TECHNIQUES FOR IDENTIFYING REPRESENTATIVE PPG PULSES

Methods, systems, and devices for identifying representative photoplethysmogram (PPG) pulses are described. A method may include acquiring a first set of PPG pulses from a user via a wearable device. The method may include comparing a set of morphological features of the first set of PPG pulses, and determining one or more PPG profiles for the user, where the one or more PPG profiles each include a set of morphological value ranges for the set of morphological features. The method may include acquiring a second set of PPG pulses from the user via the wearable device, and determining that one or more PPG pulses from the second set of PPG pulses match the one or more PPG profiles. The method may include determining one or more physiological metrics associated with the user based on the one or more PPG pulses matching the one or more PPG profiles.

FIELD OF TECHNOLOGY

The following relates to wearable devices and data processing, including techniques for identifying representative photoplethysmogram (PPG) pulses.

BACKGROUND

Some wearable devices (e.g., wearable rings, wearable watches or bracelets, or the like) may be configured to collect photoplethysmogram (PPG) data from users. In some examples, the PPG data may indicate physiological metrics (e.g., measurements) for a user, such as metrics related to cardiac output (e.g., heart rate, heart rate variability (HRV), blood pressure, oxygen levels (e.g., SpO2), or the like. However, some of the PPG pulses used to measure a specific physiological feature may vary in morphology (e.g., magnitude of pulses, timing of pulses, shape of pulses) and some of the PPG pulses may inaccurately represent a physiological measurement of the user. In some implementations, a system that uses the inaccurate PPG pulses or fails to consider additional factors that affect the PPG data may output unreliable physiological metrics of the user.

DETAILED DESCRIPTION

Some wearable devices may be configured to utilize light to acquire photoplethysmogram (PPG) data from users via wearable devices (e.g., wearable ring devices, watches or bracelets, or the like). In some examples, the PPG data may indicate physiological metrics (e.g., measurements, parameters) of a user, such as a heart rate metric, a heart rate variability (HRV) metric, a blood oxygen saturation metric, a blood pressure metric, an arterial reactivity metric, or the like. In some implementations, a wearable device may collect the PPG data in the form of one or more sets of PPG pulses to measure specific physiological parameters of the user.

However, not all PPG pulses may exhibit the same morphological features or characteristics. In other words, PPG pulses may exhibit varying shapes and characteristics. That is, morphological features of PPG pulses (e.g., PPG pulse amplitude, duration, slope, curvature, relationships between peaks) may vary from one PPG pulse to the next, and some of the PPG pulses may inaccurately represent a physiological measurement. Additionally, or alternatively, factors such as light, pressure, a posture of the user (e.g., the user is sitting or standing), or a hydration of the user (e.g., the user may have swollen fingers due to lack of hydration) may affect the accuracy of the PPG data. In particular, a system that uses the inaccurate PPG pulses or fails to account for additional factors that affect the PPG data may result in unreliable physiological measurements. That is, multiple systems may benefit from one or more techniques for identifying PPG pulses that accurately represent the physiological metrics of one or more users.

As described herein, a system may use one or more techniques to identify one or more representative (e.g., common, average) PPG pulses that accurately represent the physiological metrics of the user. That is, the one or more techniques may be used to identify the PPG pulses that are of high quality and accurately reflect physiological metrics of the user. To identify the one or more PPG pulses that accurately represent the physiological metrics of the user, the wearable device may acquire PPG data that includes a first set of PPG pulses from the user. In some aspects, the system may compare multiple morphological features from the first set of PPG pulses for each specific physiological measurement. Further, the system may determine one or more PPG profiles (e.g., one or more representative PPG pulses, one or more common pulse templates) for each specific physiological metric based on the comparison of the multiple morphological features of the first set of PPG pulses. That is, each of the one or more PPG profiles may include a set of multiple morphological value ranges for the multiple morphological features. In some examples, each of the PPG profiles may represent a representative (e.g., common, average) pulse calculated from the first set of PPG pulses for each specific physiological measurement.

In addition, the system may acquire additional PPG data from the user via the wearable device. In some cases, the system may acquire the additional PPG data from the user as a second set of PPG pulses. In some implementations, the system may determine that one or more PPG pulses from the second set of PPG pulses match the one or more PPG profiles from the first set of PPG pulses. That is, the system may detect that multiple morphological feature values of the second set of PPG pulses satisfy the multiple morphological value ranges of the one or more PPG profiles. In other words, the system may identify which PPG pulses of the second set of PPG pulses “match” the PPG profiles.

Subsequently, the system may determine one or more physiological metrics associated with the user based on the one or more PPG pulses from the second set of PPG pulses matching the one or more PPG profiles from the first set of PPG pulses. Stated differently, the system may utilize the PPG pulses that “match” the PPG profiles (e.g., the system may utilize “representative” PPG pulses) to perform physiological measurements for the user. Alternatively, the system may detect that the one or more PPG pulses from the second set of PPG pulses fails to match the one or more PPG profiles from the second set of PPG pulses and may refrain from using that specific physiological metric associated with the user or otherwise take this information into account.

In some aspects, the wearable device may identify the one or more representative PPG pulses for each user using the existing hardware features of the wearable device. In some examples, the system may define the one or more PPG pulse profiles (e.g., one or more PPG templates) that represent common PPG pulses of the user. That is, the system may acquire one or more PPG pulses and may compare each of the PPG pulses to each other to determine the one or more PPG pulse profiles. In such cases, the system may determine the one or more PPG profiles by identifying common (e.g., average) values (e.g., average length, amplitude, slope, or the like) of the multiple PPG pulses. For example, the system may define one or more PPG pulse profiles based on common PPG pulses acquired from the user via a day-time calibration sequence. That is, the calibration sequence may be initiated to define valid samples to determine which of the PPG pulses are suitable (e.g., reliable) for performing physiological measurements. In some cases, the system may utilize a changing correlation between different signal paths to find an optimal measurement time for the PPG pulses.

In some implementations, the system may account for posture estimation of the user, and may determine different sets of PPG profiles based on different postures of the user. For example, the system may detect the posture of the user (e.g., the user may be standing, sitting, lying down, or the like) which may affect the signal quality metrics of the PPG pulses. As such, the system may use the PPG pulse profiles, the calibration sequence, and additional factors to select accurate PPG pulses with appropriate signal quality metrics that represent the physiological metrics of the user (e.g., first set of PPG profiles for when the user is standing, and second set of PPG profiles for when the user is sitting).

Aspects of the disclosure are initially described in the context of systems supporting physiological data collection from users via wearable devices. Aspects of the disclosure are further illustrated by and described with reference to apparatus diagrams, system diagrams, and flowcharts that relate to techniques for identifying representative PPG pulses.

FIG.1illustrates an example of a system100that supports techniques for identifying representative PPG pulses in accordance with aspects of the present disclosure. The system100includes a plurality of electronic devices (e.g., wearable devices104, user devices106) that may be worn and/or operated by one or more users102. The system100further includes a network108and one or more servers110.

The electronic devices may include any electronic devices known in the art, including wearable devices104(e.g., ring wearable devices, watch wearable devices, etc.), user devices106(e.g., smartphones, laptops, tablets). The electronic devices associated with the respective users102may include one or more of the following functionalities: 1) measuring physiological data, 2) storing the measured data, 3) processing the data, 4) providing outputs (e.g., via GUIs) to a user102based on the processed data, and 5) communicating data with one another and/or other computing devices. Different electronic devices may perform one or more of the functionalities.

Example wearable devices104may include wearable computing devices, such as a ring computing device (hereinafter “ring”) configured to be worn on a user's102finger, a wrist computing device (e.g., a smart watch, fitness band, or bracelet) configured to be worn on a user's102wrist, and/or a head mounted computing device (e.g., glasses/goggles). Wearable devices104may also include bands, straps (e.g., flexible or inflexible bands or straps), stick-on sensors, and the like, that may be positioned in other locations, such as bands around the head (e.g., a forehead headband), arm (e.g., a forearm band and/or bicep band), and/or leg (e.g., a thigh or calf band), behind the ear, under the armpit, and the like. Wearable devices104may also be attached to, or included in, articles of clothing. For example, wearable devices104may be included in pockets and/or pouches on clothing. As another example, wearable device104may be clipped and/or pinned to clothing, or may otherwise be maintained within the vicinity of the user102. Example articles of clothing may include, but are not limited to, hats, shirts, gloves, pants, socks, outerwear (e.g., jackets), and undergarments. In some implementations, wearable devices104may be included with other types of devices such as training/sporting devices that are used during physical activity. For example, wearable devices104may be attached to, or included in, a bicycle, skis, a tennis racket, a golf club, and/or training weights.

Much of the present disclosure may be described in the context of a ring wearable device104. Accordingly, the terms “ring104,” “wearable device104,” and like terms, may be used interchangeably, unless noted otherwise herein. However, the use of the term “ring104” is not to be regarded as limiting, as it is contemplated herein that aspects of the present disclosure may be performed using other wearable devices (e.g., watch wearable devices, necklace wearable device, bracelet wearable devices, earring wearable devices, anklet wearable devices, and the like).

In some aspects, user devices106may include handheld mobile computing devices, such as smartphones and tablet computing devices. User devices106may also include personal computers, such as laptop and desktop computing devices. Other example user devices106may include server computing devices that may communicate with other electronic devices (e.g., via the Internet). In some implementations, computing devices 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 cardioverter defibrillators. Other example user devices106may include home computing devices, such as internet of things (IoT) devices (e.g., IoT devices), smart televisions, smart speakers, smart displays (e.g., video call displays), hubs (e.g., wireless communication hubs), security systems, smart appliances (e.g., thermostats and refrigerators), and fitness equipment.

Some electronic devices (e.g., wearable devices104, user devices106) may measure physiological parameters of respective users102, such as photoplethysmography waveforms, continuous skin temperature, a pulse waveform, respiration rate, heart rate, HRV, actigraphy, galvanic skin response, pulse oximetry, 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 device104), mobile device application, or a server computing device may process received physiological data that was measured by other devices.

In some implementations, a user102may operate, or may 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, a user102may have a ring (e.g., wearable device104) that measures physiological parameters. The user102may also have, or be associated with, a user device106(e.g., mobile device, smartphone), where the wearable device104and the user device106are communicatively coupled to one another. In some cases, the user device106may receive data from the wearable device104and perform some/all of the calculations described herein. In some implementations, the user device106may also measure physiological parameters described herein, such as motion/activity parameters.

For example, as illustrated inFIG.1, a first user102-a(User 1) may operate, or may be associated with, a wearable device104-a(e.g., ring104-a) and a user device106-athat may operate as described herein. In this example, the user device106-aassociated with user102-amay process/store physiological parameters measured by the ring104-a.Comparatively, a second user102-b(User 2) may be associated with a ring104-b,a watch wearable device104-c(e.g., watch104-c), and a user device106-b,where the user device106-bassociated with user102-bmay process/store physiological parameters measured by the ring104-band/or the watch104-c.Moreover, an nth user102-n(User N) may be associated with an arrangement of electronic devices described herein (e.g., ring104-n,user device106-n). In some aspects, wearable devices104(e.g., rings104, watches104) and other electronic devices may be communicatively coupled to the user devices106of the respective users102via Bluetooth, Wi-Fi, and other wireless protocols.

In some implementations, the rings104(e.g., wearable devices104) of the system100may be configured to collect physiological data from the respective users102based on arterial blood flow within the user's finger. In particular, a ring104may utilize one or more light-emitting components, such as LEDs (e.g., red LEDs, green LEDs) that emit light on the palm-side of a user's finger to collect physiological data based on arterial blood flow within the user's finger. In general, the terms light-emitting components, light-emitting elements, and like terms, may include, but are not limited to, LEDs, micro LEDs, mini LEDs, laser diodes (LDs) (e.g., vertical cavity surface-emitting lasers (VCSELs), and the like.

In some cases, the system100may be configured to collect physiological data from the respective users102based on blood flow diffused into a microvascular bed of skin with capillaries and arterioles. For example, the system100may collect PPG data based on a measured amount of blood diffused into the microvascular system of capillaries and arterioles. In some implementations, the ring104may acquire the physiological data using a combination of both green and red LEDs. The physiological data may include any physiological data known in the art including, but not limited to, temperature data, accelerometer data (e.g., movement/motion data), heart rate data, HRV data, blood oxygen level data, or any combination thereof.

The use of both green and red LEDs may provide several advantages over other solutions, as red and green LEDs have been found to have their own distinct advantages when acquiring physiological data under different conditions (e.g., light/dark, active/inactive) and via different parts of the body, and the like. For example, green LEDs have been found to exhibit better performance during exercise. Moreover, using multiple LEDs (e.g., green and red LEDs) distributed around the ring104has been found to exhibit superior performance as compared to wearable devices that utilize LEDs that are positioned close to one another, such as within a watch wearable device. Furthermore, the blood vessels in the finger (e.g., arteries, capillaries) are more accessible via LEDs as compared to blood vessels in the wrist. In particular, arteries in the wrist are positioned on the bottom of the wrist (e.g., palm-side of the wrist), meaning only capillaries are accessible on the top of the wrist (e.g., back of hand side of the wrist), where wearable watch devices and similar devices are typically worn. As such, utilizing LEDs and other sensors within a ring104has been found to exhibit superior performance as compared to wearable devices worn on the wrist, as the ring104may have greater access to arteries (as compared to capillaries), thereby resulting in stronger signals and more valuable physiological data.

The electronic devices of the system100(e.g., user devices106, wearable devices104) may be communicatively coupled to one or more servers110via wired or wireless communication protocols. For example, as shown inFIG.1, the electronic devices (e.g., user devices106) may be communicatively coupled to one or more servers110via a network108. The network108may implement transfer control protocol and internet protocol (TCP/IP), such as the Internet, or may implement other network108protocols. Network connections between the network108and the respective electronic devices may facilitate transport of data via email, web, text messages, mail, or any other appropriate form of interaction within a computer network108. For example, in some implementations, the ring104-aassociated with the first user102-amay be communicatively coupled to the user device106-a,where the user device106-ais communicatively coupled to the servers110via the network108. In additional or alternative cases, wearable devices104(e.g., rings104, watches104) may be directly communicatively coupled to the network108.

The system100may offer an on-demand database service between the user devices106and the one or more servers110. In some cases, the servers110may receive data from the user devices106via the network108, and may store and analyze the data. Similarly, the servers110may provide data to the user devices106via the network108. In some cases, the servers110may be located at one or more data centers. The servers110may be used for data storage, management, and processing. In some implementations, the servers110may provide a web-based interface to the user device106via web browsers.

In some aspects, the system100may detect periods of time that a user102is asleep, and classify periods of time that the user102is asleep into one or more sleep stages (e.g., sleep stage classification). For example, as shown inFIG.1, User102-amay be associated with a wearable device104-a(e.g., ring104-a) and a user device106-a.In this example, the ring104-amay collect physiological data associated with the user102-a,including temperature, heart rate, HRV, respiratory rate, and the like. In some aspects, data collected by the ring104-amay be input to a machine learning classifier, where the machine learning classifier is configured to determine periods of time that the user102-ais (or was) asleep. Moreover, the machine learning classifier may be configured to classify periods of time into different sleep stages, including an awake sleep stage, a rapid eye movement (REM) sleep stage, a light sleep stage (non-REM (NREM)), and a deep sleep stage (NREM). In some aspects, the classified sleep stages may be displayed to the user102-avia a GUI of the user device106-a.Sleep stage classification may be used to provide feedback to a user102-aregarding the user's sleeping patterns, such as recommended bedtimes, recommended wake-up times, and the like. Moreover, in some implementations, sleep stage classification techniques described herein may be used to calculate scores for the respective user, such as Sleep Scores, Readiness Scores, and the like.

In some aspects, the system100may utilize circadian rhythm-derived features to further improve physiological data collection, 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, that repeats approximately every 24 hours. In this regard, techniques described herein may utilize circadian rhythm adjustment models to improve physiological data collection, 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 the user102-avia the wearable device104-a.In this example, the circadian rhythm adjustment model may be configured to “weight.” or adjust, physiological data collected throughout a user's natural, approximately 24-hour circadian rhythm. In some implementations, the system may initially start with a “baseline” circadian rhythm adjustment model, and may modify the baseline model using physiological data collected from each user102to generate tailored, individualized circadian rhythm adjustment models that are specific to each respective user102.

In some aspects, the system100may utilize other biological rhythms to further improve physiological data collection, analysis, and processing by phase of these other rhythms. For example, if a weekly rhythm is detected within an individual's baseline data, then the model may be configured to adjust “weights” of data by day of the week. Biological rhythms that may require adjustment to the model by this method include: 1) ultradian (faster than a day rhythms, including sleep cycles in a sleep state, and oscillations from less than an hour to several hours periodicity in the measured physiological variables during wake state; 2) circadian rhythms; 3) non-endogenous daily rhythms shown to be imposed on top of circadian rhythms, as in work schedules; 4) weekly rhythms, or other artificial time periodicities exogenously imposed (e.g., in a hypothetical culture with 12 day “weeks,” 12 day rhythms could be used); 5) multi-day ovarian rhythms in women and spermatogenesis rhythms in men; 6) lunar rhythms (relevant for individuals living with low or no artificial lights); and 7) seasonal rhythms.

The biological rhythms are not always stationary rhythms. For example, many women experience variability in ovarian cycle length across cycles, and ultradian rhythms are not expected to occur at exactly the same time or periodicity across days even within a user. As such, signal processing techniques sufficient to quantify the frequency composition while preserving temporal resolution of these rhythms in physiological data may be used to improve detection of these rhythms, to assign phase of each rhythm to each moment in time measured, and to thereby modify adjustment models and comparisons of time intervals. The biological rhythm-adjustment models and parameters can be added in linear or non-linear combinations as appropriate to more accurately capture the dynamic physiological baselines of an individual or group of individuals.

In some aspects, the respective devices of the system100may support techniques for identifying one or more representative (e.g., common, average) PPG pulses that accurately represents the physiological metrics (e.g., measurements, parameters) of the user. By identifying “representative” PPG pulses, techniques described herein may enable wearable devices to select PPG pulses that will result in high-quality measurements (e.g., physiological metrics). In some examples, the physiological metrics of a user that may be determined using PPG pulses may include a heart rate metric, an HRV metric, a blood oxygen saturation metric, a blood pressure metric, an arterial reactivity metric, or the like.

To identify the one or more PPG pulses that accurately represent the physiological metrics of the user, the wearable device104may acquire PPG data that includes a first set of PPG pulses from the user102. In some aspects, the system100may compare multiple morphological features from the first set of PPG pulses. For instance, the system100may compare morphological features such as amplitudes of PPG pulses, time durations of a set of PPG pulses, slopes (e.g., first derivatives) of a set of PPG pulses, curvatures (e.g., second derivatives) of a set of PPG pulses, relationships between peaks (e.g., systolic versus diastolic) of PPG pulses, or the like. Further, the system100may determine one or more PPG profiles (e.g., one or more representative PPG pulses, one or more common pulse templates) for the specific physiological metric based on the comparison of the multiple morphological features of the first set of PPG pulses. That is, each of the one or more PPG profiles may include a set of multiple morphological value ranges for the multiple morphological features. In some examples, each of the PPG profiles may represent a representative (e.g., common, average) pulse calculated from the first set of PPG pulses for the specific physiological measurement.

In addition, the system100may acquire additional PPG data from the user102via the wearable device104. In some cases, the system100may acquire the additional PPG data from the user102as a second set of PPG pulses. In some implementations, the system100may determine that one or more PPG pulses from the second set of PPG pulses match the one or more PPG profiles from the first set of PPG pulses. That is, the system100may detect that multiple morphological feature values of the second set of PPG pulses satisfy the multiple morphological value ranges of the one or more PPG profiles. Stated differently, the system100may identify PPG pulses that match the respective PPG profiles.

Subsequently, the system100may determine one or more physiological metrics associated with the user based on the one or more PPG pulses from the second set of PPG pulses matching the one or more PPG profiles from the first set of PPG pulses. In other words, the system100may utilize the PPG pulses that match the respective PPG profiles to perform physiological measurements for the user (e.g., perform heartrate measurements, HRV measurements, SpO2 measurements, and the like). Alternatively, the system100may detect that the one or more PPG pulses from the second set of PPG pulses fails to match the one or more PPG profiles from the second set of PPG pulses and may refrain from using that physiological metric associated with the user.

FIG.2illustrates an example of a system200that supports techniques for identifying representative PPG pulses in accordance with aspects of the present disclosure. The system200may implement, or be implemented by, system100. In particular, system200illustrates an example of a ring104(e.g., wearable device104), a user device106, and a server110, as described with reference toFIG.1.

In some aspects, the ring104may be configured to be worn around a user's finger, and may determine one or more user physiological parameters when worn around the user's finger. Example measurements and determinations may include, but are not limited to, user skin temperature, pulse waveforms, respiratory rate, heart rate, HRV, blood oxygen levels, and the like.

The system200further includes a user device106(e.g., a smartphone) in communication with the ring104. For example, the ring104may be in wireless and/or wired communication with the user device106. In some implementations, the ring104may send measured and processed data (e.g., temperature data, PPG data, motion/accelerometer data, ring input data, and the like) to the user device106. The user device106may also send data to the ring104, such as ring104firmware/configuration updates. The user device106may process data. In some implementations, the user device106may transmit data to the server110for processing and/or storage.

The ring104may include a housing205that may include an inner housing205-aand an outer housing205-b. In some aspects, the housing205of the ring104may store or otherwise include various components of the ring including, but not limited to, device electronics, a power source (e.g., battery210, and/or capacitor), one or more substrates (e.g., printable circuit boards) that interconnect the device electronics and/or power source, and the like. The device electronics may include device modules (e.g., hardware/software), such as: a processing module230-a, a memory215, a communication module220-a,a power module225, and the like. The device electronics may also include one or more sensors. Example sensors may include one or more temperature sensors240, a PPG sensor assembly (e.g., PPG system235), and one or more motion sensors245.

The sensors may include associated modules (not illustrated) configured to communicate with the respective components/modules of the ring104, and generate signals associated with the respective sensors. In some aspects, each of the components/modules of the ring104may be communicatively coupled to one another via wired or wireless connections. Moreover, the ring104may include additional and/or alternative sensors or other components that are configured to collect physiological data from the user, including light sensors (e.g., LEDs), oximeters, and the like.

The ring104shown and described with reference toFIG.2is provided solely for illustrative purposes. As such, the ring104may include additional or alternative components as those illustrated inFIG.2. Other rings104that provide functionality described herein may be fabricated. For example, rings104with fewer components (e.g., sensors) may be fabricated. In a specific example, a ring104with a single temperature sensor240(or other sensor), a power source, and device electronics configured to read the single temperature sensor240(or other sensor) may be fabricated. In another specific example, a temperature sensor240(or other sensor) may be attached to a user's finger (e.g., using clamps, spring loaded clamps, etc.). In this case, the sensor may be wired to another computing device, such as a wrist worn computing device that reads the temperature sensor240(or other sensor). In other examples, a ring104that includes additional sensors and processing functionality may be fabricated.

The housing205may include one or more housing205components. The housing205may include an outer housing205-bcomponent (e.g., a shell) and an inner housing205-acomponent (e.g., a molding). The housing205may include additional components (e.g., additional layers) not explicitly illustrated inFIG.2. For example, in some implementations, the ring104may include one or more insulating layers that electrically insulate the device electronics and other conductive materials (e.g., electrical traces) from the outer housing205-b(e.g., a metal outer housing205-b). The housing205may provide structural support for the device electronics, battery210, substrate(s), and other components. For example, the housing205may protect the device electronics, battery210, and substrate(s) from mechanical forces, such as pressure and impacts. The housing205may also protect the device electronics, battery210, and substrate(s) from water and/or other chemicals.

The outer housing205-bmay be fabricated from one or more materials. In some implementations, the outer housing205-bmay include a metal, such as titanium, that may provide strength and abrasion resistance at a relatively light weight. The outer housing205-bmay also be fabricated from other materials, such polymers. In some implementations, the outer housing205-bmay be protective as well as decorative.

The inner housing205-amay be configured to interface with the user's finger. The inner housing205-amay be formed from a polymer (e.g., a medical grade polymer) or other material. In some implementations, the inner housing205-amay be transparent. For example, the inner housing205-amay be transparent to light emitted by the PPG light emitting diodes (LEDs). In some implementations, the inner housing205-acomponent may be molded onto the outer housing205-b.For example, the inner housing205-amay include a polymer that is molded (e.g., injection molded) to fit into an outer housing205-bmetallic shell.

The ring104may include one or more substrates (not illustrated). The device electronics and battery210may be included on the one or more substrates. For example, the device electronics and battery210may be mounted on one or more substrates. Example substrates may include one or more printed circuit boards (PCBs), such as flexible PCB (e.g., polyimide). In some implementations, the electronics/battery210may include surface mounted devices (e.g., surface-mount technology (SMT) devices) on a flexible PCB. In some implementations, the one or more substrates (e.g., one or more flexible PCBs) may include electrical traces that provide electrical communication between device electronics. The electrical traces may also connect the battery210to the device electronics.

The device electronics, battery210, and substrates may be arranged in the ring104in a variety of ways. In some implementations, one substrate that includes device electronics may be mounted along the bottom of the ring104(e.g., the bottom half), such that the sensors (e.g., PPG system235, temperature sensors240, motion sensors245, and other sensors) interface with the underside of the user's finger. In these implementations, the battery210may be included along the top portion of the ring104(e.g., on another substrate).

The various components/modules of the ring104represent functionality (e.g., circuits and other components) that may be included in the ring104. Modules may include any discrete and/or integrated electronic circuit components that implement analog and/or digital circuits capable of producing the functions attributed to the modules herein. For example, the modules may include analog circuits (e.g., amplification circuits, filtering circuits, analog/digital conversion circuits, and/or other signal conditioning circuits). The modules may also include digital circuits (e.g., combinational or sequential logic circuits, memory circuits etc.).

The memory215(memory module) of the ring104may include any volatile, non-volatile, magnetic, or electrical media, such as a 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 memory215may store any of the data described herein. For example, the memory215may be configured to store data (e.g., motion data, temperature data, PPG data) collected by the respective sensors and PPG system235. Furthermore, memory215may include instructions that, when executed by one or more processing circuits, cause the modules to perform various functions attributed to the modules herein. The device electronics of the ring104described herein are only example device electronics. As such, the types of electronic components used to implement the device electronics may vary based on design considerations.

The functions attributed to the modules of the ring104described herein may be embodied as one or more processors, hardware, firmware, software, or any combination thereof. Depiction of different features as modules is intended to highlight different functional aspects and does not necessarily imply that such modules must be realized by separate hardware/software components. Rather, functionality associated with one or more modules may be performed by separate hardware/software components or integrated within common hardware/software components.

The processing module230-aof the ring104may include one or more processors (e.g., processing units), microcontrollers, digital signal processors, systems on a chip (SOCs), and/or other processing devices. The processing module230-acommunicates with the modules included in the ring104. For example, the processing module230-amay transmit/receive data to/from the modules and other components of the ring104, such as the sensors. As described herein, the modules may be implemented by various circuit components. Accordingly, the modules may also be referred to as circuits (e.g., a communication circuit and power circuit).

The processing module230-amay communicate with the memory215. The memory215may include computer-readable instructions that, when executed by the processing module230-a,cause the processing module230-ato perform the various functions attributed to the processing module230-aherein. In some implementations, the processing module230-a(e.g., a microcontroller) may include additional features associated with other modules, such as communication functionality provided by the communication module220-a(e.g., an integrated Bluetooth Low Energy transceiver) and/or additional onboard memory215.

The communication module220-amay include circuits that provide wireless and/or wired communication with the user device106(e.g., communication module220-bof the user device106). In some implementations, the communication modules220-a,220-bmay include wireless communication circuits, such as Bluetooth circuits and/or Wi-Fi circuits. In some implementations, the communication modules220-a,220-bcan include wired communication circuits, such as Universal Serial Bus (USB) communication circuits. Using the communication module220-a,the ring104and the user device106may be configured to communicate with each other. The processing module230-aof the ring may be configured to transmit/receive data to/from the user device106via the communication module220-a.Example data may include, but is not limited to, motion data, temperature data, pulse waveforms, heart rate data, HRV data, PPG data, and status updates (e.g., charging status, battery charge level, and/or ring104configuration settings). The processing module230-aof the ring may also be configured to receive updates (e.g., software/firmware updates) and data from the user device106.

The ring104may include a battery210(e.g., a rechargeable battery210). An example battery210may include a Lithium-Ion or Lithium-Polymer type battery210, although a variety of battery210options are possible. The battery210may be wirelessly charged. In some implementations, the ring104may include a power source other than the battery210, such as a capacitor. The power source (e.g., battery210or capacitor) may have a curved geometry that matches the curve of the ring104. In some aspects, a charger or other power source may include additional sensors that may be used to collect data in addition to, or that supplements, data collected by the ring104itself. Moreover, a charger or other power source for the ring104may function as a user device106, in which case the charger or other power source for the ring104may be configured to receive data from the ring104, store and/or process data received from the ring104, and communicate data between the ring104and the servers110.

In some aspects, the ring104includes a power module225that may control charging of the battery210. For example, the power module225may interface with an external wireless charger that charges the battery210when interfaced with the ring104. The charger may include a datum structure that mates with a ring104datum structure to create a specified orientation with the ring104during104charging. The power module225may also regulate voltage(s) of the device electronics, regulate power output to the device electronics, and monitor the state of charge of the battery210. In some implementations, the battery210may include a protection circuit module (PCM) that protects the battery210from high current discharge, over voltage during104charging, and under voltage during104discharge. The power module225may also include electro-static discharge (ESD) protection.

The one or more temperature sensors240may be electrically coupled to the processing module230-a.The temperature sensor240may be configured to generate a temperature signal (e.g., temperature data) that indicates a temperature read or sensed by the temperature sensor240. The processing module230-amay determine a temperature of the user in the location of the temperature sensor240. For example, in the ring104, temperature data generated by the temperature sensor240may indicate a temperature of a user at the user's finger (e.g., skin temperature). In some implementations, the temperature sensor240may contact the user's skin. In other implementations, a portion of the housing205(e.g., the inner housing205-a) may form a barrier (e.g., a thin, thermally conductive barrier) between the temperature sensor240and the user's skin. In some implementations, portions of the ring104configured to contact the user's finger may have thermally conductive portions and thermally insulative portions. The thermally conductive portions may conduct heat from the user's finger to the temperature sensors240. The thermally insulative portions may insulate portions of the ring104(e.g., the temperature sensor240) from ambient temperature.

In some implementations, the temperature sensor240may generate a digital signal (e.g., temperature data) that the processing module230-amay use to determine the temperature. As another example, in cases where the temperature sensor240includes a passive sensor, the processing module230-a(or a temperature sensor240module) may measure a current/voltage generated by the temperature sensor240and determine the temperature based on the measured current/voltage. Example temperature sensors240may 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.

The processing module230-amay sample the user's temperature over time. For example, the processing module230-amay sample the user's temperature according to a sampling rate. An example sampling rate may include one sample per second, although the processing module230-amay be configured to sample the temperature signal at other sampling rates that are higher or lower than one sample per second. In some implementations, the processing module230-amay sample the user's temperature continuously throughout the day and night. Sampling at a sufficient rate (e.g., one sample per second) throughout the day may provide sufficient temperature data for analysis described herein.

The processing module230-amay store the sampled temperature data in memory215. In some implementations, the processing module230-amay process the sampled temperature data. For example, the processing module230-amay determine average temperature values over a period of time. In one example, the processing module230-amay determine an average temperature value each minute by summing all temperature values collected over the minute and dividing by the number of samples over the minute. In a specific example where the temperature is sampled at one sample per second, the average temperature may be a sum of all sampled temperatures for one minute divided by sixty seconds. The memory215may store the average temperature values over time. In some implementations, the memory215may store average temperatures (e.g., one per minute) instead of sampled temperatures in order to conserve memory215.

The sampling rate, which may be stored in memory215, 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 be changed throughout the day/night. In some implementations, the ring104may filter/reject temperature readings, such as large spikes in temperature that are not indicative of physiological changes (e.g., a temperature spike from a hot shower). In some implementations, the ring104may filter/reject temperature readings that may not be reliable due to other factors, such as excessive motion during104exercise (e.g., as indicated by a motion sensor245).

The ring104(e.g., communication module) may transmit the sampled and/or average temperature data to the user device106for storage and/or further processing. The user device106may transfer the sampled and/or average temperature data to the server110for storage and/or further processing.

Although the ring104is illustrated as including a single temperature sensor240, the ring104may include multiple temperature sensors240in one or more locations, such as arranged along the inner housing205-anear the user's finger. In some implementations, the temperature sensors240may be stand-alone temperature sensors240. Additionally, or alternatively, one or more temperature sensors240may be included with other components (e.g., packaged with other components), such as with the accelerometer and/or processor.

The processing module230-amay acquire and process data from multiple temperature sensors240in a similar manner described with respect to a single temperature sensor240. For example, the processing module230may individually sample, average, and store temperature data from each of the multiple temperature sensors240. In other examples, the processing module230-amay sample the sensors at different rates and average/store different values for the different sensors. In some implementations, the processing module230-amay be configured to determine a single temperature based on the average of two or more temperatures determined by two or more temperature sensors240in different locations on the finger.

The temperature sensors240on the ring104may acquire distal temperatures at the user's finger (e.g., any finger). For example, one or more temperature sensors240on the ring104may acquire a user's temperature from the underside of a finger or at a different location on the finger. In some implementations, the ring104may continuously acquire distal temperature (e.g., at a sampling rate). Although distal temperature measured by a ring104at the finger is described herein, other devices may measure temperature at the same/different locations. In some cases, the distal temperature measured at a user's finger may differ from the temperature measured at a user's wrist or other external body location. Additionally, the distal temperature measured at a user's finger (e.g., a “shell” temperature) may differ from the user's core temperature. As such, the ring104may provide a useful temperature signal that may not be acquired at other internal/external locations of 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 evident in core temperature. For example, continuous temperature measurement at the finger may capture minute-to-minute or hour-to-hour temperature fluctuations that provide additional insight that may not be provided by other temperature measurements elsewhere in the body.

The ring104may include a PPG system235. The PPG system235may include one or more optical transmitters that transmit light. The PPG system235may also include one or more optical receivers that receive light transmitted by the one or more optical transmitters. An optical receiver may generate a signal (hereinafter “PPG” signal) that indicates an amount of light received by the optical receiver. The optical transmitters may illuminate a region of the user's finger. The PPG signal generated by the PPG system235may indicate the perfusion of blood in the illuminated region. For example, the PPG signal may indicate blood volume changes in the illuminated region caused by a user's pulse pressure. The processing module230-amay sample the PPG signal and determine a user's pulse waveform based on the PPG signal. The processing module230-amay determine a variety of physiological parameters based on the user's pulse waveform, such as a user's respiratory rate, heart rate, HRV, oxygen saturation, and other circulatory parameters.

In some implementations, the PPG system235may be configured as a reflective PPG system235where the optical receiver(s) receive transmitted light that is reflected through the region of the user's finger. In some implementations, the PPG system235may be configured as a transmissive PPG system235where the optical transmitter(s) and optical receiver(s) are arranged opposite to one another, such that light is transmitted directly through a portion of the user's finger to the optical receiver(s).

The number and ratio of transmitters and receivers included in the PPG system235may vary. Example optical transmitters may include light-emitting diodes (LEDs). The optical transmitters may transmit light in the infrared spectrum and/or other spectrums. Example optical receivers may include, but are not limited to, photosensors, phototransistors, and photodiodes. The optical receivers may be configured to generate PPG signals in response to the wavelengths received from the optical transmitters. The location of the transmitters and receivers may vary. Additionally, a single device may include reflective and/or transmissive PPG systems

The PPG system235illustrated inFIG.2may include a reflective PPG system235in some implementations. In these implementations, the PPG system235may include a centrally located optical receiver (e.g., at the bottom of the ring104) and two optical transmitters located on each side of the optical receiver. In this implementation, the PPG system235(e.g., optical receiver) may generate the PPG signal based on light received from one or both of the optical transmitters. In other implementations, other placements, combinations, and/or configurations of one or more optical transmitters and/or optical receivers are contemplated.

The processing module230-amay 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 module230-amay cause the optical transmitter with the 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).

Sampling the PPG signal generated by the PPG system235may result in a pulse waveform that may be referred to as a “PPG.” The pulse waveform may indicate blood pressure vs time for multiple cardiac cycles. The pulse waveform may include peaks that indicate cardiac cycles. Additionally, the pulse waveform may include respiratory induced variations that may be used to determine respiration rate. The processing module230-amay store the pulse waveform in memory215in some implementations. The processing module230-amay process the pulse waveform as it is generated and/or from memory215to determine user physiological parameters described herein.

The processing module230-amay determine the user's heart rate based on the pulse waveform. For example, the processing module230-amay determine heart rate (e.g., in beats per minute) based on the time between peaks in the pulse waveform. The time between peaks may be referred to as an interbeat interval (IBI). The processing module230-amay store the determined heart rate values and IBI values in memory215.

The processing module230-amay determine HRV over time. For example, the processing module230-amay determine HRV based on the variation in the IBIs. The processing module230-amay store the HRV values over time in the memory215. Moreover, the processing module230-amay determine the user's respiratory rate over time. For example, the processing module230-amay determine respiratory rate based on frequency modulation, amplitude modulation, or baseline modulation of the user's IBI values over a period of time. Respiratory rate may be calculated in breaths per minute or as another breathing rate (e.g., breaths per 30 seconds). The processing module230-amay store user respiratory rate values over time in the memory215.

The ring104may include one or more motion sensors245, such as one or more accelerometers (e.g., 6-D accelerometers) and/or one or more gyroscopes (gyros). The motion sensors245may generate motion signals that indicate motion of the sensors. For example, the ring104may include one or more accelerometers that generate acceleration signals that indicate acceleration of the accelerometers. As another example, the ring104may include one or more gyro sensors that generate gyro signals that indicate angular motion (e.g., angular velocity) and/or changes in orientation. The motion sensors245may be included in one or more sensor packages. An example accelerometer/gyro sensor is a Bosch BMl160 inertial micro electro-mechanical system (MEMS) sensor that may measure angular rates and accelerations in three perpendicular axes.

The processing module230-amay sample the motion signals at a sampling rate (e.g., 50 Hz) and determine the motion of the ring104based on the sampled motion signals. For example, the processing module230-amay sample acceleration signals to determine acceleration of the ring104. As another example, the processing module230-amay sample a gyro signal to determine angular motion. In some implementations, the processing module230-amay store motion data in memory215. Motion data may include sampled motion data as well as motion data that is calculated based on the sampled motion signals (e.g., acceleration and angular values).

The ring104may store a variety of data described herein. For example, the ring104may store temperature data, such as raw sampled temperature data and calculated temperature data (e.g., average temperatures). As another example, the ring104may store PPG signal data, such as pulse waveforms and data calculated based on the pulse waveforms (e.g., heart rate values, IBI values, HRV values, and respiratory rate values). The ring104may also store motion data, such as sampled motion data that indicates linear and angular motion.

The ring104, or other computing device, may calculate and store additional values based on the sampled/calculated physiological data. For example, the processing module230may calculate and store various metrics, such as sleep metrics (e.g., a Sleep Score), activity metrics, and readiness metrics. In some implementations, additional values/metrics may be referred to as “derived values.” The ring104, or other computing/wearable device, may calculate a variety of values/metrics with respect to motion. Example derived values for motion data may include, but are not limited to, motion count values, regularity values, intensity values, metabolic equivalence of task values (METs), and orientation values. Motion counts, regularity values, intensity values, and METs may indicate an amount of user motion (e.g., velocity/acceleration) over time. Orientation values may indicate how the ring104is oriented on the user's finger and if the ring104is worn on the left hand or right hand.

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

In some implementations, the processing module230-amay compress the data stored in memory215. For example, the processing module230-amay delete sampled data after making calculations based on the sampled data. As another example, the processing module230-amay average data over longer periods of time in order to reduce the number of stored values. In a specific example, if average temperatures for a user over one minute are stored in memory215, the processing module230-amay calculate average temperatures over a five minute time period for storage, and then subsequently erase the one minute average temperature data. The processing module230-amay compress data based on a variety of factors, such as the total amount of used/available memory215and/or an elapsed time since the ring104last transmitted the data to the user device106.

Although a user's physiological parameters may be measured by sensors included on a ring104, other devices may measure a user's physiological parameters. For example, although a user's temperature may be measured by a temperature sensor240included in a ring104, other devices may measure a user's temperature. In some examples, other wearable devices (e.g., wrist devices) may include sensors that measure user physiological parameters. Additionally, medical devices, such as external medical devices (e.g., wearable medical devices) and/or implantable medical devices, may measure a user's physiological parameters. One or more sensors on any type of computing device may be used to implement the techniques described herein.

The physiological measurements may be taken continuously throughout the day and/or night. In some implementations, the physiological measurements may be taken during104portions of the day and/or portions of the night. In some implementations, the physiological measurements may be taken in response to determining that the user is in a specific state, such as an active state, resting state, and/or a sleeping state. For example, the ring104can make physiological measurements in a resting/sleep state in order to acquire cleaner physiological signals. In one example, the ring104or other device/system may detect when a user is resting and/or sleeping and acquire physiological parameters (e.g., temperature) for that detected state. The devices/systems may use the resting/sleep physiological data and/or other data when the user is in other states in order to implement the techniques of the present disclosure.

In some implementations, as described previously herein, the ring104may be configured to collect, store, and/or process data, and may transfer any of the data described herein to the user device106for storage and/or processing. In some aspects, the user device106includes a wearable application250, an operating system (OS), a web browser application (e.g., web browser280), one or more additional applications, and a GUI275. The user device106may further include other modules and components, including sensors, audio devices, haptic feedback devices, and the like. The wearable application250may include an example of an application (e.g., “app”) that may be installed on the user device106. The wearable application250may be configured to acquire data from the ring104, store the acquired data, and process the acquired data as described herein. For example, the wearable application250may include a user interface (UI) module255, an acquisition module260, a processing module230-b,a communication module220-b,and a storage module (e.g., database265) configured to store application data.

The various data processing operations described herein may be performed by the ring104, the user device106, the servers110, or any combination thereof. For example, in some cases, data collected by the ring104may be pre-processed and transmitted to the user device106. In this example, the user device106may perform some data processing operations on the received data, may transmit the data to the servers110for data processing, or both. For instance, in some cases, the user device106may perform processing operations that require relatively low processing power and/or operations that require a relatively low latency, whereas the user device106may transmit the data to the servers110for processing operations that require relatively high processing power and/or operations that may allow relatively higher latency.

In some aspects, the ring104, user device106, and server110of the system200may be configured to evaluate sleep patterns for a user. In particular, the respective components of the system200may be used to collect data from a user via the ring104, and generate one or more scores (e.g., Sleep Score, Readiness Score) for the user based on the collected data. For example, as noted previously herein, the ring104of the system200may be worn by a user to collect data from the user, including temperature, heart rate, HRV, and the like. Data collected by the ring104may be used to determine when the user is asleep in order to evaluate the user's sleep for a given “sleep day.” In some aspects, scores may be calculated for the user for each respective sleep day, such that a first sleep day is associated with a first set of scores, and a second sleep day is associated with a second set of scores. Scores may be calculated for each respective sleep day based on data collected by the ring104during the respective sleep day. Scores may include, but are not limited to, Sleep Scores, Readiness Scores, and the like.

In some cases, “sleep days” may align with the traditional calendar days, such that a given sleep day runs from midnight to midnight of the respective calendar day. In other cases, sleep days may be offset relative to calendar days. For example, sleep day's may run from 6:00 pm (18:00) of a calendar day until 6:00 pm (18:00) of the subsequent calendar day. In this example, 6:00 pm may serve as a “cut-off 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 subsequent sleep day. Due to the fact that most individuals sleep the most at night, offsetting sleep days relative to calendar days may enable the system200to evaluate sleep patterns for users in such a manner that is consistent with their sleep schedules. In some cases, users may be able to selectively adjust (e.g., via the GUI) a timing of sleep days relative to calendar days so that the sleep days are aligned with the duration of time that the respective users typically sleep.

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 “contributors,” “factors,” or “contributing factors.” For example, a user's overall Sleep Score may be calculated based on a set of contributors, including: total sleep, efficiency, restfulness, REM sleep, deep sleep, latency, timing, or any combination thereof. The Sleep Score may include any quantity of contributors. The “total sleep” contributor may refer to the sum of all sleep periods of the sleep day. The “efficiency” contributor may reflect the percentage of time spent asleep compared to time spent awake while in bed, and may be calculated using the efficiency average of long sleep periods (e.g., primary sleep period) of the sleep day, weighted by a duration of each sleep period. The “restfulness” contributor may indicate how restful the user's sleep is, and may be calculated using the average of all sleep periods of the sleep day, weighted by a duration of each period. The restfulness contributor may be based on a “wake up count” (e.g., sum of all the wake-ups (when user wakes up) detected during different sleep periods), excessive movement, and a “got up count” (e.g., sum of all the got-ups (when user gets out of bed) detected during the different sleep periods).

The “REM sleep” contributor may refer to a sum total of REM sleep durations across all sleep periods of the sleep day including REM sleep. Similarly, the “deep sleep” contributor may refer to a sum total of deep sleep durations across all sleep periods of the sleep day including deep sleep. The “latency” contributor may signify how long (e.g., average, median, longest) the user takes to go to sleep, and may be calculated using the average of long sleep periods throughout the sleep day, weighted by a duration of each period and the number of such periods (e.g., consolidation of a given sleep stage or sleep stages may be its own contributor or weight other contributors). Lastly, the “timing” contributor may refer to a relative timing of sleep periods within the sleep day and/or calendar day, and may be calculated using the average of all sleep periods of the sleep day, weighted by a duration of each period.

By way of another example, a user's overall Readiness Score may be calculated based on a set of contributors, including: sleep, sleep balance, heart rate, HRV balance, recovery index, temperature, activity, activity balance, or any combination thereof. The Readiness Score may include any quantity of contributors. The “sleep” contributor may refer to the combined Sleep Score of all sleep periods within the sleep day. The “sleep balance” contributor may refer to a cumulative duration of all sleep periods within the sleep day. In particular, sleep balance may indicate to a user whether the sleep that the user has been getting over some duration of time (e.g., the past two weeks) is in balance with the user's needs. Typically, adults need 7-9 hours of sleep a night to stay healthy, alert, and to perform at their best both mentally and physically. However, it is normal to have an occasional night of bad sleep, so the sleep balance contributor takes into account long-term sleep patterns to determine whether each user's sleep needs are being met. The “resting heart rate” contributor may indicate a lowest heart rate from the longest sleep period of the sleep day (e.g., primary sleep period) and/or the lowest heart rate from naps occurring after the primary sleep period.

Continuing with reference to the “contributors” (e.g., factors, contributing factors) of the Readiness Score, the “HRV balance” contributor may indicate a highest HRV average from the primary sleep period and the naps happening after the primary sleep period. The HRV balance contributor may help users keep track of their recovery status by comparing their HRV trend over a first time period (e.g., two weeks) to an average HRV over some second, longer time period (e.g., three months). The “recovery index” contributor may be calculated based on the longest sleep period. Recovery index measures how long it takes for a user's resting heart rate to stabilize during the night. A sign of a 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” contributor may be calculated based on the longest sleep period (e.g., primary sleep period) or based on a nap happening after the longest sleep period if the user's highest temperature during the nap is at least 0.5° C. higher than the highest temperature during the longest period. In some aspects, the ring may measure a user's body temperature while the user is asleep, and the system200may display the user's average temperature relative to the user's baseline temperature. If a user's body temperature is outside of their normal range (e.g., clearly above or below0.0), the body temperature contributor may be highlighted (e.g., go to a “Pay attention” state) or otherwise generate an alert for the user.

In some aspects, the respective devices of the system200may support techniques for identifying representative PPG pulses of a user102collected via a wearable device104(e.g., a wearable ring device). To identify the one or more PPG pulses that accurately represent one or more physiological metrics of user102, the wearable device104may acquire PPG data that includes a first set of PPG pulses from the user102. In some examples, the wearable device104may collect PPG data based on an arterial blood flow, a capillary arterial flow, and/or a venous blood flow of the user102via a PPG system235. That is, the PPG system235may utilize one or more light sources (e.g., LEDs) and photodetectors near the surface of the skin to measure the volumetric variations of blood flow of the user102. In some examples, a triple LED (e.g., red, green, and IR) PPG system235may enable the wearable device104to propagate multiple light waves and measure multiple wavelengths. In some examples, the PPG data indicates physiological metrics for each respective user102. For example, the wearable device104may collect PPG data indicating physiological metrics, such as a heart rate metric, an HRV metric, a blood oxygen saturation metric, a blood pressure metric, an arterial reactivity metric (e.g., a cardiovascular age), or the like.

In some examples, the system200may compare morphological features from the first set of PPG pulses measured from the wearable device104. For example, the system200may compare the morphological features of the first set of PPG pulses such as the amplitudes of PPG pulses, time durations of PPG pulses, slopes of PPG pulses, curvatures of PPG pulses, relationships of PPG pulses, or the like. Further, the system200may compare the morphological features from the first set of PPG pulses to determine multiple morphological value ranges that for each of the morphological features (e.g., the system200determines values of W, X, Y, and Z, so that the system can determine that one or more PPG pulses with an amplitude between X and Y and a time duration between W and Z satisfies a respective PPG profile). In some examples, the morphological value ranges include a range of average morphological values for each morphological feature, a range of median morphological values for each morphological feature, and a range of mode morphological values for each morphological features, or a combination of ranges (e.g., the system200determines the average amplitude of PPG pulses in addition to a range of amplitudes that may match one or more PPG profiles).

Upon determining the morphological value ranges of the first set of PPG pulses, the system200may determine one or more PPG profiles (e.g., one or more representative PPG pulses, one or more common pulse templates) for the user102. In some examples, each of the PPG profiles may represent the morphological value ranges and may represent physiological features of the user102. For example, a PPG profile may include a “representative” or average morphological features within the determined morphological ranges, such as an amplitude (e.g., size) within a range (e.g., values between X and Y) for a duration in time (e.g., a time between W and Z). As such, each of the PPG profiles may represent a normal (e.g., common, average) PPG pulse calculated from the morphological value ranges from the first set of PPG pulses for a specific physiological measurement.

In some implementations, the system200may determine PPG profiles based on one or more wavelengths of light. That is, the system200may generate multiple sets of PPG profiles for multiple wavelengths (e.g., a first set of PPG profiles for green light, a second set of PPG profiles for red light, a third set of PPG profiles for IR light). In some examples, the PPG system235may acquire PPG data using a first light associated with a first wavelength. The PPG system235may compare multiple PPG pulses of the PPG data acquired with a first wavelength and may compare the one or more morphological features. That is, the PPG system235may determine a first set of PPG profiles associated with the first wavelength based on the comparison of multiple PPG pulses using the first light. In addition, the PPG system235may acquire PPG data using a second light associated with a second wavelength. The PPG system235may compare multiple PPG pulses for the PPG data found using a second wavelength and may compare the one or more morphological features. As such, the PPG system235may determine a second set of PPG profiles associated with the second wavelength. In such cases, the system200may be configured to compare subsequently-acquired PPG pulses with the respective PPG profiles in order to identify representative PPG pulses associated with the respective wavelengths (e.g., compare PPG pulses collected via the first wavelength to the first set of PPG profiles, compare PPG pulses collected via the second wavelength to the second set of PPG profiles).

In some aspects, the system200may generate the one or more PPG profiles based on physiological (e.g., PPG) data and additional sensor measurements that indicate that the user102is in a specific posture (e.g., user102is sitting, standing, lying down, or the like). In particular, PPG pulses collected while the user is in different postures may exhibit different morphological features (e.g., different shapes, amplitudes, durations, etc.). As such, the system200may be configured to generate different sets of PPG profiles based on the different postures of the user (e.g., first set of PPG profiles for a standing posture, second set of PPG profiles for a sitting posture).

The wearable device104may include one or more sensors that are able to measure or estimate the posture of the user102, including one or more motion sensors245, such as accelerometers (e.g., motion/activity sensors), and the one or more gyro sensors. In some examples, the one or more motion sensors245and the one or more gyro sensors may measure a direction of movement and orientation changes of a user to help determine the position/posture of the user102. Additionally, or alternatively, a pressure sensor246of the ring104may measure the ambient air pressure with respect to a relative pressure to the user102(e.g., about elevation of the hand of the user102, about the air pressure acting on the point of measurement against a tissue of the user102, such as internal hydrostatic pressure) to determine the position of the user102. In some examples, the pressure sensor246may measure hydrostatic pressure acting against one or more vein walls inside of the user102that may affect the PPG pulse morphology of PPG pulses. Moreover, in some cases, the system200may utilize one or more other data sources (such as additional wearable devices) to determine a posture of the user.

In some examples, the system200may acquire PPG data corresponding to different posture states of the user102. For example, the system200may acquire PPG data for a first time interval where the user102is in a sitting posture (e.g., a first posture) and determine a first set of PPG profiles associated with the sitting posture. In addition, the system200may acquire physiological data for a second time interval where the user102is in a standing posture (e.g., a second posture) and determine a second set of PPG profiles associated with the standing posture. As such, the system200may detect that the user102is positioned in a sitting posture because the PPG data corresponds to the first set of PPG profiles that are associated with the sitting posture. Further, the system200may generate multiple PPG profiles over periods of time that accurately represent PPG pulses associated with respective postures of the user102.

In some examples, the system200may determine one or more PPG profiles based on common PPG pulses collected from the user102via a day-time calibration sequence. The day-time calibration sequence may define valid samples and determine the PPG pulses suitable for performing measurements. In some cases, the system200may utilize a changing correlation between different signal paths to find an optimal measurement time for the PPG pulses. That is, the system200may dynamically select one or more signal paths that produce reliable PPG pulses. As such, the system200may use appropriate signal paths, the calibration sequence, and additional factors to select representative PPG pulses with appropriate signal quality metrics for the one or more PPG profiles.

In some aspects, the system200may initiate a measurement calibration sequence by instructing the user (e.g., via the wearable application250of a user device106) to position themselves in a series of different postures like standing up, sitting, and lying down (e.g., similar to how traditional blood pressure measurement with an arm cuff is performed while the user is sitting down with their arm laying flat on a surface such as a table). In such cases, sensor calibration may be performed with these predetermined postures when the device is deployed. Moreover, recalibration may be performed at regular or irregular time intervals.

Additionally, or alternatively, the system200may determine one or more PPG profiles based on relative pressure between the wearable device104and the user102. Varying pressures between the wearable device104and the tissue of the user may cause morphological features of acquired PPG pulses to change. As such, the system200may be configured to determine different sets of PPG profiles associated with different pressure ranges. In particular, with enough applied pressure, blood flow can be cut off completely from top layers of tissue. This may be illustrated by PPG signals acquired using green light disappearing earlier (e.g., becoming undetectable) as compared to other PPG signals collected using IR light as increasing pressure is applied, as IR light penetrates to deeper layers of tissue and is able to collect PPG data even when blood flow is cut off from higher layers of tissue. As the external sensor pressure acts against body internal pressure, a correlation to blood pressure may be determined, and it may be possible to determine at least one sensor pressure reference point at the pressure when the green PPG pulse shape is not visible due to applied pressure.

In some examples, the wearable device104may be equipped with the pressure sensor246that measures contact pressure between the wearable device104and the user102. In some aspects, the system200may acquire PPG data indicating that additional pressure is applied between the wearable device104and a tissue of the user102. In some examples, additional pressure is applied when the user102grabs an object, the user102has swollen extremities (e.g., fingers) due to dehydration, or the like. In some examples, the wearable device104may measure pressure via optical, piezoresistive, capacitive, or other pressure-sensing techniques. In some examples, the pressure sensor246may include one or more piezoelectric sensors. In other implementations, the system200may enable the wearable device104to use bioimpedance techniques to measure the response of an external current via the wearable device104. That is, the wearable device104may use the bioimpedance techniques to measure electrodermal activity and quantify the contact pressure (e.g., quality) between the wearable device104and the skin of the user102. In some examples, the wearable device104may include a blood pressure cuff to acquire additional physiological metrics from the user102.

To account for different pressures that may affect the morphological features of the PPG pulses, the system200may determine the multiple PPG profiles based on different values of pressure between the wearable device104and the user102. In some cases, the system200may acquire physiological data associated with different pressure states between the user102and the wearable device104. For example, the system200may acquire the physiological data via the pressure sensor246for a first time interval where the user102is in a normal pressure state (e.g., a first pressure state where the hand position of the user102is unclenched or the user102is hydrated and fingers are unswollen) and determine a first set of PPG profiles associated to the normal pressure state. In addition, the system200may acquire the physiological data via the pressure sensor246for a second time interval where the user102may apply additional pressure to the wearable device104(e.g., by gripping a handle or other object with varying grip strength). That is, the system200may detect an additional pressure state (e.g., a second pressure state where the hand position of the user102is clenched or the user102is dehydrated and fingers are swollen) and determine a second set of PPG profiles associated with the additional pressure state. In some aspects, the system200may determine multiple PPG profiles that correspond to different pressure states between the user102and the wearable device104. That is, the system200may apply the multiple PPG profiles to determine whether additional PPG data accurately represents physiological metrics of the user102when under specific pressure states. For example, the system200may compare PPG pulses collected under a first pressure state to the first set of PPG pulses, and may compare PPG pulses collected under a second pressure state to the second set of PPG pulses.

Additionally, or alternatively, the wearable device104may utilize the pressure sensor246for contact pressure estimation in combination with the PPG system235to accurately measure the physiological parameters of the user102. In some examples, the PPG system235may account for a skin color (e.g., light to dark skin color) measurement. For example, the PPG system235may enable the wearable device104to measure further penetration depths for a user with lighter skin color compared to a user with a darker skin color. In some examples, the wearable device104may use the PPG system235to measure PPG measurements via reflective techniques. For example, the wearable device104may use a lock in amplifier (LIA) to enable light to be transmitted through the tissue of the user and may measure PPG measurements (e.g., transmittal PPG measurements) based on the light that is transmitted through the tissue. In some implementations, the system200may determine a correlation between different wavelengths collected via the PPG system235for an optical path.

In addition, the system200may enable the wearable device104to acquire additional PPG data that includes a second set of PPG pulses from the user102via the PPG system235. In some examples, the system200may instruct the wearable device104to send the second set of PPG pulses to a user device106, and the user device106may compare morphological features between the second set of PPG pulses and the one or more PPG profiles from the first set of PPG pulses. In some examples, the user device106may determine that one or more PPG pulses from the second set of PPG pulses match the one or more PPG profiles from the first set of PPG pulses. That is, the system200may use the database265of the wearable application250to determine if the second set of PPG pulses satisfy the multiple morphological value ranges of the one or more PPG profiles from the first set of PPG pulses stored in the database265. In other words, the system200may check if the one or more PPG pulses from the second set of PPG values may be in the range of the morphological values displayed from the representative PPG pulse generated from the first set of PPG values. As such, the system200may determine whether the one or more representative PPG pulses represent accurate, reliable physiological metrics for the user102based on using the second set of PPG pulses and may compare whether the second set of PPG pulses match the one or more PPG profiles from the first set of PPG pulses.

FIG.3illustrates an example of a system300that supports techniques for identifying representative PPG pulses in accordance with aspects of the present disclosure. In some implementations, the system300may implement, or be implemented by, aspects of the system100and the system200as described with reference toFIGS.1and2. For example, the system300may be implemented by a wearable device104(e.g., a ring104), a user device106, one or more servers110, or any combination thereof. In the following description of the system300, the operations may be performed in a different order than the example order shown, or the operations may be performed in different orders or at different times. Some operations may also be omitted from the system300, and other operations may be added to the system300.

In the example ofFIG.3, the system300may acquire PPG data from a user via a wearable device104. In particular,FIG.3illustrates a PPG graph305that illustrates a PPG signal with a set of multiple PPG pulses310(e.g., a first set of PPG pulses). In some aspects, the PPG signal with an associated signal quality metric may represent or be used to determine a physiological metric associated with the user, such as a heart rate metric, an HRV metric, a blood oxygen saturation metric, a blood pressure metric, an arterial reactivity metric, or the like. In the PPG graph305, the wearable device104may use the PPG signal to acquire PPG data in the form of multiple PPG pulses310. In some aspects, each of the PPG pulses310may be associated with respective morphological features that may include or describe features of the PPG pulses310. For example, morphological features of a PPG pulse310may include certain features or characteristics of the respective PPG pulse310, such as an amplitude of the PPG pulse310, time duration of the PPG pulse310, a slope of the PPG pulse310(e.g., first derivative), a curvature of the PPG pulse310(e.g., second derivative), relationships between the PPG pulse310and adjacent PPG pulses310, or the like.

Additionally, the system300may compare each of the morphological features of the PPG pulses310to determine multiple morphological value ranges for each of the morphological features (e.g., value ranges for PPG pulse310amplitudes, time durations, curvatures, etc.). In some examples, the system300may compare morphological features graphically to illustrate the morphological value ranges.

For example, inFIG.3, the system300may compare one or more morphological value ranges of PPG pulses310with a PPG pulse overlay graph315or a bell curve graph325. That is, the system300may use one or both graphs to compare each of the PPG pulses310and check where the morphological value ranges overlap in order to determine a representative PPG pulse320(e.g., a normal PPG pulse, a template PPG pulse) that exhibits the common or average values of the PPG pulses310(e.g., common/average amplitude, common/average slope, etc.).

For instance, by overlaying the respective PPG pulses310with one another via the PPG pulse overlay graph315, the system300may be configured to identify the average or most common features (e.g., average amplitude, slope, curvature, time duration, etc.) across the PPG pulses310, which may be used to identify “representative” PPG pulses (e.g., PPG profiles320). Similarly, the system300may calculate a morphological feature value for each of the PPG pulses310(e.g., amplitude of each PPG pulse, slope of each PPG pulse, etc.), and generate the bell curve graph325illustrating the determined morphological feature values for the set of PPG pulses310. In this example, the bell curve graph325may be used to determine the average, median, or most common morphological feature value, which may be used to identify “representative” PPG pulses (e.g., PPG profiles320).

In some implementations, the system300may identify representative PPG pulses (e.g., PPG profiles, or PPG templates). In the example ofFIG.3, at330, the system300may identify the PPG profiles320(e.g., representative PPG pulses310) to use to compare additional PPG data from the user. In some examples, the term “PPG profiles320” may be used interchangeably to the terms “representative PPG pulses”, “PPG templates,” and the like, as described herein. In other words, at330, the system300may identify one or more PPG profiles320that exhibit average or common morphological values. As described previously herein, the system300may be configured to identify different sets of PPG profiles330, such as different sets of PPG profiles320for different wavelength ranges, different sets of PPG profiles320for different user postures and/or pressures, different sets of PPG profiles320for different types of measurements, and the like.

At335, the wearable device104of the system300may acquire additional PPG data, such as one or more PPG pulses, from the user. In some examples, the system300may acquire additional PPG data at different time intervals (e.g., time periods) throughout a day (e.g., morning, noon, night). In some aspects, the additional PPG data may be acquired via PPG systems using one or more light wavelengths from one or more LEDs.

At340, the system300(e.g., wearable device104, user device106, servers110) may compare the one or more PPG pulses from the additional PPG data collected at335to the PPG profiles320determined at330. That is, the system300may determine which PPG pulses collected at335match the one or more PPG profiles320. In some cases, the system300may be configured to identify a set of consecutive PPG pulses from the additional PPG data that match the PPG profile(s)320.

In some examples, when performing the comparison at340, the system300may account for factors such as the posture of the user, pressure states between the user and the wearable device, wavelength of light used to collect the additional PPG data at335, and the like. For example, in cases where the additional PPG data acquired at335is collected using green light, the system300may compare the PPG pulses to one or more PPG profiles320associated with green light. By way of another example, in cases where the additional PPG data is acquired at335during a time that the user is in a standing posture, the system300may compare the PPG pulses to one or more PPG profiles320associated with a standing posture.

At345, the system300may identify one or more PPG pulses acquired at335that match the one or more PPG profiles320. For example, the system300may determine that a set of consecutive PPG pulses from the additional PPG data match the PPG profiles320. That is, the system300may determine that the additional PPG pulses exhibit morphological feature values that fall within the morphological feature value ranges of the PPG profiles320.

At350, the system300may determine whether or not to use the additional PPG pulses for physiological measurements. In particular, the system300may determine whether or not to use PPG pulses for physiological measurements based on whether or not the respective PPG pulses match the one or more PPG profiles. In some examples, the system300may determine that the additional PPG pulses satisfy the morphological value ranges of the representative PPG pulse320, and may therefore use the one or more additional PPG pulses to perform physiological measurements for the user (e.g., use the PPG pulses to determine physiological metrics such as heart rate, HRV, etc.). Alternatively, the system300may identify one or more additional PPG pulses that fail to match the PPG profiles320, and may therefore refrain from using such PPG pulses to perform physiological measurements.

FIG.4illustrates a block diagram400of a device405that supports techniques for identifying representative PPG pulses in accordance with aspects of the present disclosure. The device405may include an input module410, an output module415, and a wearable application420. The device405may also include a processor. Each of these components may be in communication with one another (e.g., via one or more buses).

The input module410may provide a means for receiving information such as packets, user data, control information, or any combination thereof associated with various information channels (e.g., control channels, data channels, information channels related to illness detection techniques). Information may be passed on to other components of the device405. The input module410may utilize a single antenna or a set of multiple antennas.

The output module415may provide a means for transmitting signals generated by other components of the device405. For example, the output module415may transmit information such as packets, user data, control information, or any combination thereof associated with various information channels (e.g., control channels, data channels, information channels related to illness detection techniques). In some examples, the output module415may be co-located with the input module410in a transceiver module. The output module415may utilize a single antenna or a set of multiple antennas.

For example, the wearable application420may include a data component425, a morphology component430, a PPG profile component435, an additional data component440, an additional morphology component445, a physiological metric component450, or any combination thereof. In some examples, the wearable application420, or various components thereof, may be configured to perform various operations (e.g., receiving, monitoring, transmitting) using or otherwise in cooperation with the input module410, the output module415, or both. For example, the wearable application420may receive information from the input module410, send information to the output module415, or be integrated in combination with the input module410, the output module415, or both to receive information, transmit information, or perform various other operations as described herein.

The data component425may be configured as or otherwise support a means for acquiring PPG data from a user via a wearable device, the PPG data comprising a first set of PPG pulses. The morphology component430may be configured as or otherwise support a means for comparing a plurality of morphological features of the plurality of PPG pulses based at least in part on acquiring the PPG data. The PPG profile component435may be configured as or otherwise support a means for determining one or more PPG profiles based at least in part on a comparison of the plurality of morphological features, wherein the one or more PPG profiles each comprise a plurality of morphological value ranges for the plurality of morphological features. The additional data component440may be configured as or otherwise support a means for acquiring additional PPG data from the user via the wearable device, the additional PPG data comprising a second set of PPG pulses. The additional morphology component445may be configured as or otherwise support a means for determining that one or more PPG pulses from the second set of PPG pulses match the one or more PPG profiles based at least in part on a plurality of morphological feature values of the one or more PPG pulses satisfying the plurality of morphological value ranges of the one or more PPG profiles. The physiological metric component450may be configured as or otherwise support a means for determining, using the one or more PPG pulses, one or more physiological metrics associated with the user based at least in part on the one or more PPG pulses matching the one or more PPG profiles.

FIG.5illustrates a block diagram500of a wearable application520that supports techniques for identifying representative PPG pulses in accordance with aspects of the present disclosure. The wearable application520may be an example of aspects of a wearable application or a wearable application420, or both, as described herein. The wearable application520, or various components thereof, may be an example of means for performing various aspects of techniques for identifying representative PPG pulses as described herein. For example, the wearable application520may include a data component525, a morphology component530, a PPG profile component535, an additional data component540, an additional morphology component545, a physiological metric component550, a physiological data component555, a first PPG profile component560, a first posture component565, a second PPG pulse component570, a first pressure component575, a PPG matching component580, a morphological value range component585, or any combination thereof. Each of these components may communicate, directly or indirectly, with one another (e.g., via one or more buses).

The data component525may be configured as or otherwise support a means for acquiring PPG data from a user via a wearable device, the PPG data comprising a first set of PPG pulses. The morphology component530may be configured as or otherwise support a means for comparing a plurality of morphological features of the plurality of PPG pulses based at least in part on acquiring the PPG data. The PPG profile component535may be configured as or otherwise support a means for determining one or more PPG profiles based at least in part on a comparison of the plurality of morphological features, wherein the one or more PPG profiles each comprise a plurality of morphological value ranges for the plurality of morphological features. The additional data component540may be configured as or otherwise support a means for acquiring additional PPG data from the user via the wearable device, the additional PPG data comprising a second set of PPG pulses. The additional morphology component545may be configured as or otherwise support a means for determining that one or more PPG pulses from the second set of PPG pulses match the one or more PPG profiles based at least in part on a plurality of morphological feature values of the one or more PPG pulses satisfying the plurality of morphological value ranges of the one or more PPG profiles. The physiological metric component550may be configured as or otherwise support a means for determining, using the one or more PPG pulses, one or more physiological metrics associated with the user based at least in part on the one or more PPG pulses matching the one or more PPG profiles.

In some examples, the data component525may be configured as or otherwise support a means for determining a first set of PPG profiles associated with the first wavelength. In some examples, the additional data component540may be configured as or otherwise support a means for determining a second set of PPG profiles associated with the second wavelength, wherein the one or more PPG profiles are included within the first set of PPG profiles, the second set of PPG profiles, or both, wherein determining the one or more PPG pulses match the one or more PPG profiles is based at least in part on determining the first set of PPG profiles, the second set of PPG profiles, or both.

In some examples, the physiological data component555may be configured as or otherwise support a means for acquiring physiological data from the user via the wearable device, the physiological data acquired during a first time interval that the user is in a first posture and a second time interval that the user is in a second posture. In some examples, the first PPG profile component560may be configured as or otherwise support a means for determining a first set of PPG profiles associated with the first posture and a second set of PPG profiles associated with the second posture based at least in part on the physiological data, wherein the first set of PPG profiles comprise the one or more PPG profiles. In some examples, the first posture component565may be configured as or otherwise support a means for determining that the user is in the first posture throughout a third time interval. In some examples, the second PPG pulse component570may be configured as or otherwise support a means for comparing the second set of PPG pulses acquired during the third time interval with the first set of PPG profiles based at least in part on determining that the user is in the first posture throughout the third time interval, wherein determining that the one or more PPG pulses match the one or more PPG profiles of the first set of PPG profiles is based at least in part on the comparison.

In some examples, the physiological data component555may be configured as or otherwise support a means for acquiring physiological data from the user via the wearable device, the physiological data acquired during a first time interval associated with a first pressure between the wearable device and a tissue of the user a second time interval associated with a second pressure between the wearable device and the tissue of the user. In some examples, the first PPG profile component560may be configured as or otherwise support a means for determining a first set of PPG profiles associated with the first pressure and a second set of PPG profiles associated with the second pressure based at least in part on the physiological data, wherein the first set of PPG profiles comprise the one or more PPG profiles. In some examples, the first pressure component575may be configured as or otherwise support a means for identifying that the wearable device is associated with the first pressure between the wearable device and the tissue throughout a third time interval. In some examples, the second PPG pulse component570may be configured as or otherwise support a means for comparing the second set of PPG pulses acquired during the third time interval with the first set of PPG profiles based at least in part on identifying the first pressure throughout the third time interval, wherein determining that the one or more PPG pulses match the one or more PPG profiles of the first set of PPG profiles is based at least in part on the comparison.

In some examples, identifying that the wearable device is associated with the first pressure throughout the third time interval based at least in part on additional physiological data acquired by the wearable device throughout the third time interval. In some examples, the additional physiological data comprises pressure data.

In some examples, to support determining the one or more PPG pulses match the one or more PPG profiles, the PPG matching component580may be configured as or otherwise support a means for determining that a plurality of consecutive PPG pulses match the one or more PPG profiles, wherein the one or more physiological metrics are based at least in part on the plurality of consecutive PPG pulses.

In some examples, the morphological value range component585may be configured as or otherwise support a means for determining the plurality of morphological value ranges for the plurality of morphological features based at least in part on the comparison.

In some examples, the plurality of morphological value ranges comprise a range of average morphological values for each morphological feature, a range of median morphological values for each morphological feature, a range of mode morphological values for each morphological feature, or any combination theorem.

In some examples, the plurality of morphological features comprise an amplitude of the first set of PPG pulses, a duration of the first set of PPG pulses, a slope of the first set of PPG pulses, a curvature of the first set of PPG pulses, a relationship between peaks of the first set of PPG pulses, or any combination thereof.

In some examples, the one or more physiological metrics comprise a heart rate metric, an HRV metric, a blood oxygen saturation metric, a blood pressure metric, an arterial reactivity metric, or any combination thereof.

In some examples, the wearable device comprises a wearable ring device.

In some examples, the wearable device is configured to acquire the PPG data, the additional PPG data, or both, based at least in part on arterial blood flow of the user.

FIG.6illustrates a diagram of a system600including a device605that supports techniques for identifying representative PPG pulses in accordance with aspects of the present disclosure. The device605may be an example of or include the components of a device405as described herein. The device605may include an example of a user device106, as described previously herein. The device605may include components for bi-directional communications including components for transmitting and receiving communications with a wearable device104and a server110, such as a wearable application620, a communication module610, an antenna615, a user interface component625, a database (application data)630, a memory635, and a processor640. These components may be in electronic communication or otherwise coupled (e.g., operatively, communicatively, functionally, electronically, electrically) via one or more buses (e.g., a bus645).

The communication module610may manage input and output signals for the device605via the antenna615. The communication module610may include an example of the communication module220-bof the user device106shown and described inFIG.2. In this regard, the communication module610may manage communications with the ring104and the server110, as illustrated inFIG.2. The communication module610may also manage peripherals not integrated into the device605. In some cases, the communication module610may represent a physical connection or port to an external peripheral. In some cases, the communication module610may utilize an operating system such as iOS®, ANDROID®, MS-DOS®, MS-WINDOWS®, OS/2®, UNIX®, LINUX®, or another known operating system. In other cases, the communication module610may represent or interact with a wearable device (e.g., ring104), modem, a keyboard, a mouse, a touchscreen, or a similar device. In some cases, the communication module610may be implemented as part of the processor640. In some examples, a user may interact with the device605via the communication module610, user interface component625, or via hardware components controlled by the communication module610.

In some cases, the device605may include a single antenna615. However, in some other cases, the device605may have more than one antenna615, which may be capable of concurrently transmitting or receiving multiple wireless transmissions. The communication module610may communicate bi-directionally, via the one or more antennas615, wired, or wireless links as described herein. For example, the communication module610may represent a wireless transceiver and may communicate bi-directionally with another wireless transceiver. The communication module610may also include a modem to modulate the packets, to provide the modulated packets to one or more antennas615for transmission, and to demodulate packets received from the one or more antennas615.

The user interface component625may manage data storage and processing in a database630. In some cases, a user may interact with the user interface component625. In other cases, the user interface component625may operate automatically without user interaction. The database630may be an example of a single database, a distributed database, multiple distributed databases, a data store, a data lake, or an emergency backup database.

The memory635may include RAM and ROM. The memory635may store computer-readable, computer-executable software including instructions that, when executed, cause the processor640to perform various functions described herein. In some cases, the memory635may contain, among other things, a BIOS which may control basic hardware or software operation such as the interaction with peripheral components or devices.

The processor640may include an intelligent hardware device, (e.g., a general-purpose processor, a DSP, a CPU, a microcontroller, an ASIC, an FPGA, a programmable logic device, a discrete gate or transistor logic component, a discrete hardware component, or any combination thereof). In some cases, the processor640may be configured to operate a memory array using a memory controller. In other cases, a memory controller may be integrated into the processor640. The processor640may be configured to execute computer-readable instructions stored in a memory635to perform various functions (e.g., functions or tasks supporting a method and system for sleep staging algorithms).

For example, the wearable application620may be configured as or otherwise support a means for acquiring PPG data from a user via a wearable device, the PPG data comprising a first set of PPG pulses. The wearable application620may be configured as or otherwise support a means for comparing a plurality of morphological features of the plurality of PPG pulses based at least in part on acquiring the PPG data. The wearable application620may be configured as or otherwise support a means for determining one or more PPG profiles based at least in part on a comparison of the plurality of morphological features, wherein the one or more PPG profiles each comprise a plurality of morphological value ranges for the plurality of morphological features. The wearable application620may be configured as or otherwise support a means for acquiring additional PPG data from the user via the wearable device, the additional PPG data comprising a second set of PPG pulses. The wearable application620may be configured as or otherwise support a means for determining that one or more PPG pulses from the second set of PPG pulses match the one or more PPG profiles based at least in part on a plurality of morphological feature values of the one or more PPG pulses satisfying the plurality of morphological value ranges of the one or more PPG profiles. The wearable application620may be configured as or otherwise support a means for determining, using the one or more PPG pulses, one or more physiological metrics associated with the user based at least in part on the one or more PPG pulses matching the one or more PPG profiles.

By including or configuring the wearable application620in accordance with examples as described herein, the device605may support techniques for improved accuracy of physiological measurements. In some examples, the device605may support techniques to determine which PPG pulses may be used to perform measurements. As such, these techniques may collect multiple PPG pulses and determine one or more representative PPG pulses that accurately represent the physiological metrics of the user. Alternatively, the device605may support techniques to remove one or more PPG pulses that fail to reflect accurate physiological metrics of the user.

The wearable application620may include an application (e.g., “app”), program, software, or other component which is configured to facilitate communications with a ring104, server110, other user devices106, and the like. For example, the wearable application620may include an application executable on a user device106which is configured to receive data (e.g., physiological data) from a ring104, perform processing operations on the received data, transmit and receive data with the servers110, and cause presentation of data to a user102.

FIG.7illustrates a flowchart showing a method700that supports techniques for identifying representative PPG pulses in accordance with aspects of the present disclosure. The operations of the method700may be implemented by a user device or its components as described herein. For example, the operations of the method700may be performed by a user device as described with reference toFIGS.1through6. In some examples, a user device may execute a set of instructions to control the functional elements of the user device to perform the described functions. Additionally, or alternatively, the user device may perform aspects of the described functions using special-purpose hardware.

At705, the method may include acquiring PPG data from a user via a wearable device, the PPG data comprising a first set of PPG pulses. The operations of705may be performed in accordance with examples as disclosed herein. In some examples, aspects of the operations of705may be performed by a data component525as described with reference toFIG.5.

At710, the method may include comparing a plurality of morphological features of the plurality of PPG pulses based at least in part on acquiring the PPG data. The operations of710may be performed in accordance with examples as disclosed herein. In some examples, aspects of the operations of710may be performed by a morphology component530as described with reference toFIG.5.

At715, the method may include determining one or more PPG profiles based at least in part on a comparison of the plurality of morphological features, where the one or more PPG profiles each comprise a plurality of morphological value ranges for the plurality of morphological features. The operations of715may be performed in accordance with examples as disclosed herein. In some examples, aspects of the operations of715may be performed by a PPG profile component535as described with reference toFIG.5.

At720, the method may include acquiring additional PPG data from the user via the wearable device, the additional PPG data comprising a second set of PPG pulses. The operations of720may be performed in accordance with examples as disclosed herein. In some examples, aspects of the operations of720may be performed by an additional data component540as described with reference toFIG.5.

At725, the method may include determining that one or more PPG pulses from the second set of PPG pulses match the one or more PPG profiles based at least in part on a plurality of morphological feature values of the one or more PPG pulses satisfying the plurality of morphological value ranges of the one or more PPG profiles. The operations of725may be performed in accordance with examples as disclosed herein. In some examples, aspects of the operations of725may be performed by an additional morphology component545as described with reference toFIG.5.

At730, the method may include determining, using the one or more PPG pulses, one or more physiological metrics associated with the user based at least in part on the one or more PPG pulses matching the one or more PPG profiles. The operations of730may be performed in accordance with examples as disclosed herein. In some examples, aspects of the operations of730may be performed by a physiological metric component550as described with reference toFIG.5.

FIG.8illustrates a flowchart showing a method800that supports techniques for identifying representative PPG pulses in accordance with aspects of the present disclosure. The operations of the method800may be implemented by a user device or its components as described herein. For example, the operations of the method800may be performed by a user device as described with reference toFIGS.1through6. In some examples, a user device may execute a set of instructions to control the functional elements of the user device to perform the described functions. Additionally, or alternatively, the user device may perform aspects of the described functions using special-purpose hardware.

At805, the method may include acquiring PPG data from a user via a wearable device, the PPG data comprising a first set of PPG pulses. The operations of805may be performed in accordance with examples as disclosed herein. In some examples, aspects of the operations of805may be performed by a data component525as described with reference toFIG.5.

At810, the method may include comparing a plurality of morphological features of the plurality of PPG pulses based at least in part on acquiring the PPG data. The operations of810may be performed in accordance with examples as disclosed herein. In some examples, aspects of the operations of810may be performed by a morphology component530as described with reference toFIG.5.

At815, the method may include determining one or more PPG profiles based at least in part on a comparison of the plurality of morphological features, where the one or more PPG profiles each comprise a plurality of morphological value ranges for the plurality of morphological features. The operations of815may be performed in accordance with examples as disclosed herein. In some examples, aspects of the operations of815may be performed by a PPG profile component535as described with reference toFIG.5.

At820, the method may include determining a first set of PPG profiles associated with the first wavelength. The operations of820may be performed in accordance with examples as disclosed herein. In some examples, aspects of the operations of820may be performed by a data component525as described with reference toFIG.5.

At825, the method may include determining a second set of PPG profiles associated with the second wavelength, where the one or more PPG profiles are included within the first set of PPG profiles, the second set of PPG profiles, or both. The operations of825may be performed in accordance with examples as disclosed herein. In some examples, aspects of the operations of825may be performed by an additional data component540as described with reference toFIG.5.

At830, the method may include acquiring additional PPG data from the user via the wearable device, the additional PPG data comprising a second set of PPG pulses. The operations of830may be performed in accordance with examples as disclosed herein. In some examples, aspects of the operations of830may be performed by an additional data component540as described with reference toFIG.5.

At835, the method may include determining that one or more PPG pulses from the second set of PPG pulses match the one or more PPG profiles based at least in part on a plurality of morphological feature values of the one or more PPG pulses satisfying the plurality of morphological value ranges of the one or more PPG profiles, where determining the one or more PPG pulses match the one or more PPG profiles is based at least in part on determining the first set of PPG profiles, the second set of PPG profiles, or both. The operations of835may be performed in accordance with examples as disclosed herein. In some examples, aspects of the operations of835may be performed by an additional morphology component545as described with reference toFIG.5.

At840, the method may include determining, using the one or more PPG pulses, one or more physiological metrics associated with the user based at least in part on the one or more PPG pulses matching the one or more PPG profiles. The operations of840may be performed in accordance with examples as disclosed herein. In some examples, aspects of the operations of840may be performed by a physiological metric component550as described with reference toFIG.5.

A method is described. The method may include acquiring PPG data from a user via a wearable device, the PPG data comprising a first set of PPG pulses, comparing a plurality of morphological features of the plurality of PPG pulses based at least in part on acquiring the PPG data, determining one or more PPG profiles based at least in part on a comparison of the plurality of morphological features, wherein the one or more PPG profiles each comprise a plurality of morphological value ranges for the plurality of morphological features, acquiring additional PPG data from the user via the wearable device, the additional PPG data comprising a second set of PPG pulses, determining that one or more PPG pulses from the second set of PPG pulses match the one or more PPG profiles based at least in part on a plurality of morphological feature values of the one or more PPG pulses satisfying the plurality of morphological value ranges of the one or more PPG profiles, and determining, using the one or more PPG pulses, one or more physiological metrics associated with the user based at least in part on the one or more PPG pulses matching the one or more PPG profiles.

An apparatus is described. The apparatus may include a processor, memory coupled with the processor, and instructions stored in the memory. The instructions may be executable by the processor to cause the apparatus to acquire PPG data from a user via a wearable device, the PPG data comprising a first set of PPG pulses, compare a plurality of morphological features of the plurality of PPG pulses based at least in part on acquiring the PPG data, determine one or more PPG profiles based at least in part on a comparison of the plurality of morphological features, wherein the one or more PPG profiles each comprise a plurality of morphological value ranges for the plurality of morphological features, acquire additional PPG data from the user via the wearable device, the additional PPG data comprising a second set of PPG pulses, determine that one or more PPG pulses from the second set of PPG pulses match the one or more PPG profiles based at least in part on a plurality of morphological feature values of the one or more PPG pulses satisfying the plurality of morphological value ranges of the one or more PPG profiles, and determine, using the one or more PPG pulses, one or more physiological metrics associated with the user based at least in part on the one or more PPG pulses matching the one or more PPG profiles.

Another apparatus is described. The apparatus may include means for acquiring PPG data from a user via a wearable device, the PPG data comprising a first set of PPG pulses, means for comparing a plurality of morphological features of the plurality of PPG pulses based at least in part on acquiring the PPG data, means for determining one or more PPG profiles based at least in part on a comparison of the plurality of morphological features, wherein the one or more PPG profiles each comprise a plurality of morphological value ranges for the plurality of morphological features, means for acquiring additional PPG data from the user via the wearable device, the additional PPG data comprising a second set of PPG pulses, means for determining that one or more PPG pulses from the second set of PPG pulses match the one or more PPG profiles based at least in part on a plurality of morphological feature values of the one or more PPG pulses satisfying the plurality of morphological value ranges of the one or more PPG profiles, and means for determining, using the one or more PPG pulses, one or more physiological metrics associated with the user based at least in part on the one or more PPG pulses matching the one or more PPG profiles.

A non-transitory computer-readable medium storing code is described. The code may include instructions executable by a processor to acquire PPG data from a user via a wearable device, the PPG data comprising a first set of PPG pulses, compare a plurality of morphological features of the plurality of PPG pulses based at least in part on acquiring the PPG data, determine one or more PPG profiles based at least in part on a comparison of the plurality of morphological features, wherein the one or more PPG profiles each comprise a plurality of morphological value ranges for the plurality of morphological features, acquire additional PPG data from the user via the wearable device, the additional PPG data comprising a second set of PPG pulses, determine that one or more PPG pulses from the second set of PPG pulses match the one or more PPG profiles based at least in part on a plurality of morphological feature values of the one or more PPG pulses satisfying the plurality of morphological value ranges of the one or more PPG profiles, and determine, using the one or more PPG pulses, one or more physiological metrics associated with the user based at least in part on the one or more PPG pulses matching the one or more PPG profiles.

Some examples of the method, apparatuses, and non-transitory computer-readable medium described herein may further include operations, features, means, or instructions for determining a first set of PPG profiles associated with the first wavelength and determining a second set of PPG profiles associated with the second wavelength, wherein the one or more PPG profiles may be included within the first set of PPG profiles, the second set of PPG profiles, or both, wherein determining the one or more PPG pulses match the one or more PPG profiles may be based at least in part on determining the first set of PPG profiles, the second set of PPG profiles, or both.

Some examples of the method, apparatuses, and non-transitory computer-readable medium described herein may further include operations, features, means, or instructions for acquiring physiological data from the user via the wearable device, the physiological data acquired during a first time interval that the user may be in a first posture and a second time interval that the user may be in a second posture, determining a first set of PPG profiles associated with the first posture and a second set of PPG profiles associated with the second posture based at least in part on the physiological data, wherein the first set of PPG profiles comprise the one or more PPG profiles, determining that the user may be in the first posture throughout a third time interval, and comparing the second set of PPG pulses acquired during the third time interval with the first set of PPG profiles based at least in part on determining that the user may be in the first posture throughout the third time interval, wherein determining that the one or more PPG pulses match the one or more PPG profiles of the first set of PPG profiles may be based at least in part on the comparison.

Some examples of the method, apparatuses, and non-transitory computer-readable medium described herein may further include operations, features, means, or instructions for acquiring physiological data from the user via the wearable device, the physiological data acquired during a first time interval associated with a first pressure between the wearable device and a tissue of the user a second time interval associated with a second pressure between the wearable device and the tissue of the user, determining a first set of PPG profiles associated with the first pressure and a second set of PPG profiles associated with the second pressure based at least in part on the physiological data, wherein the first set of PPG profiles comprise the one or more PPG profiles, identifying that the wearable device may be associated with the first pressure between the wearable device and the tissue throughout a third time interval, and comparing the second set of PPG pulses acquired during the third time interval with the first set of PPG profiles based at least in part on identifying the first pressure throughout the third time interval, wherein determining that the one or more PPG pulses match the one or more PPG profiles of the first set of PPG profiles may be based at least in part on the comparison.

Some examples of the method, apparatuses, and non-transitory computer-readable medium described herein may further include operations, features, means, or instructions for identifying that the wearable device may be associated with the first pressure throughout the third time interval based at least in part on additional physiological data acquired by the wearable device throughout the third time interval and the additional physiological data comprises pressure data.

In some examples of the method, apparatuses, and non-transitory computer-readable medium described herein, determining the one or more PPG pulses match the one or more PPG profiles may include operations, features, means, or instructions for determining that a plurality of consecutive PPG pulses match the one or more PPG profiles, wherein the one or more physiological metrics may be based at least in part on the plurality of consecutive PPG pulses.

Some examples of the method, apparatuses, and non-transitory computer-readable medium described herein may further include operations, features, means, or instructions for determining the plurality of morphological value ranges for the plurality of morphological features based at least in part on the comparison.

In some examples of the method, apparatuses, and non-transitory computer-readable medium described herein, the plurality of morphological value ranges comprise a range of average morphological values for each morphological feature, a range of median morphological values for each morphological feature, a range of mode morphological values for each morphological feature, or any combination theorem.

In some examples of the method, apparatuses, and non-transitory computer-readable medium described herein, the plurality of morphological features comprise an amplitude of the first set of PPG pulses, a duration of the first set of PPG pulses, a slope of the first set of PPG pulses, a curvature of the first set of PPG pulses, a relationship between peaks of the first set of PPG pulses, or any combination thereof.

In some examples of the method, apparatuses, and non-transitory computer-readable medium described herein, the one or more physiological metrics comprise a heart rate metric, an HRV metric, a blood oxygen saturation metric, a blood pressure metric, an arterial reactivity metric, or any combination thereof.

In some examples of the method, apparatuses, and non-transitory computer-readable medium described herein, the wearable device comprises a wearable ring device.

In some examples of the method, apparatuses, and non-transitory computer-readable medium described herein, the wearable device may be configured to acquire the PPG data, the additional PPG data, or both, based at least in part on arterial blood flow of the user.