRV balance, recovery index, body temperature, activity, activity balance, or any combination thereof. The readiness score may include any number of factors. The “Sleep” factor may refer to the combined sleep score for all sleep periods within a sleep day. The “Sleep Balance” factor may refer to the cumulative duration of all sleep periods within a sleep day. In particular, sleep balance can indicate to a user whether the sleep they have had over a certain period (e.g., the past two weeks) is balanced with their needs. Typically, adults need 7-9 hours of sleep per night to be healthy, mentally sharp, and perform at their best both mentally and physically. However, since occasional sleepless nights are normal, the sleep balance factor takes long-term sleep patterns into account to determine whether each user's sleep needs are being met. The “resting heart rate” factor may represent the lowest heart rate from the longest sleep period of the sleep day (e.g., the primary sleep period), and / or the lowest heart rate from naps that occur after the primary sleep period.

[0092] Continuing to refer to the “factors” (e.g., contributing factors) of the readiness score, the “HRV balance” factor may represent the mean peak HRV from the main sleep period and naps occurring after the main sleep period. The HRV balance factor can help users track their recovery status by comparing their HRV trend over a first time period (e.g., two weeks) to the mean HRV over a second, longer time period (e.g., three months). The “recovery index” factor may be calculated based on the longest sleep period. The recovery index measures the time it takes for the user’s resting heart rate to stabilize during the night. A sign of very good recovery is that the user’s resting heart rate stabilizes during the first half of the night, at least six hours before the user wakes up, leaving the body time to recover for the next day. The “body temperature” factor may be calculated based on the longest sleep period (e.g., the main sleep period) or based on naps occurring after the longest sleep period if the user’s peak body temperature during the nap is at least 0.5°C higher than the peak body temperature during the longest period. In some respects, the ring may measure the user's body temperature while the user is sleeping, and the system 200 may display the user's average temperature relative to the user's baseline temperature. If the user's body temperature is outside the normal range (e.g., significantly higher or lower than 0.0), the body temperature factor may be highlighted (e.g., go to a “pay attention” state) or otherwise generate an alert to the user.

[0093] In some respects, system 200 may support techniques for determining blood pressure based on the relative timing of pulse waves (e.g., heart rate pulse). To provide some context for the need to determine blood pressure, in some examples, one or more users (e.g., individuals) 102 may measure their blood pressure regularly in a clinical setting, and thus, user 102 may measure their blood pressure infrequently (e.g., once or twice a year). In addition, user 102 may not only be unable to measure blood pressure, but also other health measurements related to heart rate, heart rate variability, cardiovascular age, arteriosclerosis, AFib, ectopic pulse, orthostatic test, VO2max, etc. Therefore, user 102 may unknowingly fail to take precautions based on whether health measurements indicate a positive or negative value. That is, if user 102 were aware of one or more health measurements, user 102 could integrate healthy living options, including improving nutrition (e.g., eating fruits and vegetables), physical activity, sleep, and stress management. However, as explained, user 102 rarely visits a primary healthcare facility where one or more physicians can measure the user's cardiovascular health (for example, by performing an electrocardiogram (ECG) and measuring continuous heart rate), and therefore user 102 may be unaware of risk factors such as an increased risk of heart attack, stroke, heart failure, and other complications.

[0094] In particular, users 102 affected by cardiovascular health issues may make lifestyle choices (e.g., changes) to improve their overall cardiovascular health in the long term. For example, a user 102 monitoring their cardiovascular health may be concerned with risk factors for heart disease and / or stroke and may reduce unhealthy eating habits (e.g., high salt intake), lack of exercise, tobacco use, and alcohol. A user 102 may also reduce these behaviors to avoid increased blood pressure, increased blood sugar, or increased blood lipids, which could lead to them being overweight and / or obese. In some cases, a user 102 may be concerned with one or more cardiovascular health measures, such as cardiovascular age, also known as heart age and vascular age. Specifically, heart age is an assessment of well-known risk factors for heart disease (e.g., age, sex, blood pressure, cholesterol) to estimate the user 102's risk of heart attack or stroke compared to a defined health range. In some cases, when heart age exceeds the user 102's current age, the user 102 may have a modifiable risk of developing heart disease.

[0095] In another example, user 102 may have concerns about their vascular age, and a vascular age test may provide a measure of user 102's apparent arterial age compared to a healthy user 102. In some examples, user 102 may display a vascular age exceeding their chronological age, indicating that user 102 may be at risk of developing cardiovascular disease (CVD). Therefore, affected user 102 may reduce arteriosclerosis and blood pressure and mitigate vascular aging by implementing lifestyle changes such as increasing aerobic exercise, reducing calorie intake, reducing sodium including flavonoids in the diet, and other healthy eating patterns. In some aspects, tests that produce cardiovascular age measurements may compare data from one user 102 to that of multiple users 102. That is, the test may compare user 102's pulse waveform to typical pulse waveforms across different age groups.

[0096] In some respects, cardiovascular health measurements can utilize blood pressure measurements to accurately predict user 102's health and well-being. Specifically, blood pressure may represent binary information including systolic blood pressure measured from one or more arteries during user 102's heartbeat and diastolic blood pressure measured from one or more arteries between user 102's heartbeats. In some examples, blood pressure classifications may include either normal blood pressure or hypertension. For user 102, normal blood pressure may represent a systolic blood pressure of less than 130 millimeters of mercury (mmHg) and a diastolic blood pressure of less than 80 mmHg. Alternatively, hypertension may represent a systolic blood pressure greater than 130 mmHg and a diastolic blood pressure greater than 80 mmHg.

[0097] In some respects, blood pressure measurements can indicate the pressure of circulating blood against the walls of blood vessels. In some cases, blood pressure can result from the user's heart pumping blood through the circulatory system. That is, the heart pumps blood in the form of pulse waves (e.g., pulsations), and each pulse wave has morphology (e.g., morphological features describing the size / shape of the pulse wave). Furthermore, each pulse wave may exhibit different morphology (e.g., size and shape) corresponding to blood pressure (e.g., high or low). For example, pulse waves obtained in different ways, such as PPG pulse waves and arterial pressure (ABP) pulse waves, may exhibit different systolic peaks, diastolic peaks, overlapping peaks, pulse wave width, pulse wave slope, inflection points, etc.

[0098] In some examples, a comparison of pulse waves may show the difference between PPG pulse waves obtained non-invasively (e.g., by a finger clip device) and ABP pulse waves obtained invasively (e.g., by direct insertion into the user's vein via a needle). Furthermore, PPG and ABP pulse waves may be compared graphically over time to determine in-phase analysis. That is, morphological correlations (e.g., r) between PPG and ABP waveforms may be determined to accurately determine whether the user falls into a specific blood pressure category, such as normal blood pressure (e.g., normal blood pressure), prehypertension (e.g., at risk of hypertension), or hypertension (e.g., hypertension). Thus, in order for the system to measure blood pressure appropriately, the system may utilize multiple pulse waves to appropriately indicate the corresponding blood pressure category of user 102 and determine whether user 102 is at risk of a specific blood pressure condition or disease.

[0099] In some cases, pulse waves may be monitored via spot checks, and binary classification may indicate whether the pulse wave is normal or elevated. In other cases, pulse waves may be evaluated against a blood pressure trend (e.g., a blood pressure trend line). That is, pulse waves may be compared to a typical blood pressure trend of the user expressed at different times of the day. In some cases, pulse waves may be acquired over a period of time (e.g., weekly, monthly, yearly). Thus, blood pressure over a certain period of time may be compared to the user's blood pressure, which may include the sum of continuous blood pressure at night. In such cases, continuous monitoring of blood pressure (e.g., chronic exposure) may be an important indicator (e.g., a determinant) of cardiovascular risk. That is, the area under the blood pressure curve, in other words, the cumulative cardiovascular risk, may be calculated by multiplying the continuous blood pressure by the time (e.g., area under the curve = time * continuous blood pressure). In some cases, pulse waves may be compared to a typical nocturnal blood pressure trend to determine whether the user has nocturnal hypertension based on the pulse wave drop. For a user, a normal nocturnal blood pressure trend may show a blood pressure drop that is about 10-15% lower than a typical daytime pulse wave. However, detecting blood pressure changes exceeding 15% (e.g., changes based on absolute and additional values) may alert users to conditions such as elevated sodium, salt sensitivity, chronic kidney disease (CKD), congestive heart failure (CHF), diabetes, structural vascular disease, or insomnia. Furthermore, the U.S. Food and Drug Administration (FDA) permits monitoring pulse waves via spot checks or blood pressure trends to detect a user's blood pressure, and therefore, techniques supporting these methods would be beneficial for integration into users outside of hospital settings.

[0100] In some respects, one or more healthcare professionals (e.g., nurses, doctors) may use blood pressure devices (e.g., blood pressure monitors, blood pressure cuffs, blood pressure monitors) that may miss one or more pulse waves and determine the blood pressure index for each user 102. In some cases, user 102 may use a home blood pressure device to obtain blood pressure index outside of a clinical setting. However, blood pressure devices may use one or more arm cuffs that may be uncomfortable for the user to wear consistently. That is, one or more solutions for conveniently measuring blood pressure on a daily basis may enable user 102 to monitor their health. However, conventional wearable devices 104 have been unable to perform blood pressure measurements due to limitations in signal processing and a lack of information about the relationship between blood pressure and PPG waveform characteristics. Therefore, methods and / or techniques for conveniently measuring blood pressure on a consistent basis are desired but have not yet been implemented.

[0101] Accordingly, the system 200 of this disclosure may support techniques for determining blood pressure based on the relative timing of pulse waves. That is, the system 200 may determine the blood pressure of a user 102 using one or more wearable devices 104 (e.g., one or more wearable ring devices, a wristwatch, a chest monitor). Thus, the system 200 may use one or more wearable devices 104 positioned at relative positions on the user 102 to acquire physiological data from one or more wearable devices 104, determine the pulse wave duration associated with one or more heartbeats, and determine the blood pressure index of the user 102 based on the pulse wave duration.

[0102] In this example, Figure 2 shows a single wearable device 104 connected to a user device 106, but the system 200 may include additional wearable devices 104 (not shown) configured to communicate with the user device 106. That is, in some cases, the system 200 may use multiple wearable devices 104 (e.g., chest-worn wearable devices, wearable ring devices, wearable watches) positioned at different physiological locations (e.g., parts) on the body (e.g., chest, fingers, wrists, ankles, etc.) to determine the blood pressure index of user 102.

[0103] For example, a first wearable device 104 located at a first physiological location of user 102 and a second wearable device 104 located at a second physiological location of user 102 can each acquire physiological data from user 102. That is, one or more heartbeats propagate from user 102's heart to different locations on user 102's body (e.g., fingers, toes, head, etc.). In this example, one or more heartbeats may be interchangeable with one or more pulse waves. In some cases, pulse waves may propagate to different physiological locations at different speeds based on user 102's fluctuating blood pressure. For example, higher blood pressure may indicate that the pulse wave travels faster to different physiological locations, while lower blood pressure may indicate that the pulse wave travels slower to different physiological locations. That is, as blood pressure fluctuates with speed, the pulse wave may reach different physiological locations at different times.

[0104] In some examples, system 200 may acquire physiological data indicating the pulse wave observation time of one or more heartbeats. In some aspects, system 200 may acquire first physiological data indicating the first pulse wave observation time of the user's heartbeat at a first physiological location from user 102 via first wearable device 104, and second physiological data indicating the second pulse wave observation time of the heartbeat, an additional heartbeat of the user, or both from user 102 via second wearable device 104. In some cases, wearable device 104 may use a PPG system 235 including one or more light-emitting components (e.g., LEDs) and a photodetector near the surface of the skin to measure volume fluctuations of blood flow in user 102. In some examples, a triple-LED (e.g., red, green, and IR) PPG system 235 may allow wearable device 104 to propagate multiple light waves into user 102's tissues based on the wavelength of light in order to acquire physiological data. In other words, the PPG system 235 can enable system 200 to acquire first physiological data, which may include first PPG data, via the first wearable device 104 at a first physiological location, and second physiological data, which may include second PPG data, via the second wearable device 104 at a second physiological location.

[0105] Furthermore, or alternatively, the first physiological data may include acceleration data (e.g., motion data), ECG data, or both. In some cases, the wearable device 104 may acquire acceleration data from one or more motion sensors 245. That is, the system 200 may use the ECG and acceleration data, combined with PPG data from the second physiological data, to identify one or more pulse waves in the user 102's chest and determine when one or more pulse waves reach the user 102's extremities.

[0106] Furthermore, the first physiological data may represent the first pulse wave observation time, and the second physiological data may represent the second pulse wave observation time. Each pulse wave observation time may represent the time when the pulse wave was observed at each distal location on the body (e.g., finger, earlobe, toe, etc.). Thus, the pulse wave observation times can be used to determine the pulse wave time (e.g., pulse wave transmission time), which indicates the time it takes for the pulse wave to travel from one part of the body to another.

[0107] To determine the duration of one or more pulse waves for one or more heartbeats, one or more healthcare professionals may perform an ECG examination, in which electrical signals from the user 102's heart are checked for cardiac status and one or more pulse wave durations may be monitored. For example, an ECG examination may monitor one or more pulse wave durations, such as pulse wave propagation time (PTT) and pulse wave arrival time (PAT), which indicate the time elapsed for a pulse wave to reach different locations on the body of one or more users 102. That is, PTT may indicate the time period during which a pulse wave travels from one arterial site to another (for example, the time difference between the arrival times of pulse waves at two peripheral site PPGs). In another example, PAT may indicate the time interval during which a pulse wave travels from the user 102's heart to one or more distal locations on the body. That is, PAT may take into account PTT in addition to the pre-ejection period (PEP), where PEP is the time required to convert the electrical signal into mechanical pumping force and the isovolumetric contraction of the left ventricle to open the aortic valve in user 102's heart, plus the time period during which blood is not ejected. In some examples, pulse wave observation times may be compared to estimate user 102's accurate blood pressure. For example, system 200 may estimate user 102's blood pressure by comparing PTT representing a first pulse wave observation time with PAT representing a second observation time. Thus, system 200 may observe multiple pulse wave observation times to determine when one or more pulse waves arrive at different parts of user 102's body (e.g., from the ECG in the heart to the PPG pulse wave in the finger, or from the PPG in the wrist to the finger).

[0108] Once the pulse wave observation time is determined, the system 200 may determine the pulse wave duration (e.g., pulse wave transmission time, pulse wave time difference) associated with one or more heartbeats. That is, the system 200 may determine the user 102's blood pressure index by comparing each pulse wave observation time, such as comparing the first pulse wave observation time when one pulse wave reaches a first physiological position with the second observation time when one pulse wave reaches a second physiological position. Alternatively, the system 200 may determine the user 102's blood pressure index by comparing the first pulse wave observation time when one pulse wave reaches a first physiological position with the second pulse wave observation time when an additional pulse wave reaches a second physiological position. That is, the system 200 may utilize multiple wearable devices 104 attached to different physiological positions and compare different pulse wave observation times to determine the corresponding blood pressure index for user 102.

[0109] Furthermore, or alternatively, the system 200 may use a single wearable device 104 to determine a blood pressure index for user 102 based on when pulse waves arrive at different layers of tissue. For example, wearable device 104-a may use a triple-LED (e.g., red, green, and IR) PPG system 235 to allow wearable device 104 to propagate multiple light waves into user 102's tissue based on the wavelength of light. That is, the depth of light penetration into user 102's skin (e.g., wavelength range) increases with wavelength from the UV to the visible light range and through the IR range. In some cases, the depth of light penetration into user 102's skin may vary because the distance from the LED to the penetration depth may be fixed within a certain range, but the signal may reach further penetration depths because different wavelengths of light may be used. In system 200, light-emitting components and photodetectors may be coupled to a controller to transmit light associated with one or more wavelengths. For example, the controller of the wearable device 104 may transmit blue light associated with a wavelength of approximately 460 nanometers (nm), green light associated with a wavelength of approximately 530 nm, red light associated with a wavelength of approximately 660 nm, and / or IR light associated with a wavelength of approximately 940 nm, and each of the transmitted light wavelengths may reach one or more layers of tissue (e.g., an epidermal layer of approximately 0.3 mm, a dermal layer of approximately 1.0 mm, and a subcutaneous tissue layer of approximately 3.0 mm). That is, each of the transmitted light may reach one or more layers of tissue where blood vessels are located, such as capillaries located closest to the user 102's skin in the epidermis, arterioles located in the intermediate layer in the dermis, and arteries located in the deepest layer in the subcutaneous tissue. Thus, the system 200 may use light-emitting components and photodetectors coupled to the controller on the wearable device 104 to send one or more lights associated with wavelength ranges to one or more tissue layers at multiple locations to acquire physiological data.

[0110] In some implementations, the system 200 may acquire physiological data via one or more pressure sensors 246. In some examples, first physiological data may be acquired during a first time interval associated with a first pressure applied between the wearable device 104 and the tissue layer. Furthermore, second physiological data may be acquired during a second time interval associated with a second pressure applied between the wearable device 104 and the tissue layer. In some aspects, the system 200 includes a wearable device 104 having an optical sensor in contact with the user 102's skin, the optical sensor may restrict blood circulation in different skin tissue layers. Thus, by changing the pressure applied to the wearable device 104, light of different wavelengths can be allowed to penetrate to different tissue penetration depths, and thus heart rate pulse waves can be identified at different penetration depths. In some cases, the pressure between the optical sensor and the user 102's skin may be gradually increased, so that each of the tissue layers is blocked, and the PPG system 235 may not be able to transmit light through the tissue layer from one or more light-emitting components. In some cases, external pressure may be applied to the optical sensor when user 102 grasps an object or when user 102 has a swollen extremity (e.g., a finger) due to dehydration or the like.

[0111] In some cases, user 102 may apply a first pressure during a first time interval and / or a second pressure during a second time interval to acquire first physiological data, second physiological data, or both. That is, the PPG system 235 may detect changes in one or more pulse waves (e.g., PPG pulse waves) from light-emitting components (e.g., light of different colors) resulting from external pressure detected by a pressure sensor 246 indicating pressure from an optical sensor acting on user 102's intravenous pressure (e.g., blood pressure). That is, system 200 may determine a correlation between arterial pressure and one or more pulse wave morphologies (e.g., shapes) obtained from capillaries located closest to user 102's skin in the epidermis, arterioles located in the middle layer of the dermis, and arteries located in the deepest layer of the subcutaneous tissue.

[0112] In some examples, the first physiological data may include PPG data, and the second physiological data may include pressure data (e.g., bioimpedance data, piezoelectric data, or both). Thus, the system 200 may determine the correlation between arterial pressure and pulse wave morphology, and may consider external pressure when determining the user 102's blood pressure. Furthermore, in some aspects, a pressure sensor (e.g., a piezoelectric sensor) may be used to identify vibrations or other pressure changes that can be assigned to a heartbeat, which may be used to determine when a heartbeat is detected (e.g., pulse wave arrival time), and thus may be used to determine the user's blood pressure index.

[0113] In some aspects, the system may be configured to identify other conditions or characteristics of the wearable device 104 and / or user 102 that affect signal quality or characteristics, such as user skin temperature and ring rotation / fit (e.g., tightness or looseness of the ring, as determined using a pressure sensor or PPG sensor). In such cases, the system may be configured to identify how such characteristics affect the blood pressure index and to compensate for such characteristics when determining the user's blood pressure index. That is, the PPG signal may be compensated using data from other sources such as a pressure sensor or a temperature sensor.

[0114] Furthermore, or alternatively, the first and / or second physiological data may include acceleration data (e.g., motion data) associated with user 102. In some cases, the wearable device 104 may acquire acceleration data from one or more motion sensors 245. For example, the wearable device 104 may use the motion sensors 245 to determine user 102's heart rate when user 102 is moving (e.g., exercising). That is, the system 200 may use the acceleration data to show how motion affects blood flow, and subsequently blood pressure.

[0115] Furthermore, a single wearable device 104 may acquire first physiological data from user 102 using the PPG system 235. In some examples, the first physiological data may represent the first pulse wave observation time of user 102's heartbeat at a first tissue penetration depth (e.g., epidermis, dermis). In addition, the wearable device 104 may acquire second physiological data from user 102, which may represent the second pulse wave observation time of heartbeat, additional heartbeats of the user, or both, at a second tissue penetration depth (e.g., dermis, subcutaneous tissue). That is, the system 200 may transfer PPG data from wearable device 104 to one or more user devices 106 for processing. In some cases, the system 200 may determine that the heart pulse wave arrives faster in one or more capillaries located in a first layer (e.g., the tissue layer closest to the user 102's skin) and slower in one or more arteries located in a second layer (e.g., deeper tissue layers further from the user 102's skin). Therefore, the system 200 may enable the controller to determine the pulse wave time associated with a heartbeat, an additional heartbeat, or both, based on a comparison of the first pulse wave observation time and the second pulse wave observation time. Furthermore, the system 200 may use the pulse wave time to determine the user 102's blood pressure index. Thus, the system 200 may determine the user 102's blood pressure index by measuring the time elapsed for the pulse wave to reach different tissue penetration depths using a single wearable device 104. As described herein, the system 200 may determine the user 102's blood pressure index and may selectively adjust the user 102's blood pressure index using acceleration data from one or more motion sensors 245.

[0116] In some aspects, the system 200 may transfer physiological data, including pulse wave observation times for one or more pulse waves for physiological location and / or penetration depth, from one or more wearable devices 104 to one or more user devices 106. That is, once the user device 106 has acquired the physiological data, it may determine the blood pressure index of user 102. In some aspects, the user device 106 may store the blood pressure trend of user 102 in a database 265. That is, the blood pressure trend may indicate the normal (e.g., typical) blood pressure level of user 102 and may indicate the baseline blood pressure index associated with user 102. Furthermore, the user device 106 may compare the current blood pressure index with the baseline blood pressure index and calculate the difference (e.g., deviation). In some cases, user 106 may determine a significant difference between user 102's baseline blood pressure index and user 102's current blood pressure index and may use the GUI 275 of the user device 106 to display the information associated with the difference. Therefore, GUI 275 may alert (e.g., notify) the user 102 of the current blood pressure index compared to the user 102's typical blood pressure trend, and / or any additional instructions the user 102 should follow to calibrate the blood pressure index.

[0117] Figure 3 shows an example of a multiple wearable device system 300 that supports a technique for determining blood pressure based on the relative timing of pulse waves, according to aspects of the present disclosure. In some implementations, the multiple wearable device system 300 may implement or be implemented by aspects of system 100 and system 200 as described with reference to Figures 1 and 2. For example, the multiple wearable device system 300 may be implemented by a wearable device 104 (e.g., a ring 104), a user device 106, one or more servers 110, or any combination thereof.

[0118] In the following description of the multiple wearable device system 300, the operations may be performed in an order different from the exemplary order shown, or the operations may be performed in a different order or at different times. Some operations may also be omitted from the multiple wearable device system 300, and other operations may be added to the multiple wearable device system 300. In this example, the multiple wearable device system 300 may be referred to as system 300. Thus, “first wearable device 104-a,” “second wearable device 104-b,” and similar terms may be used interchangeably with “wearable ring device” unless otherwise specified herein.

[0119] In the example shown in Figure 3, the system 300 may use multiple wearable devices 104 (e.g., chest-worn wearable device, wearable ring device, wearable watch) positioned at different locations on the body (e.g., chest, fingers, wrists, ankles, etc.) to determine the blood pressure index of user 102. In this example, user 102 may wear a first wearable device 104-a at a location close to user 102's chest (e.g., a first physiological location, first position 305-a) and a second wearable device 104-b at a location on user 102's extremities (e.g., fingers, hands, wrists, feet, ankles) (e.g., a second physiological location, second position 305-b). In other words, one or more heartbeats propagate from the user 102's heart to different (e.g., distal) locations on the user 102's body (e.g., fingers, toes, head, etc.). In this example, one or more heartbeats may be interchangeable with one or more pulse waves.

[0120] As described herein, the heart rate pulse wave can propagate to different locations 305 on the body at a fluctuating speed based on the user 102's fluctuating blood pressure. For example, the higher the blood pressure, the faster the heart rate can propagate throughout the body, and the lower the blood pressure, the faster the heart rate can propagate throughout the body. In other words, as blood pressure fluctuates according to the speed, the pulse wave can reach different locations 305 at different times.

[0121] In some cases, the system 300 may acquire physiological data from the wearable device 104, such as first physiological data and second physiological data. In some implementations, the system 300 may acquire physiological data including one or more heart rate pulse waves of user 102, and may compare pulse waves over a period of time. In some examples, the system 300 may acquire first physiological data from user 102 via the first wearable device 104-a, indicating the observation time 310-a of the first pulse wave of user 102's heart rate at a first location 305-a, and second physiological data from user 102 via the second wearable device 104-b, indicating the observation time 310-b of the second pulse wave of user 102's heart rate (or additional heart rate) at a second location 305-b. In some cases, the first pulse wave observation time 310-a and the second pulse wave observation time 310-b may indicate when a heartbeat (or separate heartbeat) arrives at (for example, is observed) the respective location 305.

[0122] In some cases, the pulse wave observation time 310 may be used to determine the time period it takes for the heart rate pulse wave to travel between different locations on the user's body (for example, the time it takes for the heartbeat to travel from the heart at a first location 305-a to a second location 305-b). That is, user 102 may wear multiple wearable devices 104 at different locations 305. In this example, wearable device 104-a is worn on user 102's chest and located at location 305-a, and wearable device 104-b is worn on user 102's finger. However, in other examples, wearable device 104 may include wearable device 104 (e.g., a wearable watch) (not shown) worn on user 102's wrist at the first location 305-a and wearable device 104-b worn on user 102's finger at the second location 305-b.

[0123] In these and additional examples, the system 300 may measure pulse wave observation times 310 indicating when a heartbeat arrives at different locations 305. In some examples, the system 300 may determine that a first pulse wave observation time 310-a at a first location 305-a is recorded earlier than a second pulse wave observation time 310 at a second location 305-b. That is, the second pulse wave observation time 310-b may occur after the first pulse wave observation time 310-a due to the additional time required for one or more pulse waves to travel from the heart to the second location 305. In such examples, the system 300 may record different pulse wave observation times 310 for a single heartbeat in different wearable devices 104 depending on the location 305 of the wearable device 104 relative to the user 102's heart.

[0124] In some examples, the pulse wave observation time 310 may include time measurements, specifically PTT and PAT, which indicate the time elapsed for the pulse wave to reach different locations on the body of one or more users 102. That is, PTT may indicate the time period during which the pulse wave travels from one arterial site to another (for example, the time difference between the arrival times of pulse waves at two peripheral site PPGs). In other examples, PAT may indicate the time interval during which the pulse wave travels from the heart of user 102 to one or more distal locations on the body. That is, PAT may consider PTT in addition to the pre-ejection period (PEP), where PEP is the time period during which blood is not ejected, in addition to the time required to convert electrical signals into mechanical pumping force and the isovolumetric contraction of the left ventricle to open the aortic valve in the heart of user 102. In some examples, the pulse wave observation time 310 may be compared to estimate the accurate blood pressure of user 102. For example, system 300 can estimate user 102's blood pressure by comparing PTT, which may represent a first pulse wave observation time 310-a at a first position 305-a, with PAT, which may represent a second observation time 310-b at a second position 305-b. Thus, system 300 can observe multiple pulse wave observation times 310 to determine when one or more pulse waves arrive at different parts of user 102's body (for example, from the ECG in the heart to the PPG pulse wave in the finger, or from the PPG in the wrist to the finger).

[0125] Once the pulse wave observation time 310 is determined, the system 300 may determine the pulse wave time (e.g., PTT, PAT, pulse wave time difference) associated with one or more heartbeats. That is, the system 300 may compare each pulse wave observation time 310, such as comparing a first pulse wave observation time 310-a with a second observation time 310-b, to determine a blood pressure index for user 102. In some examples, the system 300 may determine the pulse wave time as the time interval between the first pulse wave observation time 310-a and the second pulse wave observation time 310-b. Thus, the system 300 may utilize multiple wearable devices 104 attached to different locations 305, compare the time intervals between observation times 310 to determine when the pulse wave was detected at a different location 305, and determine the blood pressure index for user 102.

[0126] Figure 3 shows different wearable devices 104-a and 104-b positioned in close proximity to the user's heart and the user's hands / fingers, but this is for illustrative purposes only. In this regard, aspects of the present disclosure can be used to compare pulse wave observation times 310 between any two locations 305 on the user's body and thus measure pulse wave times (e.g., PTT, PAT) between any two locations 305. For example, in other cases, the system 300 can measure pulse wave observation times 310 between wearable devices 104 worn on each hand, between a wearable device worn on the user's wrist and the user's fingers, etc. In such cases, the pulse wave observation times 310 can be used to determine the user's blood pressure index.

[0127] Figure 4 shows an example of a wearable device system 400 that supports a technique for determining blood pressure based on the relative timing of pulse waves, according to the aspects of this disclosure. In some implementations, the wearable device system 400 may implement or be implemented by aspects of system 100, system 200, and system 300, as described with reference to Figures 1 to 3.

[0128] For example, the wearable device system 400 may be implemented by a wearable device 104 (e.g., a ring 104), a user device 106, one or more servers 110, or any combination thereof. In the following description of the wearable device system 400, the operations may be performed in a different order than the exemplary order shown, or the operations may be performed in a different order or at different times. Some operations may also be omitted from the wearable device system 400, and other operations may be added to the wearable device system 400. In this example, the wearable device system 400 may be referred to as system 400. Thus, “wearable device 104-c” may be used interchangeably with “wearable ring device” unless otherwise specified herein.

[0129] In the example shown in Figure 4, system 400 may use a single wearable device 104-c to determine a blood pressure index for user 102 based on when the pulse wave reaches different tissue layers 420. For example, wearable device 104-c may use PPG technology, which includes a triple LED (e.g., red, green, and IR) system that allows wearable device 104-c to propagate multiple light waves into different tissue layers 420 of user 102 based on the wavelength of light. That is, the depth of light penetration into user 102's skin increases with wavelength from the UV to the visible light range and through the IR range.

[0130] In system 400, light-emitting components 410 (e.g., LEDs) and photodetectors 415 may be coupled to a controller to transmit light to a location 425 associated with one or more wavelengths and to acquire measurements. In other words, light of different wavelengths (and / or different pressures applied to the wearable device 104-c) may be used to transmit light to different tissue penetration depths to determine pulse wave observation times (e.g., pulse wave observation times 310 as shown in Figure 3) at different locations 425.

[0131] In this example, the light-emitting component 410 may emit first light (not shown) associated with a wavelength range that penetrates to a depth or position 425-a in the epidermal layer 420, and the first light is returned to the photodetector 415 along with the acquired first physiological data. Furthermore, the light-emitting component 410 may emit second light associated with a wavelength range that penetrates to a depth or position 425-b in the subcutaneous layer 420, and the second light is returned to the photodetector 415 along with the acquired second physiological data. In other words, the system 400 can enable the controller of the wearable device 104 to transmit blue light that travels up to 460 nm, green light associated with a wavelength of approximately 530 nm, red light associated with a wavelength of approximately 660 nm, and / or IR light associated with a wavelength of approximately 940 nm, and each of the transmitted wavelengths of light may reach one or more tissue layers 420 (e.g., epidermal layer 420-a at approximately 0.3 mm, dermal layer 420-b at approximately 1.0 mm, and subcutaneous tissue layer 420-c at approximately 3.0 mm). That is, each of the transmitted light may reach one or more layers of tissue where blood vessels are located, such as capillaries in the epidermis that are closest to the user 102's skin, arterioles in the middle layer of the dermis, and arteries in the deepest layer of the subcutaneous tissue. Therefore, the system 400 may use a light-emitting component 410 and a photodetector 415 coupled to a controller on the wearable device 104-c to transmit one or more lights associated with a wavelength range to one or more tissue layers 420 at multiple locations 425 in order to acquire physiological data.

[0132] Furthermore, a single wearable device 104-c may transmit light from a light-emitting component 410 through one or more tissue layers 420 to a photodetector 415 in order to acquire first physiological data from user 102. In some examples, the first physiological data may indicate the first pulse wave observation time of user 102's heartbeat at a first tissue penetration depth (e.g., epidermal layer 420-a, dermal layer 420-b). The wearable device 104-c may also acquire second physiological data from user 102, which may indicate the second pulse wave observation time of heartbeat, additional heartbeats of the user, or both, at a second tissue penetration depth (e.g., dermal layer 420-b, subcutaneous tissue layer 420-c). In some cases, the system 200 may determine that the heart pulse wave arrives first at one or more arteries located in a second layer, such as the dermis 420-b or the subcutaneous layer 420-c, and later at one or more capillaries located in a first layer, such as the epidermal layer 420-a, or vice versa.

[0133] Therefore, system 400 may determine pulse wave times associated with a heartbeat, an additional heartbeat, or both, based on a comparison of the first pulse wave observation time and the second pulse wave observation time. Furthermore, system 400 may use the pulse wave times to determine the blood pressure index of user 102. In other words, system 400 may determine the difference when heartbeat pulse waves are observed at different tissue layers or different penetration depths in order to determine the user's blood pressure index. Therefore, system 400 may use a single wearable device 104-c to measure the time elapsed until the pulse wave reaches different tissue penetration depths in order to determine the blood pressure of user 102.

[0134] In some cases, the light emitted by the light-emitting components 410 (e.g., LEDs) of the wearable device 104-c may be measured by multiple photodetectors 415. In some cases, the light-emitting components 410 and photodetectors 415 may be arranged at different radial positions on the inner surface of the wearable device 104-c. For example, in some cases, multiple light-emitting components 410 and multiple PDs may be arranged around the inner surface of the wearable device 104-b in an alternating arrangement pattern (e.g., LED, PD, LED, PD) with regular or irregular spacing between each component. In other cases, multiple photodetectors 415 may be arranged adjacent to each other at the same or similar radial positions on the wearable device 104-c.

[0135] In some cases, measuring light using multiple photodetectors 415 (for example, multiple photodetectors 415 located at the same distance from a common light-emitting component 410) may allow the wearable device 104-c to determine the phase difference of the optical signals received by each photodetector 415. Such parallel measurement of light by multiple photodetectors 415 may enable more robust and reliable PPG data acquisition. For example, in some cases, the phase difference between light measured by multiple PD 315 may be used to determine the velocity of blood moving through blood vessels, which may then be used to further determine or estimate blood pressure.

[0136] As previously stated herein, aspects of this disclosure include the ability to use PPG data to identify pulse wave observation times, thereby enabling the determination of a user's blood pressure index using PPG data. In some implementations, the wearable device 104 may collect PPG data in the form of one or more groups of PPG pulse waves to measure the user's specific physiological parameters. However, not all PPG pulse waves exhibit the same morphological features or characteristics. In other words, PPG pulse waves can exhibit a variety of shapes and characteristics. That is, the morphological features of PPG pulse waves (e.g., PPG pulse wave amplitude, duration, gradient, curvature, and relationships between peaks) may vary from PPG pulse wave to PPG pulse wave, and some PPG pulse waves may inaccurately represent physiological measurements. Furthermore, or instead, factors such as light, pressure, user posture (e.g., whether the user is sitting or standing), or user hydration status (e.g., the user may have swollen fingers due to dehydration) may affect the accuracy of the PPG data. In particular, systems that use inaccurate PPG pulse waves or fail to consider additional factors that affect PPG data may yield unreliable physiological measurements. That is, multiple systems may benefit from one or more techniques for identifying PPG pulse waves that accurately represent the physiological indicators of one or more users.

[0137] Accordingly, in some implementations, the systems 100, 200, 300, and 400 of this disclosure may be configured to identify one or more "representative" (e.g., common, mean) PPG pulse waves that accurately represent the user's physiological indicators, and the identified representative PPG pulse waves may be used to determine the pulse wave observation time and / or blood pressure measurement. That is, the techniques described herein may be used to identify high-quality PPG pulse waves that accurately reflect the user's physiological indicators in order to determine blood pressure measurements.

[0138] To identify one or more PPG pulse waves that accurately represent a user's physiological indicators (for example, to identify PPG pulse waves used to determine pulse wave observation time and / or blood pressure indicators), the wearable device 104 may acquire PPG data from the user, including a first group of PPG pulse waves. In some aspects, the system may compare multiple morphological features from the first group of PPG pulse waves for each specific physiological measurement. Furthermore, based on the comparison of multiple morphological features of the first group of PPG pulse waves, the system may determine one or more PPG profiles (e.g., one or more representative PPG pulse waves, one or more common pulse wave templates) for each specific physiological indicator. That is, each of the one or more PPG profiles may include a group of multiple morphological value ranges for multiple morphological features. In some examples, each PPG profile may represent a representative (e.g., common, mean) pulse wave calculated from the first group of PPG pulse waves for each specific physiological measurement.

[0139] In addition, the system may acquire additional PPG data from the user via the wearable device 104. In some cases, the system may acquire additional PPG data from the user as a second group of PPG pulse waves. In some implementations, the system may determine that one or more PPG pulse waves from the second group of PPG pulse waves match one or more PPG profiles from the first group of PPG pulse waves. That is, the system may detect that multiple morphological feature values ​​of the second group of PPG pulse waves satisfy multiple morphological value ranges of one or more PPG profiles. In other words, the system may identify which PPG pulse waves from the second group of PPG pulse waves "match" a PPG profile.

[0140] Subsequently, the system may determine one or more physiological indicators associated with the user based on one or more PPG profiles from a first group of PPG pulse waves and one or more PPG pulse waves from a second group of PPG pulse waves that match. In other words, the system may perform physiological measurements of the user using PPG pulse waves that "match" the PPG profile (for example, the system may use "representative" PPG pulse waves). For example, the system / wearable device 104 may be configured to determine pulse wave observation time and, therefore, blood pressure measurement using PPG pulse waves that match the PPG profile.

[0141] Conversely, the system may detect that one or more PPG pulse waves from a second group of PPG pulse waves do not match one or more PPG profiles from the second group of PPG pulse waves, and may refrain from using that particular physiological indicator associated with the user, or may take this information into consideration. In other words, the system / wearable device may not utilize PPG pulse waves that do not match a PPG profile to determine pulse wave observation time and / or blood pressure measurements.

[0142] In some aspects, a wearable device may use the existing hardware features of the wearable device to identify one or more representative PPG pulse waves for each user. In some examples, the system may define one or more PPG pulse wave profiles (e.g., one or more PPG templates) that represent a user's typical PPG pulse waves. That is, the system may acquire one or more PPG pulse waves and compare each of them to one or more PPG pulse wave profiles. In such cases, the system may determine one or more PPG profiles by identifying common (e.g., average) values ​​(e.g., average length, amplitude, slope, etc.) of multiple PPG pulse waves. For example, the system may define one or more PPG pulse wave profiles based on common PPG pulse waves acquired from a user via a daytime calibration sequence. That is, the calibration sequence may be initiated to define a valid sample to determine which of the PPG pulse waves are suitable (e.g., reliable) for physiological measurement. In some cases, the system may utilize the changing correlation between different signal paths to find the optimal measurement time for PPG pulse waves.

[0143] In some implementations, the system may take user posture estimation into account and determine different groups of PPG profiles based on the user's different postures. For example, the system may detect user posture (e.g., the user may be standing, sitting, or lying down) that may affect the signal quality index of the PPG pulse wave. Thus, the system may use the PPG pulse wave profile, calibration sequence, and additional factors to select accurate PPG pulse waves with appropriate signal quality indexes that represent the user's physiological indicators (e.g., a first group of PPG profiles when the user is standing, and a second group of PPG profiles when the user is sitting).

[0144] Figure 5 shows an example of a timing diagram 500 that supports a technique for determining blood pressure based on the relative timing of pulse waves, according to the aspects of this disclosure. In some implementations, the timing diagram 500 may implement or be implemented by aspects of systems 100, 200, 300, and 400, as described with reference to Figures 1 to 4.

[0145] For example, timing diagram 500 may represent one or more cardiac measurements of a user, such as user 102, and the cardiac measurements are obtained using a wearable device (e.g., wearable device 104, blood pressure device, blood pressure monitor, blood pressure cuff, blood pressure monitor). In the following description of timing diagram 500, cardiac measurements may be taken in a different order than the exemplary order shown, or cardiac measurements may be taken in a different order or at different times. Some cardiac measurements may also be omitted from timing diagram 500, and other cardiac measurements may be added to timing diagram 500.

[0146] In the example of Figure 5, the timing diagram 500 may represent multiple cardiac measurements over a period of time. In some examples, the user may be equipped with one or more devices (e.g., one or more wearable devices 104, one or more blood pressure devices) to study the user's cardiac measurements. In some examples, the timing diagram 500 may represent multiple curves 505 as a graphic record of cardiac movement or function that can be used for the user's diagnosis. That is, the timing diagram 500 may be used to show cardiac time intervals that provide information about the user's left ventricular performance. For example, in the example of Figure 5, one or more devices may perform an ECG examination, in which electrical signals from the user's heart are checked for cardiac condition, and one or more pulse wave observation times may be monitored.

[0147] In some aspects, the timing diagram 500 may show an ECG curve 505-a with one or more pulse wave observation times, such as PTT and PAT, indicating the time elapsed for the pulse wave to reach different locations on the user's body. That is, PTT may indicate the time period during which the pulse wave travels from one arterial site to another (for example, the time difference between the arrival times of pulse waves at two peripheral site PPGs). In other examples, PAT may indicate the time interval during which the pulse wave travels from the user's heart to one or more distal locations on the body. That is, PAT may take PTT in addition to PEP, where PEP is the time period during which blood is not being pumped, in addition to the time required to convert electrical signals into mechanical pumping force and the isovolumetric contraction of the left ventricle to open the aortic valve of the user's heart. In some examples, PEP may affect the cardiac measurements shown in the timing diagram 500.

[0148] In addition, the timing diagram 500 may represent impedance electrocardiogram (ICG) measurements that measure cardiac function (e.g., cardiac output, cardiac index, stroke volume, and stroke volume index) as an ICG curve 505-b. That is, the ICG curve 505-b may represent the mechanical function of the heart, or it may measure the total conductivity of the chest, where the chest is the area of ​​the body between the user's neck and abdomen.

[0149] Furthermore, the timing diagram 500 may show a cardiac elasticity diagram (BCG) represented as a curve 505-c that measures the impact force generated by the heart. That is, the BCG curve 505-c may represent the downward movement of blood through the user's descending aorta. This downward movement of blood can produce an upward rebound that moves the user's body upward with each heartbeat. Therefore, the timing diagram 500 may include the BCG curve 505-c to show the mechanical vibrations caused by the user's cardiac activity.

[0150] In addition, timing diagram 500 may show a cardiac rhythm (PCG) measurement, represented as a curve 505-d for measuring heart sounds. In some examples, the PCG curve 505-d may represent sounds and murmurs produced by the closure of multiple heart valves. That is, the PCG curve 505-d may rhythmically represent two dominant sounds, such as S1 and S2. S1 may represent the closing of the atrioventricular valves (e.g., tricuspid valve, mitral valve) at the start of systole, systole represents the phase of the heartbeat when the myocardium contracts and pumps blood from the heart chambers into the arteries, and S2 may represent the closing of the aortic and pulmonary valves (e.g., semilunar valve) at the end of systole. Thus, timing diagram 500 may include a PCG curve 505-d to determine whether the user has a heart murmur that could affect the user's overall health.

[0151] In some aspects, the timing diagram 500 may include one or more PPG curves, such as PPG1 curve 505-e and PPG2 curve 505-f, which represent volume changes in the blood circulation of the user's cardiovascular system. In some examples, PPG1 curve 505-e and PPG2 curve 505-f may represent one or more pulse waves of the user and the respective times that elapse for one or more pulse waves to reach different locations. That is, PPG1 curve 505-e may represent a PPG pulse wave at a first location (e.g., the user's chest region, the user's first tissue layer), and PPG2 curve 505-f may represent a PPG pulse wave at a second location (e.g., the user's extremities, the user's second tissue layer). Thus, the timing diagram 500 may be represented by the time difference between the PPG pulse wave represented in PPG1 curve 505-e and the PPG pulse wave represented in PPG2 curve 505-f.

[0152] In some examples, the timing diagram 500 may show one or more tags (e.g., identifiers), such as TAG1 curves 505-g and TAG2 curves 505-h, which track myocardial motion. That is, the myocardium facilitates the contraction and relaxation of the heart wall in order to receive blood and pump it into the user's systemic circulation. That is, one or more tags may be defined when a QRS complex (e.g., a wave) is detected, and the QRS complex represents ventricular depolarization in the ECG. That is, one or more tags may be based on the ECG curve 505-a and may reflect the underlying myocardial deformation. Thus, one or more tags may indicate the viability of the user's cardiac muscle.

[0153] In some implementations, one or more devices may compare pulse timings associated with one or more curves 505 to obtain one or more pulse time intervals 510. In some examples, pulse timings may include pulse observation time, PTT, PAT, and / or PEP. That is, each of the pulse time intervals 510, e.g., pulse time interval 510-a, pulse time interval 510-b, pulse time interval 510-c, and additional pulse time intervals (not shown), may represent their respective timing intervals useful for determining cardiac measurements and subsequent user blood pressure.

[0154] Figure 6 shows an example of a GUI 600 supporting a technique for determining blood pressure based on the relative timing of pulse waves, according to aspects of the present disclosure. GUI 600 may implement or be implemented by aspects of System 100, System 200, System 300, System 400, Timing Diagram 500, or any combination thereof. For example, GUI 600 may be implemented for a user in a user device connected to a wearable device (e.g., a wearable ring device, watch, necklace, or any other wearable device), and may be an example of user 102, user device 106, and wearable device 104, as described with reference to Figures 1 to 5.

[0155] GUI 600 shows a set of application pages, including application page 605-a, application page 605-b, and application page 605, which may be displayed to the user (for example, user 102 and GUI 275 as described with reference to Figures 1-5) via GUI 600. In some examples, the user may open application page 605-a to view scores belonging to the user. For example, application page 605-a may display sleep scores, readiness scores, etc. In some examples, application page 605-a may display a blood pressure alert 610 that indicates an alert to the user. For example, the blood pressure alert 610 may indicate that a change in the user's blood pressure has been detected. That is, the user may select the user's blood pressure history 615. Furthermore, or alternatively, the user may decide that their blood pressure measurements may need to be recalibrated. That is, the user may have experienced changes that have affected their blood pressure indicators. For example, the user may have traveled to a higher altitude and is experiencing swelling of the extremities (e.g., fingers) due to dehydration. Furthermore, users may select Box 620 for blood pressure calibration to enable the wearable device to obtain accurate blood pressure indicators.

[0156] In some examples, the user may see the blood pressure history feature 615 and application page 605-b appear on the user's device. Application page 605-b may show blood pressure 625 taken on the day and at a specific (e.g., current) time. In some examples, blood pressure 625 may show several measurements, such as systolic blood pressure 630 measured from one or more arteries when the user's heart is beating, and diastolic blood pressure 635 measured from one or more arteries when the heart is between beats. In some examples, the blood pressure classification may include either normal blood pressure or hypertension. For the user, normal blood pressure may refer to a systolic blood pressure of less than 130 mmHg and a diastolic blood pressure of less than 80 mmHg. Alternatively, hypertension may refer to a systolic blood pressure of greater than 130 mmHg and a diastolic blood pressure of greater than 80 mmHg. In addition, pulse wave 640 may be displayed, representing a heart rate measurement (e.g., the number of times the user's heart beats per minute). Furthermore, a pulse wave of 640 can be calculated by subtracting the diastolic blood pressure of 635 from the systolic blood pressure of 625.

[0157] Furthermore, or alternatively, application page 605-b may display the user's blood pressure history 645 for a specific period. In the example in Figure 6, the blood pressure history 645 shows a night period on a particular date with two trend lines. That is, the blood pressure history 645 may show a baseline (e.g., normal, typical, trend) blood pressure index 650-a associated with the user and a blood pressure index 650-b for a night period on a particular date. That is, application page 605-b on the user device may graphically show a comparison between a blood pressure index 650-a representing the user's typical nighttime blood pressure trend and a blood pressure index 650-b representing the user's blood pressure trend for the last night period. That is, GUI 600 may display and / or show information associated with the difference between the baseline blood pressure index 650-a and the blood pressure index 650-b (e.g., your blood pressure is ±X compared to your mean blood pressure).

[0158] In some cases, GUI 600 may share information that could indicate whether a user has nocturnal hypertension based on a drop in pulse wave. For a user, a normal nocturnal blood pressure trend may show a blood pressure drop of approximately 10-15% lower than a typical daytime pulse wave. However, detecting a blood pressure change of more than 15% (e.g., a change in blood pressure based on absolute and additional values) may alert the user that they have elevated sodium, salt sensitivity, CKD, CHF, diabetes, structural vascular disease, insomnia, etc. That is, the user may look at a blood pressure history 645 over a period of time to determine whether the blood pressure index 650 could indicate a potential cardiovascular health risk.

[0159] In some examples, the blood pressure calibration 620 function and application page 605-c may appear on the user's device. In such examples, the user may select the blood pressure calibration 620 function and take a blood pressure test 655. That is, application page 605-c may indicate that the user may take a blood pressure test 655 and follow a set of instructions. For example, instruction box 660-a may indicate that the user applies pressure to the wearable device for a certain time interval (e.g., pressing the wearable device and pulling back a fist to apply pressure to the wearable ring), pauses (e.g., stopping), does not apply pressure to the ring, and reduces the pressure to a normative state, and applies pressure to the wearable device again for another time interval. Furthermore, the blood pressure test 655 may display two time interval boxes, such as a first time interval start box 660-b and a second time interval start box 660-c, which allow the user to start a time interval period for applying pressure to the wearable device. In other words, the Timer Countdown 660-d box may indicate a time period in seconds for the user to apply a first and second pressure, or a time period in seconds for the user to rest during the time interval. In some examples, the Blood Pressure Test 655 may allow a system having a single wearable device to monitor pulse wave observation times for different pulse waves at variable tissue penetration depths. As previously stated herein, by applying different pressures over different time intervals, the wearable device becomes capable of observing heart pulse waves at different tissue penetration depths, thereby enabling blood pressure measurement.

[0160] Figure 7 shows a block diagram 700 of a device 705 that supports a technique for determining blood pressure based on the relative timing of pulse waves, according to an aspect of this disclosure. Device 705 may be an example of an aspect of a wearable device as described herein. Device 705 may include an input module 710, an output module 715, and a wearable device manager 720. Device 705 may also include a processor. Each of these components may communicate with one another (for example, via one or more buses).

[0161] The wearable device manager 720, the input module 710, the output module 715, or various combinations thereof or various components thereof may be examples of means for performing various aspects of techniques for determining blood pressure based on the relative timing of pulse waves, as described herein. For example, the wearable device manager 720, the input module 710, the output module 715, or various combinations thereof or components thereof may support methods for performing one or more of the functions described herein.

[0162] In some examples, the wearable device manager 720, the input module 710, the output module 715, or various combinations or components thereof may be implemented in hardware (for example, in a communication management circuit). The hardware may include a processor, DSP, ASIC, FPGA or other programmable logic device, discrete gate or transistor logic, discrete hardware components, or any combination thereof, configured as a means for performing or otherwise supporting the functions described herein. In some examples, a processor and memory coupled to the processor may be configured to perform one or more of the functions described herein (for example, by the processor executing instructions stored in the memory).

[0163] Furthermore, or alternatively, in some examples, the wearable device manager 720, input module 710, output module 715, or various combinations or components thereof may be implemented in code executed by a processor (for example, as communication management software or firmware). When implemented in code executed by a processor, the functions of the wearable device manager 720, input module 710, output module 715, or various combinations or components thereof may be performed by a general-purpose processor, DSP, CPU, ASIC, FPGA, or any combination thereof or other programmable logic device (for example, configured as a means for performing the functions described herein, or otherwise supporting such means).

[0164] For example, the wearable device manager 720 may be configured as a means for acquiring first physiological data from a user via a first wearable device, or may support such means in other ways, the first physiological data representing a first pulse wave observation time of the user's heartbeat at a first physiological location. The wearable device manager 720 may be configured as a means for acquiring second physiological data from a user via a second wearable device, or may support such means, the second physiological data representing a second pulse wave observation time of the heartbeat, the user's additional heartbeat, or both, at a second physiological location. The wearable device manager 720 may be configured as a means for determining the pulse wave transmission time associated with the heartbeat, the additional heartbeat, or both, at least in part on a comparison of the first pulse wave observation time and the second pulse wave observation time. The wearable device manager 720 may be configured as a means for determining a user's blood pressure index at least in part on the pulse wave transmission time, or may support such means.

[0165] For example, the wearable device manager 720 may be configured as a means for transmitting light associated with one or more wavelengths using one or more light-emitting components, or may otherwise support such means. The wearable device manager 720 may be configured as a means for acquiring first physiological data from a user, at least in part on receiving light via one or more photodetectors, or may otherwise support such means, the first physiological data indicating a first pulse wave observation time of the user's heartbeat at a first tissue penetration depth. The wearable device manager 720 may be configured as a means for acquiring second physiological data from a user, at least in part on receiving light via one or more photodetectors, or may otherwise support such means, the second physiological data indicating a second pulse wave observation time of the heartbeat, an additional heartbeat of the user, or both, at a second tissue penetration depth. The wearable device manager 720 may be configured or supportive of means for determining pulse wave transmission time associated with a heart rate, additional heart rate, or both, at least in part, based on a comparison of a first pulse wave observation time and a second pulse wave observation time. The wearable device manager 720 may also be configured or supportive of means for determining a user's blood pressure index at least in part, based on pulse wave transmission time.

[0166] By including or configuring a wearable device manager 720 in accordance with the examples described herein, device 705 (for example, an input module 710, an output module 715, a wearable device manager 720, or a processor controlling a combination thereof or otherwise coupled with them) may support a technology for conveniently determining blood pressure for one or more users. That is, blood pressure may indicate the health of one or more users, and device 705 may enable one or more users to frequently monitor their health status and / or diseases without assistance from one or more healthcare professionals.

[0167] Figure 8 shows a block diagram 800 of device 805 supporting a technique for determining blood pressure based on the relative timing of pulse waves, according to an aspect of this disclosure. Device 805 may be an example of an aspect of device 705 or wearable device 115 as described herein. Device 805 may include an input module 810, an output module 815, and a wearable device manager 820. Device 805 may also include a processor. Each of these components may communicate with one another (for example, via one or more buses).

[0168] Device 805 or its various components may be examples of means for performing various aspects of techniques for determining blood pressure based on the relative timing of pulse waves, as described herein. For example, the wearable device manager 820 may include a first physiological data component 825, a second physiological data component 830, a pulse wave propagation time component 835, a blood pressure component 840, an optical component 845, a pulse wave transmission time component 850, or any combination thereof. The wearable device manager 820 may be an example of an aspect of the wearable device manager 720 as described herein. In some examples, the wearable device manager 820 or its various components may be configured to perform various operations (e.g., receiving, monitoring, transmitting) using or in other ways in cooperation with the input module 810, the output module 815, or both. For example, the wearable device manager 820 may receive information from the input module 810 and transmit information to the output module 815, or be integrated with the input module 810, the output module 815, or both to receive information, transmit information, or perform various other operations as described herein.

[0169] The first physiological data component 825 is configured as a means for acquiring first physiological data from the user via a first wearable device, or may otherwise support such means, the first physiological data representing a first pulse wave observation time of the user's heartbeat at a first physiological location. The second physiological data component 830 is configured as a means for acquiring second physiological data from the user via a second wearable device, or may support such means, the second physiological data representing a second pulse wave observation time of the heartbeat, the user's additional heartbeat, or both, at a second physiological location. The pulse wave propagation time component 835 is configured as a means for determining the pulse wave propagation time associated with the heartbeat, the additional heartbeat, or both, at least in part on a comparison of the first pulse wave observation time and the second pulse wave observation time, or may support such means. In some examples, the blood pressure component 940 is configured as a means for determining the user's blood pressure index at least in part on the pulse wave propagation time, or may support such means.

[0170] The optical component 845 is configured as a means for transmitting light associated with one or more wavelengths using one or more light-emitting components, or may otherwise support such means. The first physiological data component 825 is configured as a means for acquiring first physiological data from a user, at least in part on receiving light via one or more photodetectors, the first physiological data indicating a first pulse wave observation time of the user's heartbeat at a first tissue penetration depth. The second physiological data component 830 is configured as a means for acquiring second physiological data from a user, at least in part on receiving light via one or more photodetectors, the second physiological data indicating a second pulse wave observation time of the heartbeat, an additional heartbeat of the user, or both, at a second tissue penetration depth. The pulse wave transmission time component 850 is configured as a means for determining the pulse wave transmission time associated with the heartbeat, an additional heartbeat, or both, at least in part on comparing the first pulse wave observation time with the second pulse wave observation time. In some examples, the blood pressure component 940 may be configured as a means for determining a user's blood pressure index based at least partially on pulse wave transmission time, or may support such determination.

[0171] Figure 9 shows a block diagram 900 of a wearable device manager 920 that supports a technique for determining blood pressure based on the relative timing of pulse waves, as described herein. The wearable device manager 920 may be an example of an aspect of the wearable device manager 720, the wearable device manager 820, or both, as described herein. The wearable device manager 920, or its various components, may be an example of means for performing various aspects of the technique for determining blood pressure based on the relative timing of pulse waves, as described herein. For example, the wearable device manager 920 may include a first physiological data component 925, a second physiological data component 930, a pulse wave propagation time component 935, a blood pressure component 940, an optical component 945, a pulse wave propagation time component 950, a baseline blood pressure component 955, a blood pressure difference component 960, a user interface manager 965, a first pulse wave propagation time component 970, a second pulse wave propagation time component 975, or any combination thereof. Each of these components can communicate with one another directly or indirectly (for example, via one or more buses).

[0172] The first physiological data component 925 is configured as a means for acquiring first physiological data from the user via a first wearable device, or may otherwise support such means, the first physiological data representing the first pulse wave observation time of the user's heartbeat at a first physiological location. The second physiological data component 930 is configured as a means for acquiring second physiological data from the user via a second wearable device, or may support such means, the second physiological data representing the second pulse wave observation time of the heartbeat, the user's additional heartbeat, or both at a second physiological location. The pulse wave propagation time component 935 is configured as a means for determining the pulse wave propagation time associated with the heartbeat, the additional heartbeat, or both, at least in part on a comparison of the first pulse wave observation time and the second pulse wave observation time, or may support such means. The blood pressure component 940 is configured as a means for determining the user's blood pressure index at least in part on the pulse wave propagation time, or may support such means.

[0173] In some examples, a baseline blood pressure index associated with the user is determined. In some examples, the difference between the baseline blood pressure index and the current blood pressure index is determined. In some examples, information associated with the difference between the baseline blood pressure index and the current blood pressure index is displayed on the user device's GUI.

[0174] In some examples, pulse wave transmission time is determined as the time interval between the first pulse wave observation time and the second pulse wave observation time, and the blood pressure index is based at least partially on this time interval.

[0175] In some examples, the first physiological data includes first PPG data acquired via a first wearable device at a first physiological location. In some examples, the second physiological data includes second PPG data acquired via a second wearable device at a second physiological location.

[0176] In some examples, the first wearable device, the second wearable device, or both include a wearable ring device.

[0177] In some examples, the first physiological location includes a location close to the user's chest, and the second physiological location includes a location on the user's extremities.

[0178] In some examples, the first physiological data includes acceleration data, electrocardiogram data, or both. In some examples, the second physiological data includes PPG data.

[0179] In some examples, the first pulse wave duration of a heartbeat between the user's heart and a first physiological position is determined based at least partially on the first pulse wave observation time. In some examples, the second pulse wave duration of an additional heartbeat between the user's heart and a second physiological position is determined based at least partially on the second pulse wave observation time, and the blood pressure index is determined at least partially on a comparison of the first and second pulse wave durations.

[0180] In some examples, to support techniques for determining blood pressure based on the relative timing of pulse waves, the acceleration component 980 may be configured or support such means for selectively adjusting a blood pressure index based at least partially on acceleration data.

[0181] The optical component 945 is configured as a means for transmitting light associated with one or more wavelengths using one or more light-emitting components, or can otherwise support such means. In some examples, the first physiological data component 925 is configured as a means for acquiring first physiological data from a user, at least in part on receiving light via one or more photodetectors, the first physiological data indicating a first pulse wave observation time of the user's heartbeat at a first tissue penetration depth. In some examples, the second physiological data component 930 is configured as a means for acquiring second physiological data from a user, at least in part on receiving light via one or more photodetectors, the second physiological data indicating a second pulse wave observation time of the heartbeat, an additional heartbeat of the user, or both, at a second tissue penetration depth. The pulse wave transmission time component 950 may be configured or supportive of means for determining the pulse wave transmission time associated with a heartbeat, an additional heartbeat, or both, at least in part, based on a comparison of a first pulse wave observation time and a second pulse wave observation time. In some examples, the blood pressure component 940 may be configured or supportive of means for determining a user's blood pressure index at least in part based on the pulse wave transmission time.

[0182] In some examples, a baseline blood pressure index associated with the user is determined. In some examples, the difference between the baseline blood pressure index and the current blood pressure index is determined. In some examples, information associated with the difference between the baseline blood pressure index and the current blood pressure index is displayed on the user device's GUI.

[0183] In some examples, the first physiological data is acquired via a wearable device using first light associated with a first wavelength range configured to penetrate the user's tissue to a first tissue penetration depth. In some examples, the second physiological data is acquired via a wearable device using second light associated with a second wavelength range configured to penetrate the user's tissue to a second tissue penetration depth.

[0184] In some examples, the first physiological data is acquired during a first time interval associated with a first pressure applied between the wearable device and the user's tissue. In some examples, the second physiological data is acquired during a second time interval associated with a second pressure applied between the wearable device and the user's tissue.

[0185] In some examples, instructions are displayed on the user device's GUI for the user to apply a first pressure during a first time interval and a second pressure during a second time interval, and the acquisition of first physiological data, second physiological data, or both, is at least partially based on these instructions.

[0186] In some examples, the first physiological data includes PPG data. In some examples, the second physiological data includes pressure data.

[0187] In some examples, the first pulse wave duration of a heartbeat between the user's heart and a first tissue penetration depth is determined based at least partially on the first pulse wave observation time. In some examples, the second pulse wave duration of an additional heartbeat between the user's heart and a second tissue penetration depth is determined based at least partially on the second pulse wave observation time, and the blood pressure index is determined at least partially on a comparison of the first and second pulse wave durations.

[0188] In some examples, to support techniques for determining blood pressure based on the relative timing of pulse waves, the blood pressure component 940 may be configured or support such means for selectively adjusting the blood pressure index based at least partially on acceleration data.

[0189] In some examples, wearable devices include wearable ring devices.

[0190] Figure 10 shows a diagram of system 1000 including a device 1005 that supports a technique for determining blood pressure based on the relative timing of pulse waves, according to aspects of this disclosure. Device 1005 may be an example of, or include, the devices 705, 805, or components of the wearable device described herein. Device 1005 may include an example of the wearable device 104, as previously stated herein. Device 1005 may include components for bidirectional communication, including components for transmitting and receiving communications with user device 106 and server 110, such as a wearable device manager 1020, a communication module 1010, an antenna 1015, a sensor component 1025, a power module 1030, a memory 1035, a processor 1040, and a wireless device 1050. These components communicate electronically via one or more buses (e.g., bus 1045) or may be coupled (e.g., operably, communicatively, functionally, electronically, electrically).

[0191] For example, the wearable device manager 1020 may be configured as a means for acquiring first physiological data from a user via a first wearable device, or may support such means in other ways, wherein the first physiological data represents a first pulse wave observation time of the user's heartbeat at a first physiological location. The wearable device manager 1020 may be configured as a means for acquiring second physiological data from a user via a second wearable device, or may support such means, wherein the second physiological data represents a second pulse wave observation time of the heartbeat, the user's additional heartbeat, or both, at a second physiological location. The wearable device manager 1020 may be configured as a means for determining the pulse wave transmission time associated with the heartbeat, the additional heartbeat, or both, at least in part on a comparison of the first pulse wave observation time and the second pulse wave observation time. The wearable device manager 1020 may be configured as a means for determining a user's blood pressure index at least in part on the pulse wave transmission time, or may support such means.

[0192] For example, the wearable device manager 1020 may be configured as a means for transmitting light associated with one or more wavelengths using one or more light-emitting components, or may otherwise support such means. The wearable device manager 1020 may be configured as a means for acquiring first physiological data from a user, at least in part on receiving light via one or more photodetectors, or may otherwise support such means, the first physiological data indicating a first pulse wave observation time of the user's heartbeat at a first tissue penetration depth. The wearable device manager 1020 may be configured as a means for acquiring second physiological data from a user, at least in part on receiving light via one or more photodetectors, or may otherwise support such means, the second physiological data indicating a second pulse wave observation time of the heartbeat, an additional heartbeat of the user, or both, at a second tissue penetration depth. The wearable device manager 1020 may be configured or support a means for determining pulse wave transmission time associated with a heart rate, an additional heart rate, or both, at least in part, based on a comparison of a first pulse wave observation time and a second pulse wave observation time. The wearable device manager 1020 may also be configured or support a means for determining a user's blood pressure index at least in part, based on pulse wave transmission time.

[0193] By including or configuring a wearable device manager 1020 in accordance with the examples described herein, device 1005 may support a technology for conveniently determining blood pressure for one or more users. As described herein, device 1005 may improve the user experience by communicating blood pressure indicators to the user in a timely manner without requiring a visit to a healthcare professional for a blood pressure test.

[0194] The methods described above illustrate possible implementations; note that the operations and steps may be rearranged or, in some cases, modified, and other implementations are possible. Furthermore, aspects from two or more of the methods may be combined.

[0195] A method is described. The method may include: obtaining first physiological data from a user via a first wearable device, the first physiological data indicating a first pulse wave observation time of the user's heartbeat at a first physiological location; obtaining second physiological data from a user via a second wearable device, the second physiological data indicating a second pulse wave observation time of the heartbeat, the user's additional heartbeat, or both, at a second physiological location; determining the pulse wave conduction time associated with the heartbeat, the additional heartbeat, or both, at least in part on a comparison of the first pulse wave observation time and the second pulse wave observation time; and determining the user's blood pressure index, at least in part on the pulse wave conduction time.

[0196] An apparatus is described. The apparatus may include a processor, memory coupled to the processor, and instructions stored in the memory. Instructions may be executable by the processor to cause the apparatus to acquire first physiological data from a user via a first wearable device, the first physiological data indicating a first pulse wave observation time of the user's heartbeat at a first physiological location; to acquire second physiological data from a user via a second wearable device, the second physiological data indicating a second pulse wave observation time of the heartbeat, an additional heartbeat of the user, or both, at a second physiological location; to determine the pulse wave transmission time associated with the heartbeat, the additional heartbeat, or both, at least in part on a comparison of the first pulse wave observation time and the second pulse wave observation time; and to determine the user's blood pressure index, at least in part on the pulse wave transmission time.

[0197] Other devices are described. The devices may include means for acquiring first physiological data from a user via a first wearable device, wherein the first physiological data indicates a first pulse wave observation time of the user's heartbeat at a first physiological location; means for acquiring second physiological data from a user via a second wearable device, wherein the second physiological data indicates a second pulse wave observation time of the heartbeat, the user's additional heartbeat, or both, at a second physiological location; means for determining pulse wave transmission time associated with the heartbeat, the additional heartbeat, or both, at least in part on a comparison of the first pulse wave observation time and the second pulse wave observation time; and means for determining a blood pressure index of the user, at least in part on the pulse wave transmission time.

[0198] A non-temporary computer-readable medium for storing code is described. The code may include instructions executable by a processor to: obtain first physiological data from a user via a first wearable device, the first physiological data indicating a first pulse wave observation time of the user's heartbeat at a first physiological location; obtain second physiological data from a user via a second wearable device, the second physiological data indicating a second pulse wave observation time of the heartbeat, an additional heartbeat of the user, or both, at a second physiological location; determine the pulse wave conduction time associated with the heartbeat, the additional heartbeat, or both, at least in part on a comparison of the first pulse wave observation time and the second pulse wave observation time; and determine the user's blood pressure index, at least in part on the pulse wave conduction time.

[0199] Some examples of methods, apparatus, and non-temporary computer-readable media described herein may further include operations, features, means, or instructions for determining a baseline blood pressure index associated with a user, determining the difference between the baseline blood pressure index and the blood pressure index, and causing the GUI of the user device to display information associated with the difference between the baseline blood pressure index and the blood pressure index.

[0200] Some examples of methods, apparatus, and non-temporary computer-readable media described herein may further include operations, features, means, or instructions for determining pulse wave transmission time as the time interval between a first pulse wave observation time and a second pulse wave observation time, and the blood pressure index may be based at least in part on the time interval.

[0201] In some examples of the methods, apparatus, and non-temporary computer-readable media described herein, the first physiological data includes first PPG data acquired via a first wearable device at a first physiological location, and the second physiological data includes second PPG data acquired via a second wearable device at a second physiological location.

[0202] In some examples of the methods, apparatus, and non-temporary computer-readable media described herein, a first wearable device, a second wearable device, or both, includes a wearable ring device.

[0203] In some examples of the methods, apparatus, and non-temporary computer-readable media described herein, a first physiological location includes a location close to the user's chest, and a second physiological location includes a location on the user's extremities.

[0204] In some examples of the methods, apparatus, and non-temporary computer-readable media described herein, the first physiological data includes acceleration data, electrocardiogram data, or both, and the second physiological data includes PPG data.

[0205] Some examples of methods, apparatus, and non-temporary computer-readable media described herein may further include operations, features, means, or commands for determining a first pulse wave transmission time of a heartbeat between the user's heart and a first physiological position, based at least in part on a first pulse wave observation time, and for determining a second pulse wave transmission time of an additional heartbeat between the user's heart and a second physiological position, based at least in part on a second pulse wave observation time, wherein a blood pressure index may be based at least in part on a comparison of the first pulse wave transmission time and the second pulse wave transmission time.

[0206] In some examples of the methods, apparatus, and non-transient computer-readable media described herein, the methods, apparatus, and non-transient computer-readable media may include further actions, features, means, or instructions for selectively adjusting blood pressure indicators based at least in part on acceleration data.

[0207] A method is described. The method may include: obtaining first physiological data from a user, at least in part on transmitting light associated with one or more wavelengths using one or more light-emitting components and receiving the light through one or more photodetectors, wherein the first physiological data indicates a first pulse wave observation time of the user's heartbeat at a first tissue penetration depth; obtaining second physiological data from the user, at least in part on receiving the light through one or more photodetectors, wherein the second physiological data indicates a second pulse wave observation time of the heartbeat, an additional heartbeat of the user, or both, at a second tissue penetration depth; determining the pulse wave transmission time associated with the heartbeat, the additional heartbeat, or both, at least in part on comparing the first pulse wave observation time with the second pulse wave observation time; and determining the user's blood pressure index, at least in part on the pulse wave transmission time.

[0208] An apparatus is described. The apparatus may include a processor, memory coupled to the processor, and instructions stored in the memory. Instructions may be executable by the processor to cause the apparatus to transmit light associated with one or more wavelengths using one or more light-emitting components, and to obtain first physiological data from a user, at least in part on receiving the light through one or more photodetectors, wherein the first physiological data indicates a first pulse wave observation time of the user's heartbeat at a first tissue penetration depth; to obtain second physiological data from the user, at least in part on receiving the light through one or more photodetectors, wherein the second physiological data indicates a second pulse wave observation time of the heartbeat, an additional heartbeat of the user, or both, at a second tissue penetration depth; to determine the pulse wave transmission time associated with the heartbeat, the additional heartbeat, or both, at least in part on comparing the first pulse wave observation time with the second pulse wave observation time; and to determine the user's blood pressure index, at least in part on the pulse wave transmission time.

[0209] Other devices are described. The device may include means for transmitting light associated with one or more wavelengths using one or more light-emitting components; means for obtaining first physiological data from a user, at least in part on receiving light through one or more photodetectors, wherein the first physiological data indicates a first pulse wave observation time of the user's heartbeat at a first tissue penetration depth; means for obtaining second physiological data from a user, at least in part on receiving light through one or more photodetectors, wherein the second physiological data indicates a second pulse wave observation time of the heartbeat, an additional heartbeat of the user, or both, at a second tissue penetration depth; means for determining pulse wave transmission time associated with the heartbeat, the additional heartbeat, or both, at least in part on comparing the first pulse wave observation time with the second pulse wave observation time; and means for determining a blood pressure index of the user, at least in part on the pulse wave transmission time.

[0210] A non-temporary computer-readable medium for storing a code is described. The code may include instructions executable by a processor to obtain first physiological data from a user, at least in part on transmitting light associated with one or more wavelengths using one or more light-emitting components and receiving the light through one or more photodetectors, wherein the first physiological data indicates a first pulse wave observation time of the user's heartbeat at a first tissue penetration depth; obtain second physiological data from a user, at least in part on receiving the light through one or more photodetectors, wherein the second physiological data indicates a second pulse wave observation time of the heartbeat, an additional heartbeat of the user, or both, at a second tissue penetration depth; determine the pulse wave transmission time associated with the heartbeat, the additional heartbeat, or both, at least in part on comparing the first pulse wave observation time with the second pulse wave observation time; and determine the user's blood pressure index, at least in part on the pulse wave transmission time.

[0211] Some examples of methods, apparatus, and non-temporary computer-readable media described herein may further include operations, features, means, or instructions for determining a baseline blood pressure index associated with a user, determining the difference between the baseline blood pressure index and the blood pressure index, and causing the GUI of the user device to display information associated with the difference between the baseline blood pressure index and the blood pressure index.

[0212] In some examples of the methods, apparatus, and non-transient computer-readable media described herein, first physiological data may be acquired via a wearable device using first light associated with a first wavelength range configured to penetrate the user's tissue to a first tissue penetration depth, and second physiological data may be acquired via a wearable device using second light associated with a second wavelength range configured to penetrate the user's tissue to a second tissue penetration depth.

[0213] In some examples of the methods, apparatus, and non-temporary computer-readable media described herein, first physiological data may be acquired during a first time interval associated with a first pressure applied between the wearable device and the user's tissue, and second physiological data may be acquired during a second time interval associated with a second pressure applied between the wearable device and the user's tissue.

[0214] Some examples of methods, apparatus, and non-temporary computer-readable media described herein may further include actions, features, means, or instructions for displaying instructions on a GUI of a user device for applying a first pressure to a user during a first time interval and for applying a second pressure during a second time interval, and for obtaining first physiological data, obtaining second physiological data, or both, may be at least partially based on the instructions.

[0215] In some examples of the methods, apparatus, and non-temporary computer-readable media described herein, the first physiological data includes PPG data, and the second physiological data includes pressure data.

[0216] Some examples of the methods, apparatus, and non-temporary computer-readable media described herein may further include operations, features, means, or commands for determining a first pulse wave transmission time of a heartbeat between the user's heart and a first tissue penetration depth, based at least in part on a first pulse wave observation time, and for determining a second pulse wave transmission time of an additional heartbeat between the user's heart and a second tissue penetration depth, based at least in part on a second pulse wave observation time, wherein the blood pressure index may be based at least in part on a comparison of the first pulse wave transmission time and the second pulse wave transmission time.

[0217] In some examples of the methods, apparatus, and non-transient computer-readable media described herein, the methods, apparatus, and non-transient computer-readable media may include further actions, features, means, or instructions for selectively adjusting blood pressure indicators based at least in part on acceleration data.

[0218] In some examples of the methods, apparatus, and non-temporary computer-readable media described herein, wearable devices include wearable ring devices.

[0219] The descriptions provided herein with respect to the accompanying drawings describe exemplary configurations and do not necessarily represent all examples that may be implemented or that fall within the scope of the claims. The term “exemplary” as used herein means “acting as an example, case, or illustration,” and does not mean “preferred” or “advantageous over other examples.” Detailed descriptions may include specific details intended to give an understanding of the techniques described. However, these techniques may be implemented without these specific details. In some cases, well-known structures and devices are shown in the form of block diagrams to avoid obscuring the concepts of the examples described.

[0220] In the accompanying drawings, similar components or features may have the same reference label. Furthermore, different components of the same type may be distinguished by following the reference label with a dash and a second label that distinguishes similar components. Where only the first reference label is used herein, its description is applicable to any one of the similar components having the same first reference label, notwithstanding the second reference label.

[0221] The information and signals described herein may be represented using any of the following different techniques and methods. For example, the data, instructions, commands, information, signals, bits, symbols, and chips that may be referenced throughout the above description may be represented by voltage, electric current, electromagnetic waves, magnetic fields or magnetic particles, light fields or optical particles, or any combination thereof.

[0222] The various exemplary blocks and modules described in relation to the disclosure herein may be implemented using general-purpose processors, DSPs, ASICs, FPGAs or other programmable logic devices, discrete gate or transistor logic, discrete hardware components, or any combination thereof designed to perform the functions described herein. The general-purpose processor may be a microprocessor, but alternatively, the processor may be any conventional processor, controller, microcontroller, or state machine. The processor may also be implemented as a combination of computing devices (e.g., a combination of a DSP and a microprocessor, multiple microprocessors, one or more microprocessors working with a DSP core, or any other such configuration).

[0223] The functions described herein may be implemented in hardware, software executed by a processor, firmware, or any combination thereof. When implemented in software executed by a processor, the functions may be stored or transmitted as one or more instructions or codes on a computer-readable medium. Other examples and implementations are within the scope of this disclosure and the accompanying claims. For example, by the nature of the software, the functions described above may be implemented using software executed by a processor, hardware, firmware, hardwiring, or any combination thereof. Features implementing the functions may also be physically located in various locations, including being distributed so that parts of the functions are implemented in different physical locations. Furthermore, as used herein, including in the claims, "or" in a list of items (e.g., a list of items ending with a phrase such as "at least one of" or "one or more of") indicates an inclusive list, such as a list of at least one of A, B, or C meaning A or B or C or AB or AC or BC or ABC (i.e., A and B and C). Also, as used herein, the phrase "based on" should not be interpreted as a reference to a limited set of conditions. For example, an exemplary step described as “based on Condition A” may be based on both Condition A and Condition B without departing from the scope of this disclosure. In other words, as used herein, the phrase “based on” shall be construed in the same way as the phrase “based at least in part on.”

[0224] Computer-readable media include both non-temporary computer storage media and communication media, including any media that facilitates the transfer of computer programs from one location to another. Non-temporary storage media can be any available media that can be accessed by a general-purpose or dedicated computer. Examples, but not limitations, of non-temporary computer-readable media may include RAM, ROM, electrically erasable programmable ROM (EEPROM®), compact disk (CD) ROM or other optical disk storage, magnetic disk storage or other magnetic storage devices, or any other non-temporary media that can be used to carry or store desired program code means in the form of instructions or data structures, and can be accessed by a general-purpose or dedicated computer or general-purpose or dedicated processor. Any connection is also appropriately referred to as computer-readable media. For example, if software is transmitted from a website, server, or other remote source using coaxial cable, fiber optic cable, twisted pair, digital subscriber line (DSL), or wireless technologies such as infrared, radio, and microwave, then coaxial cable, fiber optic cable, twisted pair, DSL, or wireless technologies such as infrared, radio, and microwave are included in the definition of media. As used herein, the terms "disk" and "disc" include CDs, laserdiscs, optical discs, digital multipurpose discs (DVDs), floppy disks (registered trademark), and Blu-ray discs, where a "disk" typically reproduces data magnetically, and a "disc" reproduces data optically using a laser. Combinations of the above also fall within the range of computer-readable media.

[0225] The descriptions herein are provided to enable those skilled in the art to create or use this disclosure. Various modifications to this disclosure will be readily apparent to those skilled in the art, and the general principles defined herein may be applied to other variations without departing from the scope of this disclosure. Accordingly, this disclosure is not limited to the examples and designs described herein and should be given the broadest scope that corresponds to the principles and novel features disclosed herein.

Claims

1. A system for measuring blood pressure, A first wearable device in a first physiological position on the user's body, A second wearable device located at a second physiological position on the user's body, The first wearable device and the second wearable device include one or more processors communicably coupled to the first wearable device, the one or more processors are The method involves obtaining first physiological data from the user via the first wearable device, wherein the first physiological data indicates the first pulse wave observation time of the user's heart rate at the first physiological location. Acquiring second physiological data from the user via the second wearable device, wherein the second physiological data indicates the second pulse wave observation time of the heart rate, the user's additional heart rate, or both, at the second physiological location. Determining the pulse wave transmission time associated with the heartbeat, the additional heartbeat, or both, at least in part, based on a comparison of the first pulse wave observation time and the second pulse wave observation time. A system configured to determine the user's blood pressure index based at least partially on the pulse wave transmission time.

2. The one or more processors mentioned above are To determine the baseline blood pressure index associated with the user, To determine the difference between the baseline blood pressure index and the blood pressure index, The system according to claim 1, further configured to display information related to the difference between the baseline blood pressure index and the blood pressure index on the graphical user interface of a user device.

3. The one or more processors mentioned above are The system according to claim 1, further configured to determine the pulse wave transmission time as the time interval between the first pulse wave observation time and the second pulse wave observation time, wherein the blood pressure index is at least partially based on the time interval.

4. The system according to claim 1, wherein the first physiological data includes first photoplethysmography (PPG) data acquired via the first wearable device at the first physiological location, and the second physiological data includes second PPG data acquired via the second wearable device at the second physiological location.

5. The system according to claim 1, wherein the first wearable device, the second wearable device, or both include a wearable ring device.

6. The system according to claim 1, wherein the first physiological location includes a location close to the user's chest, and the second physiological location includes a location on the user's extremities.

7. The system according to claim 6, wherein the first physiological data includes acceleration data, electrocardiogram data, or both, and the second physiological data includes photoplethysmography (PPG) data.

8. In order to determine the pulse wave transmission time, one or more processors Based at least partially on the first pulse wave observation time, the first pulse wave transmission time of the heartbeat between the user's heart and the first physiological position is determined. The system according to claim 1, configured to determine a second pulse wave transmission time of the additional heartbeat between the user's heart and the second physiological position, based at least in part on the second pulse wave observation time, wherein the blood pressure index is based at least in part on a comparison of the first pulse wave transmission time and the second pulse wave transmission time.

9. The first physiological data, the second physiological data, or both further include acceleration data associated with the user's movement, and the one or more processors The system according to claim 1, further configured to selectively adjust the blood pressure index based at least partially on the acceleration data.

10. A wearable device for measuring blood pressure, One or more light-emitting elements, One or more photodetectors configured to receive light emitted by one or more light-emitting components, The controller comprises one or more light-emitting components and one or more photodetectors, wherein the controller is, Using the one or more light-emitting components, transmit light associated with one or more wavelengths, Obtaining first physiological data from a user, at least in part, based on receiving the light through one or more photodetectors, wherein the first physiological data indicates the first pulse wave observation time of the user's heartbeat at a first tissue penetration depth. Obtaining second physiological data from the user, at least in part, based on receiving the light through one or more photodetectors, wherein the second physiological data indicates a second pulse wave observation time of the heart rate, the user's additional heart rate, or both, at a second tissue penetration depth. Determining the pulse wave transmission time associated with the heartbeat, the additional heartbeat, or both, at least in part, based on a comparison of the first pulse wave observation time and the second pulse wave observation time. A wearable device configured to determine the user's blood pressure index based at least partially on the pulse wave transmission time.

11. The aforementioned controller, To determine the baseline blood pressure index associated with the user, To determine the difference between the baseline blood pressure index and the blood pressure index, A wearable device according to claim 10, configured to display information related to the difference between the baseline blood pressure index and the blood pressure index on the graphical user interface of the user device.

12. The first physiological data is acquired via the wearable device using first light associated with a first wavelength range configured to penetrate the user's tissue to a first tissue penetration depth. The second physiological data is acquired via the wearable device using a second light associated with a second wavelength range configured to penetrate the user's tissue to a second tissue penetration depth. The wearable device according to claim 10.

13. The first physiological data is acquired during a first time interval associated with a first pressure applied between the wearable device and the user's tissue. The second physiological data is acquired during a second time interval associated with a second pressure applied between the wearable device and the user's tissue. The wearable device according to claim 10.

14. The aforementioned controller, Instructions to the user for applying the first pressure during the first time interval and for applying the second pressure during the second time interval are displayed on the graphical user interface of the user device, and the acquisition of the first physiological data, the acquisition of the second physiological data, or both are at least partially based on the instructions. The wearable device according to claim 13.

15. The wearable device according to claim 10, wherein the first physiological data includes photoplethysmography (PPG) data, and the second physiological data includes pressure data.

16. In order to determine the pulse wave transmission time, the controller, Based at least partially on the first pulse wave observation time, the first pulse wave transmission time of the heartbeat between the user's heart and the first tissue penetration depth is determined, The wearable device according to claim 10, configured to determine a second pulse wave transmission time of the additional heartbeat between the user's heart and the second tissue penetration depth, based at least in part on the second pulse wave observation time, wherein the blood pressure index is based at least in part on a comparison of the first pulse wave transmission time and the second pulse wave transmission time.

17. The first physiological data, the second physiological data, or both, further include acceleration data associated with the user's movement, and the controller, The wearable device according to claim 10, configured to selectively adjust the blood pressure index based at least partially on the acceleration data.

18. The wearable device according to claim 10, wherein the wearable device includes a wearable ring device.

19. A method for measuring blood pressure, The method involves acquiring first physiological data from a user via a first wearable device at a first physiological location on the user's body, wherein the first physiological data indicates the first pulse wave observation time of the user's heart rate at the first physiological location. The method involves acquiring second physiological data from the user via a second wearable device at a second physiological location on the user's body, wherein the second physiological data indicates the second pulse wave observation time of the heart rate, the user's additional heart rate, or both, at the second physiological location. Determining the pulse wave transmission time associated with the heartbeat, the additional heartbeat, or both, at least in part, based on a comparison of the first pulse wave observation time and the second pulse wave observation time. A method comprising determining the user's blood pressure index based at least in part on the pulse wave transmission time.

20. To determine the baseline blood pressure index associated with the user, To determine the difference between the baseline blood pressure index and the blood pressure index, The graphical user interface of the user device displays information associated with the difference between the baseline blood pressure index and the blood pressure index, The method according to claim 19, further comprising:

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