Bidirectional sharing technology based on wearable device data

Abstract

Methods, systems, and devices are described for bi-directional sharing based on wearable device data. The system may receive instructions from the users in the group to send and receive physiological data between the users in the group. The system may then aggregate user-specific physiological data for each respective user in the group, where the physiological data is collected via a wearable device associated with each respective user. The system may then generate a score indicative of a physiological metric representative of the group of users based on the acquired physiological data for each user, and then may distribute the calculated score to each user in the group.

Description

[0001] Cross-referencing

[0002] This patent application claims priority to the following applications: U.S. Patent Application No. 18 / 402,285, filed January 2, 2024, by Saarinen et al., entitled “TECHNIQUES FOR TWO-WAY SHARING OF WEARABLE-BASED DATA”; and U.S. Provisional Patent Application No. 63 / 480,863, filed January 20, 2023, by Saarinen et al., entitled “TECHNIQUES FOR TWO-WAY SHARING OF WEARABLE-BASED DATA”, which have been assigned to the assignee of this application and are expressly incorporated herein by reference. Technical Field

[0003] The following content relates to wearable devices and data processing, including two-way sharing technologies based on wearable device data. Background Technology

[0004] Some wearable devices can be configured to collect data from users so that the user's device can determine various health and wellness information based on this data. There may be a desire to improve the methods for sharing health and wellness information among users. Attached Figure Description

[0005] Figure 1 Examples of systems supporting bidirectional data sharing technology based on wearable devices, according to various aspects of this disclosure, are shown.

[0006] Figure 2 Examples of systems supporting bidirectional data sharing technology based on wearable devices, according to various aspects of this disclosure, are shown.

[0007] Figure 3 Examples of systems supporting bidirectional data sharing technology based on wearable devices, according to various aspects of this disclosure, are shown.

[0008] Figure 4 An example of a process flow supporting a two-way data sharing technology based on wearable devices, according to various aspects of this disclosure, is shown.

[0009] Figure 5 A block diagram of an apparatus supporting a two-way data sharing technology based on wearable devices, according to various aspects of this disclosure, is shown.

[0010] Figure 6A block diagram is shown that supports a wearable application based on a two-way sharing technology of wearable device data according to various aspects of this disclosure.

[0011] Figure 7 A diagram of a system including a device supporting a two-way sharing technology based on wearable device data is shown according to various aspects of this disclosure.

[0012] Figure 8 A flowchart is shown illustrating a method for supporting bidirectional sharing of wearable device data according to various aspects of this disclosure. Detailed Implementation

[0013] Users can wear wearable devices, such as wearable rings, that collect data from the user (such as physiological data) to determine various health and wellness information. Additionally, some users may wish to receive health and wellness information from other users (such as parents, grandparents, spouses, children, close friends, etc.). However, indiscriminately sharing large amounts of health and wellness information can infringe on privacy or make it difficult for users to view and analyze, reducing the operability and therefore the value of the shared information. This issue becomes even more complex when a user wishes to receive health and wellness information from multiple users (such as multiple family members). Therefore, a user's ability to interact with, manage, or support groups in terms of health and wellness may be limited.

[0014] According to the techniques described herein, data from a group of people can be acquired and used to generate one or more comprehensive health and wellness scores or insights for that group, which can then be used to generate one or more recommendations for that group. For example, a user can join a user group that has been authorized to share health and wellness data among users (e.g., via user devices) so that data collected by the user's wearable devices can be used to generate comprehensive health and wellness information for that group. The comprehensive score calculated for the group can be used to effectively convey information about the group's overall health status, overall mood, or feelings. In some examples, the group's comprehensive health and wellness information can also serve as the basis for generating one or more recommendations for that group. Such techniques can allow for improved community interaction and support. Furthermore, by aggregating user-specific data and generating comprehensive health or wellness scores representing the entire group, the techniques described herein can enhance users' ability to view and process health and wellness data for the entire user group as well as individual users within the group.

[0015] Alternatively, individual-specific data for the group can be displayed on an individual basis, enabling other members of the group to react (e.g., offer encouragement or suggestions) or adjust their own behavior in response to viewing the individual-specific data of others. For example, when displaying the first user's individual-specific health and wellness information to a second user, the second user's device can prompt the second user to send a message (e.g., text, emoji) to the first user based on that individual-specific health and wellness information.

[0016] The various aspects of this disclosure are initially described in the context of systems that support the collection of physiological data from users via wearable devices. These aspects will be further illustrated and described in conjunction with systems and processes. Furthermore, these aspects will be illustrated and described in conjunction with apparatus diagrams, system diagrams, and flowcharts related to wearable device-based bidirectional data sharing technologies.

[0017] Figure 1 An example of a system 100 supporting a two-way data sharing technology based on wearable devices, according to various aspects of this disclosure, is shown. System 100 includes multiple electronic devices (e.g., wearable device 104, user device 106) that can be worn and / or operated by one or more users 102. System 100 further includes a network 108 and one or more servers 110.

[0018] Electronic devices may include any electronic devices known in the art, including wearable device 104 (e.g., a ring wearable device, a watch wearable device, etc.) and user device 106 (e.g., a smartphone, a laptop computer, a tablet computer). Electronic devices associated with a corresponding user 102 may include one or more of the following functions: 1) measuring physiological data; 2) storing the measured data; 3) processing the data; 4) providing output (e.g., via a GUI) to user 102 based on the processed data; and 5) communicating data with each other and / or with other computing devices. Different electronic devices may perform one or more of these functions.

[0019] Example wearable device 104 may include wearable computing devices, such as a ring computing device (hereinafter referred to as a "ring") configured to be worn on the finger of user 102, a wrist computing device (e.g., a smartwatch, fitness band, or bracelet) configured to be worn on the wrist of user 102, and / or a head-mounted computing device (e.g., glasses / goggles). Wearable device 104 may also include cords, straps (e.g., flexible or non-flexible cords or straps), hook and loop sensors, etc., that can be positioned in other locations, such as a band around the head (e.g., a forehead band), arms (e.g., a forearm band and / or a double headband), and / or legs (e.g., a thigh or calf band), behind the ears, under the armpits, etc. Wearable device 104 may also be attached to or included in clothing items. For example, wearable device 104 may be included in a pocket and / or pouch on clothing. As another example, wearable device 104 may be clipped and / or pinned to clothing, or may otherwise be held near user 102. Exemplary clothing items may include, but are not limited to, hats, shirts, gloves, trousers, socks, outerwear (e.g., jackets), and underwear. In some implementations, wearable device 104 may be included in other types of equipment, such as training / sports equipment used during physical activity. For example, wearable device 104 may be attached to or included in a bicycle, skis, tennis racket, golf club, and / or training weights.

[0020] Many aspects of this disclosure can be described in the context of the ring wearable device 104. Therefore, unless otherwise indicated herein, the terms "ring 104," "wearable device 104," and similar terms may be used interchangeably. However, the use of the term "ring 104" should not be considered limiting, as it is contemplated herein that various aspects of this disclosure can be implemented using other wearable devices (e.g., watch wearable devices, necklace wearable devices, bracelet wearable devices, earring wearable devices, ankle wearable devices, etc.).

[0021] In some aspects, user equipment 106 may include handheld mobile computing devices, such as smartphones and tablets. User equipment 106 may also include personal computers, such as laptops and desktops. Other example user equipment 106 may include server computing devices capable of communicating with other electronic devices, such as via the Internet. In some implementations, the computing device may include medical devices, such as external wearable computing devices (e.g., Holter monitors). Medical devices may also include implantable medical devices, such as pacemakers and defibrillators. Other example user equipment 106 may include home computing devices, such as Internet of Things (IoT) devices (e.g., IoT devices), smart TVs, smart speakers, smart displays (e.g., video call displays), hubs (e.g., wireless communication hubs), security systems, smart appliances (e.g., thermostats and refrigerators), and fitness equipment.

[0022] Some electronic devices (e.g., wearable device 104, user device 106) can measure physiological parameters of the corresponding user 102, such as photoplethysmography waveforms, continuous skin temperature, pulse waveforms, respiratory rate, heart rate, heart rate variability (HRV), body motion monitoring, skin conductance response, pulse oxygen saturation, and / or other physiological parameters. Some electronic devices that measure physiological parameters may also perform some / all of the calculations described herein. Some electronic devices may not measure physiological parameters but may perform some / all of the calculations described herein. For example, a ring (e.g., wearable device 104), a mobile device application, or a server computing device may process physiological data received from other devices.

[0023] In some implementations, user 102 may operate or be associated with multiple electronic devices, some of which can measure physiological parameters, and some of which can process the measured physiological parameters. In some implementations, user 102 may have a loop for measuring physiological parameters (e.g., wearable device 104). User 102 may also have or be associated with user device 106 (e.g., a mobile device, a smartphone), wherein wearable device 104 and user device 106 are communicatively coupled to each other. In some cases, user device 106 may receive data from wearable device 104 and perform some / all of the calculations described herein. In some implementations, user device 106 may also measure physiological parameters described herein, such as motion / activity parameters.

[0024] For example, such as Figure 1 As shown, a first user 102-a (user 1) can operate, or be associated with, a wearable device 104-a (e.g., ring 104-a) and a user device 106-a that can operate as described herein. In this example, the user device 106-a associated with user 102-a can process / store physiological parameters measured by ring 104-a. In contrast, a second user 102-b (user 2) can be associated with ring 104-b, a watch-wearable device 104-c (e.g., watch 104-c), and user device 106-b, wherein the user device 106-b associated with user 102-b can process / store physiological parameters measured by ring 104-b and / or watch 104-c. Furthermore, an nth user 102-n (user N) can be associated with an arrangement of electronic devices (e.g., ring 104-n, user device 106-n) described herein. In some respects, wearable devices 104 (e.g., ring 104, watch 104) and other electronic devices can be communicatively coupled to user equipment 106 of the corresponding user 102 via Bluetooth, Wi-Fi and other wireless protocols.

[0025] In some implementations, the ring 104 of system 100 (e.g., wearable device 104) can be configured to collect physiological data from the corresponding user 102 based on arterial blood flow within the user's finger. Specifically, the ring 104 can utilize one or more light-emitting components (such as LEDs (e.g., red LEDs, green LEDs)) emitting light on the palmar side of the user's finger to collect physiological data based on arterial blood flow within the user's finger. Generally, the terms light-emitting component, light-emitting element, and similar terms may include, but are not limited to, LEDs, micro LEDs, mini LEDs, laser diodes (LDs) (e.g., vertical-cavity surface-emitting lasers (VCSELs)), etc.

[0026] In some cases, system 100 can be configured to collect physiological data from a corresponding user 102 based on blood flow diffusing into the skin's microvascular bed, which has capillaries and arterioles. For example, system 100 can collect PPG data based on the measured blood volume diffusing into the microvascular system of capillaries and arterioles. In some embodiments, ring 104 can use a combination of both green and red LEDs to acquire physiological data. Physiological data can include any physiological data known in the art, including but not limited to temperature data, accelerometer data (e.g., movement / exercise data), heart rate data, HRV data, blood oxygen level data, or any combination thereof.

[0027] The use of both green and red LEDs offers several advantages over other solutions, as they have been found to have their own distinct strengths in acquiring physiological data under different conditions (e.g., bright / dark, active / inactive) and through different parts of the body. For example, green LEDs have been found to exhibit better performance during exercise. Furthermore, wearable devices using multiple LEDs (e.g., green and red LEDs) distributed around ring 104 have been found to exhibit superior performance compared to wearable devices using LEDs positioned close to each other (such as within a watch). Additionally, blood vessels in the fingers (e.g., arteries, capillaries) are more easily accessed via LEDs than those in the wrist. Specifically, arteries in the wrist are located at the base of the wrist (e.g., the palmar side of the wrist), meaning that only capillaries are accessible at the top of the wrist (e.g., the back of the wrist on the palmar side), where wearable watches and similar devices are typically worn. Accordingly, it has been found that using LEDs and other sensors within the ring 104 exhibits superior performance compared to wearable devices worn on the wrist, because the ring 104 has greater access to arteries (compared to capillaries), resulting in stronger signals and more valuable physiological data.

[0028] Electronic devices of system 100 (e.g., user equipment 106, wearable device 104) can be communicatively coupled to one or more servers 110 via wired or wireless communication protocols. For example, such as Figure 1 As shown, electronic devices (e.g., user equipment 106) can be communicatively coupled to one or more servers 110 via network 108. Network 108 can implement Transmission Control Protocol and Internet Protocol (TCP / IP) such as the Internet, or it can implement other network 108 protocols. The network connection between network 108 and the corresponding electronic device can facilitate data transmission via email, web, text messaging, mail, or any other suitable form of interaction within computer network 108. For example, in some implementations, a ring 104-a associated with a first user 102-a can be communicatively coupled to user equipment 106-a, wherein user equipment 106-a is communicatively coupled to server 110 via network 108. In additional or alternative cases, wearable device 104 (e.g., ring 104, watch 104) can be directly communicatively coupled to network 108.

[0029] System 100 can provide on-demand database services between user equipment 106 and one or more servers 110. In some cases, server 110 can receive data from user equipment 106 via network 108, and can store and analyze that data. Similarly, server 110 can provide data to user equipment 106 via network 108. In some cases, server 110 may be located in one or more data centers. Server 110 can be used for data storage, management, and processing. In some implementations, server 110 may provide a web-based interface to user equipment 106 via a web browser.

[0030] In some respects, system 100 can detect the duration of user 102's sleep and categorize the duration of user 102's sleep into one or more sleep stages (e.g., sleep stage classification). For example, as... Figure 1As shown, user 102-a can be associated with wearable device 104-a (e.g., ring 104-a) and user device 106-a. In this example, ring 104-a can collect physiological data associated with user 102-a, including temperature, heart rate, HRV, respiratory rate, etc. In some aspects, the data collected by ring 104-a can be fed into a machine learning classifier, which is configured to determine the time period during which user 102-a is asleep (or previously asleep). Furthermore, the machine learning classifier can be configured to classify the time period into different sleep stages, including awake sleep, rapid eye movement (REM) sleep, light sleep (non-REM (NREM)), and deep sleep (NREM). In some aspects, the classified sleep stages can be displayed to user 102-a via the GUI of user device 106-a. The sleep stage classification can be used to provide user 102-a with feedback on the user's sleep patterns, such as recommended sleep times, recommended wake-up times, etc. Furthermore, in some implementations, the sleep stage classification technique described in this paper can be used to calculate scores for the corresponding user, such as sleep score, readiness score, etc.

[0031] In some respects, system 100 can leverage features derived from circadian rhythms to further improve physiological data collection, data processing procedures, and other techniques described herein. The term circadian rhythm can refer to the natural internal processes that regulate an individual's sleep-wake cycle, which repeats approximately every 24 hours. In this regard, the techniques described herein can utilize circadian rhythm regulation models to improve physiological data collection, analysis, and data processing. For example, a circadian rhythm regulation model, along with physiological data collected from user 102-a via wearable device 104-a, can be fed into a machine learning classifier. In this example, the circadian rhythm regulation model can be configured to "weight" or regulate physiological data collected throughout the user's natural, approximately 24-hour circadian rhythm. In some implementations, the system can initially start with a "baseline" circadian rhythm regulation model and can modify the baseline model using physiological data collected from each user 102 to generate a customized, personalized circadian rhythm regulation model specific to each respective user 102.

[0032] In some respects, System 100 can utilize other circadian rhythms to further improve the collection, analysis, and processing of physiological data through phases of these other rhythms. For example, if a weekly rhythm is detected within an individual's baseline data, the model can be configured to adjust the "weights" of the data by the days within that week. Circadian rhythms that may require adjustment of the model in this manner include: 1) ultradian rhythms (faster than daily rhythms, including sleep cycles during sleep and oscillations in physiological variables measured during waking periods ranging from less than an hour to several hours in cycle time); 2) diurnal rhythms; 3) non-endogenous daily rhythms that are applied over diurnal rhythms, such as in a work schedule; 4) weekly rhythms, or other exogenously applied artificial time cycles (e.g., a 12-day rhythm can be used in a hypothetical culture with a "week" of 12 days); 5) multi-day ovarian rhythms in women and spermatogenesis rhythms in men; 6) lunar rhythms (associated with individuals living in low or no artificial light); and 7) seasonal rhythms.

[0033] Biorhythms are not always resting rhythms. For example, many women experience variability in ovarian cycle length between cycles, and even within a single user, it is not expected that superdial rhythms will occur at exactly the same time or cycle over several days. Thus, signal processing techniques sufficient to quantify frequency components while maintaining temporal resolution of these rhythms in physiological data can be used to improve the detection of these rhythms, assign phases of each rhythm to each moment measured, and thereby modify regulatory models and comparisons of time intervals. Biorhythm regulatory models and parameters can be added, in linear or nonlinear combinations as appropriate, to more accurately capture the dynamic physiological baseline of an individual or group of individuals.

[0034] In some examples, user device 106 of user 102 may receive information collected by wearable devices of other users 102 so that user 102 can view information about other users 102. However, in some cases, user device 106 may process and display this information on a user-by-user basis, which may hinder user 102 from having a holistic understanding of the health and well-being of other users as a group (e.g., a sports team, a family unit, a work group). Furthermore, the large amount of data received from other users 106 in the group may be difficult for user 102 to view and parse, reducing the operability of the received data and thus diminishing its value. Therefore, user 102 may not be able to manage, interact with, or support the group in a manner that takes into account the overall health and well-being of the group.

[0035] According to the techniques described herein, user device 106 can receive user-specific information collected by wearable device 104 of an authorized user group and generate comprehensive health and wellness information for that user group based on that information. To receive information from other users in the group, user device 106 can authorize the sharing of information collected for user 102 of user device 106 (e.g., a user can join or create / start the group and exchange information with other members within the group). While described in relation to a single group, user 102 can belong to multiple groups, each with its own comprehensive scores and insights generated based on information collected by wearable device 104 of users within that group. In some examples, user groups authorized to share information within the group may be referred to as “circles,” “trust circles,” or other suitable terms.

[0036] Additionally or alternatively, user devices 106 within the group may display user-specific information on a per-user basis, allowing group members to focus on each other's health and wellness, which in turn can foster positive in-group interaction and inspire improved individual behaviors. For example, user devices 106 displaying user-specific sleep scores for group members may prompt users of user devices 106 to provide feedback on their sleep scores (e.g., via user device 106) and / or may recommend sleep-specific suggestions to users based on their sleep scores (e.g., go to bed earlier). User-specific health and wellness information sent to a second user that is specific to the first user may be compressed and displayed on the second user's user device in a manner different from that on the first user's user device (e.g., more easily parsed, more private).

[0037] Those skilled in the art will understand that one or more aspects of this disclosure can be implemented in system 100 to additionally or alternatively address problems beyond those described above. Furthermore, various aspects of this disclosure can provide technical improvements to "conventional" systems or processes as described herein. However, the specification and drawings only include exemplary technical improvements derived from implementing aspects of this disclosure and therefore do not represent all technical improvements provided within the scope of the claims.

[0038] Figure 2 An example of a system 200 supporting a two-way data sharing technology based on wearable devices, according to various aspects of this disclosure, is shown. System 200 may implement or be implemented by system 100. Specifically, system 200 shows examples of a ring 104 (e.g., wearable device 104), user equipment 106, and server 110, as referenced. Figure 1 As described.

[0039] In some aspects, the ring 104 can be configured to be worn on a user's finger, and when worn on the user's finger, it can determine one or more user physiological parameters. Example measurements and determinations may include, but are not limited to, user skin temperature, pulse waveform, respiratory rate, heart rate, HRV, blood oxygen level, etc.

[0040] System 200 further includes user equipment 106 (e.g., a smartphone) that communicates with ring 104. For example, ring 104 may communicate wirelessly and / or wiredly with user equipment 106. In some implementations, ring 104 may send measured and processed data (e.g., temperature data, photoplethysmography (PPG) data, motion / accelerometer data, ring input data, etc.) to user equipment 106. User equipment 106 may also send data to ring 104, such as ring 104 firmware / configuration updates. User equipment 106 may process data. In some implementations, user equipment 106 may transmit data to server 110 for processing and / or storage.

[0041] Ring 104 may include a housing 205, which may include an inner housing 205-a and an outer housing 205-b. In some aspects, the housing 205 of ring 104 may store or otherwise include various components of the ring, including but not limited to device electronics, power sources (e.g., battery 210, and / or capacitors), one or more substrates (e.g., printable circuit boards) interconnecting the device electronics and / or power sources, etc. Device electronics may include device modules (e.g., hardware / software), such as: processing module 230-a, memory 215, communication module 220-a, power module 225, etc. Device electronics may also include one or more sensors. Example sensors may include one or more temperature sensors 240, PPG sensor assemblies (e.g., PPG system 235), and one or more motion sensors 245.

[0042] These sensors may include association modules (not shown) configured to communicate with corresponding components / modules of ring 104 and generate signals associated with the corresponding sensors. In some aspects, each of the components / modules of ring 104 may be communicatively coupled to each other via a wired or wireless connection. Furthermore, ring 104 may include additional and / or alternative sensors or other components configured to collect physiological data from the user, including light sensors (e.g., LEDs), pulse oximeters, etc.

[0043] Reference Figure 2 The ring 104 shown and described is provided for illustrative purposes only. Therefore, the ring 104 may include, for example... Figure 2Additional or alternative components, such as those shown, can be manufactured. Other rings 104 can be manufactured to provide the functionality described herein. For example, rings 104 with fewer components (e.g., sensors) can be manufactured. In a particular example, a ring 104 can be manufactured having a single temperature sensor 240 (or other sensor), a power supply, and device electronics configured to read the single temperature sensor 240 (or other sensor). In another particular example, the temperature sensor 240 (or other sensor) can be attached to a user's finger (e.g., using a clamp, a spring-loaded clamp, etc.). In this case, the sensor can be wired to another computing device, such as a wrist-worn computing device that reads the temperature sensor 240 (or other sensor). In other examples, rings 104 can be manufactured to include additional sensors and processing capabilities.

[0044] Housing 205 may include one or more housing 205 assemblies. Housing 205 may include an outer housing 205-b assembly (e.g., a housing) and an inner housing 205-a assembly (e.g., a molded part). Housing 205 may be included in... Figure 2 Additional components not explicitly shown (e.g., additional layers). For example, in some implementations, ring 104 may include one or more insulating layers that electrically insulate device electronics and other conductive materials (e.g., electrical traces) from housing 205-b (e.g., metal housing 205-b). Housing 205 may provide structural support for device electronics, battery 210, one or more substrates, and other components. For example, housing 205 may protect device electronics, battery 210, and one or more substrates from mechanical forces such as pressure and shock. Housing 205 may also protect device electronics, battery 210, and one or more substrates from water and / or other chemicals.

[0045] The housing 205-b can be made of one or more materials. In some implementations, the housing 205-b may include a metal, such as titanium, which provides strength and abrasion resistance at a relatively light weight. The housing 205-b may also be made of other materials, such as polymers. In some implementations, the housing 205-b can be both protective and decorative.

[0046] The inner housing 205-a can be configured to engage with a user's finger. The inner housing 205-a can be formed of a polymer (e.g., a medical-grade polymer) or other materials. In some implementations, the inner housing 205-a can be transparent. For example, the inner housing 205-a can be transparent to light emitted by a PPG light-emitting diode (LED). In some implementations, the inner housing 205-a assembly can be molded onto the outer housing 205-b. For example, the inner housing 205-a can include a polymer molded (e.g., injection molded) to fit into the metal casing of the outer housing 205-b.

[0047] Ring 104 may include one or more substrates (not shown). Device electronics and battery 210 may be included on one or more substrates. For example, device electronics and battery 210 may be mounted on one or more substrates. Example substrates may include one or more printed circuit boards (PCBs), such as flexible PCBs (e.g., polyimide). In some implementations, electronics / battery 210 may include surface-mount devices (e.g., surface mount technology (SMT) devices) on a flexible PCB. In some implementations, one or more substrates (e.g., one or more flexible PCBs) may include electrical traces providing electrical communication between device electronics. The electrical traces may also connect battery 210 to device electronics.

[0048] Device electronics, battery 210, and substrate can be arranged in various ways within ring 104. In some implementations, a substrate including the device electronics may be mounted along the bottom (e.g., lower half) of ring 104, such that sensors (e.g., PPG system 235, temperature sensor 240, motion sensor 245, and other sensors) engage with the underside of a user's finger. In these implementations, battery 210 may be included along the top portion of ring 104 (e.g., on another substrate).

[0049] The various components / modules of ring 104 may include functions (e.g., circuits and other components) within ring 104. A module 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, a module may include analog circuitry (e.g., amplifier circuitry, filter circuitry, analog-to-digital converter circuitry, and / or other signal conditioning circuitry). A module may also include digital circuitry (e.g., combinational or sequential logic circuitry, memory circuitry, etc.).

[0050] The memory 215 (memory module) of ring 104 may include any volatile, non-volatile, magnetic, or electrical dielectric, such as random access memory (RAM), read-only memory (ROM), non-volatile RAM (NVRAM), electrically erasable programmable ROM (EEPROM), flash memory, or any other memory device. Memory 215 may store any data described herein. For example, memory 215 may be configured to store data collected by the corresponding sensors and PPG system 235 (e.g., motion data, temperature data, PPG data). Furthermore, memory 215 may include instructions that, when executed by one or more processing circuits, cause the module to perform various functions belonging to the modules herein. The device electronics of ring 104 described herein are merely example device electronics. Therefore, the type of electronic components used to implement the device electronics may vary based on design considerations.

[0051] The functionality of the modules belonging to ring 104 described herein can be embodied in one or more processors, hardware, firmware, software, or any combination thereof. Describing different features as modules is intended to highlight different functional aspects and does not necessarily imply that these modules must be implemented by separate hardware / software components. Rather, the functionality associated with one or more modules can be performed by separate hardware / software components or integrated within common hardware / software components.

[0052] The processing module 230-a of ring 104 may include one or more processors (e.g., processing units), microcontrollers, digital signal processors, system-on-a-chip (SoC), and / or other processing devices. The processing module 230-a communicates with modules contained within ring 104. For example, the processing module 230-a may send / receive data to / from modules and other components (such as sensors) of ring 104. As described herein, modules can be implemented from various circuit components. Therefore, a module may also be referred to as a circuit (e.g., communication circuitry and power supply circuitry).

[0053] Processing module 230-a can communicate with memory 215. Memory 215 may include computer-readable instructions that, when executed by processing module 230-a, cause processing module 230-a to perform various functions belonging to processing module 230-a herein. In some implementations, processing module 230-a (e.g., a microcontroller) may include additional features associated with other modules, such as communication functions provided by communication module 220-a (e.g., an integrated Bluetooth Low Energy transceiver) and / or additional onboard memory 215.

[0054] Communication module 220-a may include circuitry providing wireless and / or wired communication with user equipment 106 (e.g., communication module 220-b of user equipment 106). In some implementations, communication modules 220-a and 220-b may include wireless communication circuitry, such as Bluetooth circuitry and / or Wi-Fi circuitry. In some implementations, communication modules 220-a and 220-b may include wired communication circuitry, such as Universal Serial Bus (USB) communication circuitry. Using communication module 220-a, ring 104 and user equipment 106 may be configured to communicate with each other. Ring processing module 230-a may be configured to transmit / receive data to / from user equipment 106 via communication module 220-a. Example data may include, but is not limited to, motion data, temperature data, pulse waveform, heart rate data, HRV data, PPG data, and status updates (e.g., charging status, battery charge level, and / or ring 104 configuration settings). The ring processing module 230-a can also be configured to receive updates (e.g., software / firmware updates) and data from the user equipment 106.

[0055] Ring 104 may include a battery 210 (e.g., a rechargeable battery 210). Example battery 210 may include a lithium-ion or lithium-polymer type battery 210, but various battery options are possible. Battery 210 can be wirelessly charged. In some implementations, ring 104 may include a power source other than battery 210, such as a capacitor. The power source (e.g., battery 210 or capacitor) may have a curved geometry that matches the curves of ring 104. In some aspects, the charger or other power source may include additional sensors that can be used to collect data in addition to or supplement the data collected by ring 104 itself. Furthermore, the charger or other power source of ring 104 may act as user equipment 106, in which case the charger or other power source of ring 104 may be configured to receive data from ring 104, store and / or process data received from ring 104, and communicate data between ring 104 and server 110.

[0056] In some aspects, ring 104 includes a power module 225 that controls the charging of battery 210. For example, power module 225 may engage with an external wireless charger that charges battery 210 when engaged with ring 104. The charger may include a reference structure that mates with a reference structure of ring 104 to create a specified orientation of ring 104 during charging. Power module 225 may also regulate the voltage of device electronics, regulate the power output to device electronics, and monitor the state of charge of battery 210. In some implementations, battery 210 may include a protection circuit module (PCM) that protects battery 210 from high-current discharge, overvoltage during charging, and undervoltage during discharging. Power module 225 may also include electrostatic discharge (ESD) protection.

[0057] One or more temperature sensors 240 may be electrically coupled to processing module 230-a. Temperature sensors 240 may be configured to generate temperature signals (e.g., temperature data) indicating the temperature read or sensed by the temperature sensors 240. Processing module 230-a may determine the temperature of a user at the location of the temperature sensors 240. For example, in ring 104, the temperature data generated by the temperature sensors 240 may indicate the user's temperature at their finger (e.g., skin temperature). In some implementations, temperature sensors 240 may contact the user's skin. In other implementations, a portion of housing 205 (e.g., inner housing 205-a) may form a barrier (e.g., a thin thermally conductive barrier) between the temperature sensors 240 and the user's skin. In some implementations, the portion of ring 104 configured to contact the user's finger may have a thermally conductive portion and a thermally insulating portion. The thermally conductive portion conducts heat from the user's finger to the temperature sensors 240. The thermally insulating portion insulates portions of ring 104 (e.g., temperature sensors 240) from ambient temperature.

[0058] In some implementations, temperature sensor 240 can generate a digital signal (e.g., temperature data), which processing module 230-a can use to determine the temperature. As another example, if temperature sensor 240 includes a passive sensor, processing module 230-a (or temperature sensor 240 module) can measure the current / voltage generated by temperature sensor 240 and determine the temperature based on the measured current / voltage. Example temperature sensor 240 may include a thermistor (such as a negative temperature coefficient (NTC) thermistor) or other types of sensors, including resistors, transistors, diodes, and / or other electrical / electronic components.

[0059] Processing module 230-a can sample the user's temperature over time. For example, processing module 230-a can sample the user's temperature based on a sampling rate. An example sampling rate might include one sample per second, but processing module 230-a can be configured to sample the temperature signal at other sampling rates, higher or lower than one sample per second. In some implementations, processing module 230-a can continuously sample the user's temperature throughout the day and night. Sampling at a sufficient rate (e.g., one sample per second) throughout the day can provide enough temperature data for the analysis described herein.

[0060] Processing module 230-a can store the sampled temperature data in memory 215. In some implementations, processing module 230-a can process the sampled temperature data. For example, processing module 230-a can determine the average temperature value over a time period. In one example, processing module 230-a can determine the average temperature value for a minute by summing all temperature values ​​collected per minute and dividing by the number of samples in that minute. In a specific example where temperature is sampled at one sample per second, the average temperature can be the sum of all sampled temperatures for one minute divided by sixty seconds. Memory 215 can store the average temperature value over time. In some implementations, memory 215 can store the average temperature (e.g., one per minute) instead of the sampled temperatures to save memory 215.

[0061] The sampling rate, which can be stored in memory 215, can be configurable. In some implementations, the sampling rate can be the same throughout the day and night. In other implementations, the sampling rate can vary throughout the day / night. In some implementations, ring 104 can filter / reject temperature readings, such as large spikes in temperature that do not indicate physiological changes (e.g., temperature spikes from a hot shower). In some implementations, ring 104 can filter / reject temperature readings that may be unreliable due to other factors, such as excessive movement during exercise (e.g., as indicated by motion sensor 245)).

[0062] Ring 104 (e.g., a communication module) can transmit sampled temperature data and / or average temperature data to user equipment 106 for storage and / or further processing. User equipment 106 can transmit sampled temperature data and / or average temperature data to server 110 for storage and / or further processing.

[0063] Although ring 104 is shown as including a single temperature sensor 240, ring 104 may include multiple temperature sensors 240 in one or more locations, such as arranged along the inner housing 205-a near the user's finger. In some implementations, the temperature sensor 240 may be a standalone temperature sensor 240. Additionally or alternatively, one or more temperature sensors 240 may be included with other components (e.g., packaged together with other components), such as with an accelerometer and / or a processor.

[0064] Processing module 230-a can acquire and process data from multiple temperature sensors 240 in a manner similar to that described with respect to a single temperature sensor 240. For example, processing module 230 can sample, average, and store temperature data from each of the multiple temperature sensors 240 separately. In other examples, processing module 230-a can sample the sensors at different rates and average / store different values ​​for different sensors. In some implementations, processing module 230-a can be configured to determine a single temperature based on the average of two or more temperatures determined by two or more temperature sensors 240 at different locations on the finger.

[0065] Temperature sensors 240 on ring 104 can acquire the distal temperature at a user's finger (e.g., any finger). For example, one or more temperature sensors 240 on ring 104 can acquire the user's temperature from the underside of the finger or different locations on the finger. In some implementations, ring 104 can continuously acquire distal temperatures (e.g., at a sampling rate). While distal temperatures measured by ring 104 at a finger are described herein, other devices can measure temperatures at the same / different locations. In some cases, the distal temperature measured at a user's finger may differ from the temperature measured at the user's wrist or other external body locations. Furthermore, the distal temperature measured at a user's finger (e.g., "shell" temperature) may differ from the user's core temperature. Thus, ring 104 can provide a useful temperature signal that may not have been acquired at other internal / external locations of the body. In some cases, continuous temperature measurements at the finger can capture temperature fluctuations (e.g., small or large fluctuations) that may not be apparent in the core temperature. For example, continuous temperature measurements at the fingertips can capture temperature fluctuations minute by minute or hour by hour, providing additional insights that other temperature measurements in other parts of the body may not offer.

[0066] Ring 104 may include a PPG system 235. The PPG system 235 may include one or more light emitters that emit light. The PPG system 235 may also include one or more light receivers that receive light emitted by the one or more light emitters. The light receivers may generate a signal indicating the amount of light received by the light receivers (hereinafter referred to as a "PPG" signal). The light emitters may illuminate an area of ​​the user's finger. The PPG signal generated by the PPG system 235 may indicate blood perfusion in the illuminated area. For example, the PPG signal may indicate changes in blood volume in the illuminated area caused by the user's pulse pressure. Processing module 230-a may sample the PPG signal and determine the user's pulse waveform based on the PPG signal. Processing module 230-a may determine various physiological parameters, such as the user's respiratory rate, heart rate, HRV, oxygen saturation, and other circulatory parameters, based on the user's pulse waveform.

[0067] In some implementations, the PPG system 235 can be configured as a reflective PPG system 235, wherein one or more light receivers receive transmitted light reflected from an area of ​​the user's finger. In some implementations, the PPG system 235 can be configured as a transmissive PPG system 235, wherein one or more light emitters and one or more light receivers are arranged opposite each other such that light is directly transmitted through a portion of the user's finger to one or more light receivers.

[0068] The number and ratio of transmitters and receivers included in the PPG system 235 can vary. Example light transmitters may include light-emitting diodes (LEDs). Light transmitters may emit light in the infrared spectrum and / or other spectra. Example light receivers may include, but are not limited to, photoelectric sensors, phototransistors, and photodiodes. Light receivers can be configured to generate PPG signals in response to wavelengths received from the light transmitter. The positions of the transmitters and receivers can be changed. Furthermore, a single device may include a reflective and / or transmissive PPG system 235.

[0069] In some implementations, Figure 2 The PPG system 235 shown may include a reflective PPG system 235. In these implementations, the PPG system 235 may include a centrally located optical receiver (e.g., at the bottom of ring 104) and two optical emitters located on each side of the optical receiver. In this implementation, the PPG system 235 (e.g., the optical receiver) may generate a PPG signal based on light received from one or both of these optical emitters. In other implementations, other placements, combinations, and / or configurations of one or more optical emitters and / or optical receivers are considered.

[0070] Processing module 230-a can control one or both of the optical emitters to emit light while sampling the PPG signal generated by the optical receiver. In some implementations, processing module 230-a can cause the optical emitter with a stronger received signal to emit light while sampling the PPG signal generated by the optical receiver. For example, when the PPG signal is sampled at a sampling rate (e.g., 250 Hz), the selected optical emitter can emit light continuously.

[0071] Sampling the PPG signal generated by the PPG system 235 can produce a pulse waveform, which may be referred to as "PPG". The pulse waveform can indicate the blood pressure pair (vs) time over multiple cardiac cycles. The pulse waveform may include peak values ​​indicating cardiac cycles. Furthermore, the pulse waveform may include respiratory-induced changes that can be used to determine respiratory rate. In some implementations, the processing module 230-a may store the pulse waveform in memory 215. The processing module 230-a may process the pulse waveform when it is generated and / or when it is retrieved from memory 215 to determine the user physiological parameters described herein.

[0072] Processing module 230-a can determine a user's heart rate based on a pulse waveform. For example, processing module 230-a can determine the heart rate (e.g., in heartbeats per minute) based on the time between peaks in the pulse waveform. The time between peaks may be referred to as the inter-beat interval (IBI). Processing module 230-a can store the determined heart rate value and IBI value in memory 215.

[0073] Processing module 230-a can determine the HRV over time. For example, processing module 230-a can determine the HRV based on changes in the IBI. Processing module 230-a can store the HRV value over time in memory 215. Furthermore, processing module 230-a can determine the user's respiratory rate over time. For example, processing module 230-a can determine the respiratory rate based on the user's IBI value over a time period using frequency modulation, amplitude modulation, or baseline modulation. The respiratory rate can be calculated as breaths per minute or as another respiratory rate (e.g., breaths every 30 seconds). Processing module 230-a can store the user's respiratory rate value over time in memory 215.

[0074] Ring 104 may include one or more motion sensors 245, such as one or more accelerometers (e.g., 6-D accelerometers) and / or one or more gyroscopes. Motion sensors 245 may generate motion signals indicating the motion of the sensors. For example, ring 104 may include one or more accelerometers that generate acceleration signals indicating the acceleration of the accelerometers. As another example, ring 104 may include one or more gyroscope sensors that generate gyroscope signals indicating angular motion (e.g., angular velocity) and / or changes in orientation. Motion sensors 245 may be included in one or more sensor packages. An example accelerometer / gyroscope sensor is the Bosch BM1160 inertial microelectromechanical system (MEMS) sensor, which can measure angular rate and acceleration on three vertical axes.

[0075] Processing module 230-a can sample the motion signal at a sampling rate (e.g., 50 Hz) and determine the motion of ring 104 based on the sampled motion signal. For example, processing module 230-a can sample an acceleration signal to determine the acceleration of ring 104. As another example, processing module 230-a can sample a gyroscope signal to determine angular motion. In some implementations, processing module 230-a can store motion data in memory 215. The motion data may include sampled motion data and motion data calculated based on the sampled motion signal (e.g., acceleration and angle values).

[0076] Ring 104 can store various types of data described herein. For example, ring 104 can store temperature data, such as raw sampled temperature data and calculated temperature data (e.g., average temperature). As another example, ring 104 can store PPG signal data, such as pulse waveforms and data calculated based on pulse waveforms (e.g., heart rate values, IBI values, HRV values, and respiratory rate values). Ring 104 can also store motion data, such as sampled motion data indicating linear and angular motion.

[0077] Ring 104 or other computing devices can calculate and store additional values ​​based on the sampled / computed physiological data. For example, processing module 230 can calculate and store various metrics such as sleep metrics (e.g., sleep score), activity metrics, and readiness metrics. In some implementations, the additional value / metric may be referred to as a "derived value." Ring 104 or other computing / wearable devices can calculate various values / metrics related to movement. Example derived values ​​of movement data may include, but are not limited to, movement count values, regularity values, intensity values, metabolic equivalence (MET) of task values, and orientation values. Movement counts, regularity values, intensity values, and MET can indicate the amount of user movement over time (e.g., speed / acceleration). Orientation values ​​can indicate how ring 104 is oriented on the user's fingers and whether ring 104 is worn on the left or right hand.

[0078] In some implementations, motion counts and regularity values ​​can be determined by counting the number of acceleration peaks over one or more time periods (e.g., one or more time periods of 30 seconds to 1 minute). Intensity values ​​can indicate the number of motions and the associated intensity of the motions (e.g., acceleration values). Depending on the associated threshold acceleration value, intensity values ​​can be categorized as low, medium, and high. MET can be determined based on the intensity of motions during a time period (e.g., 30 seconds), the regularity / irregularity of the motions, and the number of motions associated with different intensities.

[0079] In some implementations, processing module 230-a can compress the data stored in memory 215. For example, processing module 230-a can delete sampled data after performing calculations based on the sampled data. As another example, processing module 230-a can average data over a longer time period to reduce the number of stored values. In a particular example, if the user's average temperature over one minute is stored in memory 215, processing module 230-a can calculate the average temperature over a five-minute time period for storage and then erase the one-minute average temperature data. Processing module 230-a can compress data based on various factors, such as the total amount of memory 215 used / available and / or the time elapsed since the last time loop 104 transmitted the data to user equipment 106.

[0080] While a user's physiological parameters can be measured by sensors included on ring 104, other devices can also measure them. For example, while a user's temperature can be measured by temperature sensor 240 included in ring 104, other devices can also measure it. In some examples, other wearable devices (e.g., wrist devices) may include sensors for measuring a user's physiological parameters. Furthermore, medical devices such as external medical devices (e.g., wearable medical devices) and / or implantable medical devices can measure a user's physiological parameters. The techniques described herein can be implemented using one or more sensors on any type of computing device.

[0081] Physiological measurements can be acquired continuously throughout the day and / or night. In some implementations, physiological measurements can be acquired during various parts of the day and / or night. In some implementations, physiological measurements can be acquired in response to determining that the user is in a specific state (e.g., active state, resting state, and / or sleeping state). For example, ring 104 can perform physiological measurements during rest / sleep states to obtain cleaner physiological signals. In one example, ring 104 or other devices / systems can detect when the user is resting and / or sleeping and acquire physiological parameters (e.g., temperature) of the detected state. When the user is in other states, the devices / systems can use rest / sleep physiological data and / or other data to implement the techniques of this disclosure.

[0082] In some implementations, as described previously herein, ring 104 may be configured to collect, store, and / or process data, and may transfer any data described herein to user device 106 for storage and / or processing. In some aspects, user device 106 includes wearable application 250, operating system (OS) 285, web browser application (e.g., web browser 280), one or more additional applications, and GUI 275. User device 106 may further include other modules and components, including sensors, audio devices, haptic feedback devices, etc. Wearable application 250 may include examples of applications (e.g., “apps”) that can be installed on user device 106. Wearable application 250 may be configured to acquire data from ring 104, store the acquired data, and process the acquired data as described herein. For example, wearable application 250 may include user interface (UI) module 255, acquisition module 260, processing module 230-b, communication module 220-b, and storage module (e.g., database 265) configured to store application data.

[0083] The various data processing operations described herein can be performed by ring 104, user equipment 106, server 110, or any combination thereof. For example, in some cases, data collected by ring 104 may be preprocessed and transmitted to user equipment 106. In this example, user equipment 106 may perform some data processing operations on the received data, transmit the data to server 110 for data processing, or both. For example, in some cases, user equipment 106 may perform processing operations requiring relatively low processing power and / or requiring relatively low latency, while user equipment 106 may transmit data to server 110 for processing operations requiring relatively high processing power and / or allowing relatively high latency.

[0084] In some aspects, the ring 104, user device 106, and server 110 of system 200 can be configured to assess a user's sleep patterns. Specifically, the corresponding components of system 200 can be used to collect data from the user via ring 104 and generate one or more scores (e.g., sleep score, readiness score) for the user based on the collected data. For example, as previously noted herein, the ring 104 of system 200 can be worn by the user to collect data from the user, including temperature, heart rate, HRV, etc. The data collected by ring 104 can be used to determine when the user fell asleep to assess the user's sleep for a given "sleep day." In some aspects, a score can be calculated for each corresponding 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. The score for each corresponding sleep day can be calculated based on data collected by ring 104 during the corresponding sleep day. The scores can include, but are not limited to, sleep scores, readiness scores, etc.

[0085] In some cases, a "sleep day" can be aligned with a traditional calendar day, allowing a given sleep day to extend from midnight to midnight on the corresponding calendar day. In other cases, a sleep day can be offset relative to a calendar day. For example, a sleep day can extend from 6:00 PM (6:00 PM) on a calendar day to 6:00 PM (6:00 PM) on a subsequent calendar day. In this example, 6:00 PM can serve as a "deadline," 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 subsequent sleep days. Because most individuals sleep the most at night, offsetting the sleep day relative to the calendar day allows System 200 to assess the user's sleep patterns in a manner consistent with their sleep schedule. In some cases, users may be able to selectively adjust (e.g., via a GUI) the timing of their sleep day relative to the calendar day, aligning the sleep day with the duration of the user's typical sleep.

[0086] In some implementations, a user's total score for each corresponding day (e.g., sleep score, readiness score) can be determined / calculated based on one or more "contributors," "factors," or "contribution factors." For example, a user's total sleep score can be calculated based on a set of contributors, including: total sleep, efficiency, restfulness, REM sleep, deep sleep, wait time, timing, or any combination thereof. The sleep score can include any number of contributors. A "total sleep" contributor can refer to the sum of all sleep periods on a sleep day. An "efficiency" contributor can reflect the percentage of time spent asleep compared to the time spent waking up while sleeping, and can be calculated using the efficiency average of the long sleep periods (e.g., the main sleep period) of the sleep day, weighted by the duration of each sleep period. A "restfulness" contributor can indicate how restful a user's sleep is, and can be calculated using the average of all sleep periods of the sleep day, weighted by the duration of each period. Tranquility contributors can be based on “wake-up count” (e.g., the sum of all wake-ups detected during different sleep periods when the user wakes up), excessive movement, and “get-out count” (e.g., the sum of all get-outs detected during different sleep periods when the user gets out of bed).

[0087] A “REM sleep” contributor can refer to the sum of REM sleep durations across all sleep segments on a sleep day that includes REM sleep. Similarly, a “deep sleep” contributor can refer to the sum of deep sleep durations across all sleep segments on a sleep day that includes deep sleep. A “waiting time” contributor can represent how long it takes a user to fall asleep (e.g., average, median, longest) and can be calculated using the average of long sleep segments between sleep days, weighted by the duration of each segment and the number of such segments (e.g., combining one or more given sleep stages can be its own contributor or can be weighted by other contributors). Finally, a “timed” contributor can refer to the relative timed sleep segments within a sleep day and / or calendar day and can be calculated using the average of all sleep segments on a sleep day weighted by the duration of each segment.

[0088] As another example, a user's overall readiness score can 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 can include any number of contributors. A "sleep" contributor can refer to the combined sleep score of all sleep segments within a sleep day. A "sleep balance" contributor can refer to the cumulative duration of all sleep segments within a sleep day. Specifically, sleep balance can indicate to a user whether the sleep a user has taken over a certain period (e.g., the past two weeks) is in line with the user's needs. Typically, adults need 7-9 hours of sleep per night to maintain health, alertness, and optimal mental and physical performance. However, occasional nights with poor sleep are common, so sleep balance contributors consider long-term sleep patterns to determine whether each user's sleep needs are being met. A "resting heart rate" contributor can indicate the lowest heart rate from the longest sleep segment of the sleep day (e.g., the main sleep segment) and / or the lowest heart rate from a nap that occurs after the main sleep segment.

[0089] Continuing to reference the "contributors" (e.g., factors, contributing factors) of the readiness score, the "HRV balance" contributor can indicate the highest average HRV from the main sleep period and naps that occur after the main sleep period. The HRV balance contributor helps users track their recovery status by comparing their HRV trend over a first time period (e.g., two weeks) with the average HRV over a second, longer time period (e.g., three months). The "recovery index" contributor can be calculated based on the longest sleep period. The recovery index measures how long it takes for a user's resting heart rate to stabilize during the night. A very good sign of 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 time for the body to recover the next day. If the user's highest temperature during a nap is at least 0.5°C higher than the highest temperature during the longest sleep period, the "body temperature" contributor can be calculated based on the longest sleep period (e.g., the main sleep period) or based on naps that occur after the longest sleep period. In some aspects, the ring can measure the user's body temperature while the user is asleep, and the system 200 can display the user's average temperature relative to the user's baseline temperature. If a user's body temperature is outside their normal range (e.g., clearly above or below 0.0), the temperature contributor can be highlighted (e.g., put into "attention" status) or an alert can be generated for the user in other ways.

[0090] In some respects, system 200 may support techniques for generating group-based health and wellness scores and insights. For example, user device 106 may receive user-specific information (e.g., user-specific physiological data, user-specific scores) collected by wearable device 104 for a user group that has been authorized to share information within the group (e.g., two-way data sharing). User device 106 may use the user-specific information for the group users to generate group-specific scores or insights, which may in turn be used to generate group-specific recommendations.

[0091] Alternatively or additionally, user device 106 may display user-specific information (or a subset of user-specific information) on an individual basis so that group members can monitor each other’s health and wellness and take appropriate action (e.g., provide responses via electronic devices, update health and wellness goals).

[0092] Figure 3 An example of a system 300 supporting a two-way data sharing technology based on wearable devices according to various aspects of this disclosure is shown. System 300 may implement aspects of system 100, system 200, or both, or be implemented by them. For example, system 300 may include a wearable device 304 (which may be a wearable ring device) and a user device 306. Wearable device 304 may be as described in the reference... Figure 1 and Figure 2 The wearable device 104 described is an example, while the user device 306 may be as shown in the reference. Figure 1 and Figure 2 An example of user equipment 106 is described.

[0093] System 300 can implement the bidirectional data sharing technology described herein, which is used to generate group-specific health and wellness information based on user-specific data collected by wearable device 304. For example, system 300 can generate group-specific health and wellness information for a user group including user 302-a, user 302-b, and user 302-c. Users 302 in the group may be located in the same location (e.g., in the same room, in the same building, or within a threshold distance from each other) or may be geographically dispersed (e.g., in different communities, different cities, or different countries).

[0094] User-specific data used to generate group-specific health and wellness information can be collected by the respective wearable devices 304 of users 302 in the group. For example, wearable device 304-a can collect physiological data from user 302-a and transmit the physiological data to user device 306-a. Similarly, wearable devices 304-b and 304-c can collect physiological data from users 302-b and 302-c and transmit the physiological data to their respective user devices 306-b and 306-c. User-specific data can be exchanged via wireless devices in the group (e.g., wearable devices 304, user devices 306) to enable the generation of group-specific health and wellness information. In other words, the physiological data of each user 302 in the group can be shared with other users 302 in the group (e.g., bidirectional sharing). The user-specific data exchanged between user devices 306 can be updated over time (e.g., repeated sharing) to reflect trends and / or the latest user-specific data of group members.

[0095] In some examples, user equipment 306 (e.g., user equipment 306-c) may retain handshake procedures with other user equipment 306 (e.g., directly or via one or more servers 310) to establish one or more wireless electronic communication links. For example, for a given user equipment 306 associated with a group of users, user equipment 306-c may send (e.g., via wireless electronic communication) a request to establish a wireless electronic communication link (e.g., a Bluetooth link) with that user equipment 306. Upon receiving a message acknowledging the request, user equipment 306-c may exchange electronic wireless communication signaling with user equipment 306 to establish a wireless electronic communication link. After establishing a wireless electronic communication link with user equipment 306, user equipment 306-c may receive instructions (from an application associated with user equipment 306) authorizing the transmission and reception (e.g., using the wireless electronic communication link) of physiological data collected by the associated wearable device 304. In some cases, one or more servers 310 can be configured to facilitate the exchange of signaling for a “handshake procedure” used to establish a trusted user group, thereby facilitating the bidirectional exchange of physiological data.

[0096] User 302 can join the group by authorizing user device 306 of user 302 to exchange user-specific information with other user devices 306 in the group. For example, after receiving authorization from user 302-c, the application of user device 306-c can exchange user-specific information with other applications of user devices 306 in the group. The user-specific information transmitted to other user devices 306 may include raw information (e.g., physiological data) or processed information (e.g., scores or insights based on physiological data). User devices 306 can communicate directly (e.g., via peer-to-peer wireless communication) or indirectly (e.g., via network 308).

[0097] In some cases, user 302 can manually create user groups with which they wish to share data by sending requests to other users 302. Alternatively, system 300 can recommend user groups or circles to share data, such as based on the geographical location of each user 302, or based on the user 302's physiological characteristics. For example, system 300 can determine the spatial relationship between users 302 (e.g., determining that users 302 are located close to each other, such as in the same apartment building) and can send prompts / recommendations based on the determined spatial relationship, suggesting that users 302 form a group for bidirectional sharing. As another example, system 300 can identify users 302 with similar physiological characteristics (e.g., similar circadian rhythms, similar sleep patterns, etc.) and can send prompts / recommendations suggesting that users 302 form a group for bidirectional sharing.

[0098] After forming a group (e.g., a circle, a trust circle, etc.), system 300 can aggregate physiological data from each corresponding user 302 (e.g., via wearable device 304) and distribute the collected physiological data to other users 302 in the group. To this end, each user 302 can share their own physiological data with other users and receive physiological data from other users in the group. That is, in addition to providing user-specific information of user 302-c to other user devices 306 in the group, system 300 (e.g., server 310, user device 306-c) can also receive user-specific information of user 302 in the group. For example, user device 306-c can receive user-specific information of user 302-a from the application of user device 306-a, and can receive user-specific information of user 302-b from the application of user device 306-b. In some aspects, the physiological data of each corresponding user 302 in the group can be aggregated at the corresponding user device 306, aggregated at the server 310, and then distributed to users 302 in the group, or both.

[0099] Physiological data can be collected from users 302 in the group at predetermined times (e.g., 9:00 AM and 9:00 PM), based on certain events (e.g., after each user wakes up, after completing an exercise, etc.), based on physiological data meeting a certain threshold (e.g., based on a threshold change in identifying user physiological data), or based on any combination thereof. For this purpose, the physiological data of users 302 in the group can be "pushed" and / or "pulled" to aggregate the group's data.

[0100] System 300 (e.g., server 310, user device 306-c) can use user-specific information of users in the group to generate one or more scores or insights for the group. For example, system 300 can generate a comprehensive readiness score or a comprehensive sleep score for the group, which is a function of user-specific information for the group (e.g., the comprehensive sleep score for the group can be calculated as the average or median sleep score for each corresponding user 302 in the group). Additionally or alternatively, system 300 can generate an activity score for the group, indicating the group's collective (e.g., average) activity level. Additionally or alternatively, system 300 can generate an anxiety score for the group, indicating the group's collective anxiety level. In some examples, system 300 can use a machine learning (ML) model to generate the comprehensive score. System 300 (e.g., server 310, user device 306-c) can transmit (e.g., via wireless electronic communication) control signaling (e.g., to user device 306 associated with the group), causing user device 306 associated with the group to display an indication of the group score or insight.

[0101] In some respects, the composite score calculated for a group can be used to convey information about the overall health, well-being, and / or stress of the entire group. In some cases, the score calculated for an individual user 302 and / or the composite score calculated for a group can be used as a “status” for social media applications, instant messaging applications (e.g., workplace instant messaging applications), etc.

[0102] In some respects, system 300 enables user 302 within a group to share messages with other users in the group, and to “respond” to the scores and / or physiological data of other users 302 in the group (e.g., responding with custom replies, emojis, or other predefined responses). In this regard, the techniques described herein allow user 302 to proactively respond to and connect with other users 302 in the group to encourage healthy habits and to encourage each other to achieve fitness goals.

[0103] In addition to generating group-specific scores (or instead of generating group-specific scores), system 300 (e.g., server 310, user device 306-c) can also determine insights for the group. For example, system 300 can determine that the group has an unusual score relative to its historical scores (e.g., a score outside the standard deviation range). In some examples, insights can be based on activities or events shared among users in the group. For example, user device 306-c can determine that the group is not getting enough rest and is unable to perform the activities scheduled for the group (e.g., a strength training class). "Scores" can include quantitative values ​​representing group characteristics, while "insights" can be observations or assessments that convey qualitative or descriptive information about group characteristics. In some examples, system 300 can use ML models to determine insights for the group.

[0104] In some examples, system 300 (e.g., server 310, user device 306-c) can determine group-specific recommendations based on group-specific health and wellness information (e.g., one or more group-specific scores, one or more group-specific insights). For example, system 300 can suggest an activity (e.g., a walk, a nap, drinking coffee) for a group of users, propose changes to the activity (e.g., shortening a training session, engaging in lighter physical activity), recommend changes to the schedule (e.g., postponing a meeting), and so on. Making a recommendation may involve system 300 (e.g., server 310, user device 306-c) sending (e.g., via wireless electronic communication) control signaling (e.g., to the user device associated with the group) that causes the user device associated with the group to display an indication of the recommendation. In some examples, system 300 may use an ML model to determine group-specific recommendations.

[0105] In some cases, system 300 can provide recommendations or insights to a user group based on the calendar information of each corresponding user 302. For example, system 300 can aggregate calendar information for each user 302, such as from a calendar application that can be executed on the corresponding user's device 306. In this example, system 300 may see, based on the acquired calendar information, that users in the group have a meeting scheduled for 9:00 AM, but may also see that the group had poor sleep last night (e.g., the group exhibited low sleep scores and / or low overall sleep scores). Therefore, system 300 can see that each user in the group has an available time slot from 1:00 PM to 1:30 PM (e.g., based on the acquired calendar information), and can therefore provide a recommendation for the group to postpone the meeting time from 9:00 AM to 1:00 PM based on aggregated physiological information and calendar data.

[0106] In some examples, system 300 may apply different weighting (e.g., scaling) to user-specific data of certain users 302 than to other users 302. For example, system 300 may weight user-specific data of user 302 based on a priority level associated with the user (e.g., assigned to the user). Additionally or alternatively, system 300 may selectively exclude user-specific data of one or more users 302 (e.g., identified anomalies, users indicated as absent or sick) from the data used to generate group-specific health and wellness information. Therefore, user-specific data of some or all users 302 in a group may contribute to group-specific health and wellness information.

[0107] In some examples, the weights applied to a user's user-specific data may be based on how that user-specific data changes relative to the user's historical (e.g., baseline) user-specific data, how that user-specific data changes relative to a statistical indicator (e.g., mean) of the user-specific data of the rest of the group, or both. In some examples, the weights applied to user-specific data may be based on one or more inputs received from the user. For example, a user may request that user-specific information for one or more users be applied with relatively larger or smaller weights relative to other users in the group. In some cases, the weights applied to user-specific data may be statically selected by system 300. In other cases, the weights applied to each corresponding user's physiological data may be dynamically determined. In this case, the weights for each corresponding user may be determined based on a comparison of each corresponding user's physiological data with its own baseline, a comparison with the data of the rest of the group, or a comparison with both. For example, a first user may exhibit physiological data for a given day that is relatively similar to the first user's baseline data (e.g., similar sleep data, similar activity data), while a second user may exhibit physiological data for a given day that deviates significantly from the second user's baseline data (e.g., significantly different sleep data, significantly different activity data). In this example, when calculating the group's overall score for a given day, the second user's data can be weighted more heavily than the first user's data.

[0108] In some examples, system 300 may suggest groups to user 302-c. For example, system 300 (e.g., server 310, user device 306-c) may suggest groups to user 302-c based on spatial relationships (e.g., proximity) between user 302-c and other users 302 in the group, based on one or more physiological characteristics shared by user 302-c and other users 302 in the group (e.g., circadian rhythm, sleep type), based on demographic characteristics shared by user 302-c and other users 302 in the group (e.g., same sex, similar age, etc.), or based on other commonalities between user 302-c and other users in the group (e.g., shared fitness goals, similar activity patterns, similar sleep patterns).

[0109] User-specific information shared by user equipment 306 can be selected by user 302 of user equipment 306. For example, user 302-c can choose the type of data to share with other user equipment in the group. For illustration, user 302-c can choose to share sleep data with the group but not fertility data. If user 302-c belongs to two different groups, user 302-c can choose to share different types of data with both groups. If user 302-c chooses to share a first type of data with the first group (but not with the second group) and a second type of data with the second group (but not with the first group), then user equipment 306-c can A) determine that sharing the first type of data with the first group is permitted, but not with the second group; and B) transmit the first type of data to the user equipment associated with the first group (but not with the second group). Similarly, user equipment 306-c can A) determine that sharing the second type of data with the second group is permitted, but not with the first group; and B) transmit the second type of data to the user equipment associated with the second group (but not with the first group). In some examples, user device 306-c may suggest the data types that user 302-c wants to share with the group. Additionally or alternatively, user 302-c may choose to share data collected during certain time periods (e.g., data collected during weekdays) rather than data collected during other time periods (e.g., data collected during weekends). In some examples, user 302-c may instruct user device 306 to anonymize data shared with the group. In some examples, user 302-c may specify a particular user for whom data should be anonymized.

[0110] In some examples, user device 306-c may wait for user 302-c to authenticate before exchanging (e.g., sending or receiving) user-specific data with other user devices 306. For instance, user device 306-c may wait for wearable device 304-c to authorize user 302-c before exchanging user-specific data with other user devices 306. Furthermore, in some implementations, other users 302 in the group may need to approve or authorize the new user 302 before adding the new user 302 to the group to enable bidirectional sharing with the new user 302.

[0111] In some examples, system 300 can identify one or more users 302 who are anomalous in terms of user-specific data that deviate significantly from (e.g., deviate by a threshold amount) the user-specific data of other users 302 in the group. In other words, system 300 can flag users 302 who exhibit physiological data or scores that deviate from the group's average / median physiological data / scores as a whole. For example, system 300 (e.g., server 310, user device 306-c) can identify user 302-a as anomalous based on user 302-a's sleep score being x% lower than the next lowest sleep score, or x% lower than the group's average sleep score. By doing so, system 300 can enable users 302 in the group to proactively reach out to or encourage those users 302 who may be experiencing mental, physical, and / or emotional difficulties.

[0112] System 300 can flag anomalous users 302 and generate user-specific recommendations for these anomalies. In some examples, system 300 can generate multiple group-specific scores or insights that vary based on the inclusion and exclusion of anomalous user-specific data. For example, user device 306-c can generate “true” group-specific scores or insights that reflect user-specific data for all users 302 in the group, and can generate “adjusted” group-specific scores that reflect user-specific data for a subset of users 302 in the group after excluding anomalous users (and may more accurately represent the overall health of the group).

[0113] In some examples, system 300 may display user-specific data of one or more users alongside group-specific data for comparison. For example, user device 306-c may display user-specific data of user 302-c (or one or more other users) alongside group-specific data. Additionally or alternatively, system 300 may sort and display user-specific data of one or more users in descending or ascending order. Additionally or alternatively, system 300 may display indications of how a user of user device 306-c is compared to a group, how a user is compared to the top or bottom z percent of the group, or any combination thereof. In some examples, system 300 may provide one or more recommendations for a user of user device 306-c based on how a user is compared to a group or other members of the group. In some examples, a user of user device 306-c may select specific individuals whose user-specific data they wish to display. For example, a user may select individuals by name, relationship, or ranking (e.g., user device 306-c may display the top z percent of user data for a group).

[0114] In some examples, system 300 (e.g., via user device 306-c) can control one or more external devices near the group (e.g., if the group is co-located) based on group-specific health and wellness information. For example, user device 306-c can modify the environment by altering the lumens or color of light emitted by one or more lights near the user, based on the user's group sleep score. As another example, user device 306-c can adjust the temperature setting of the thermostat in the room where the group is located, based on the user's group anxiety score. As another example, user device 306-c can adjust the volume of speakers near the group, based on the user's group sleep score. As yet another example, user device 306-c can adjust the position of smart curtains near the group, based on the user's group readiness score.

[0115] User equipment 306-c can autonomously change the settings or operating parameters of nearby electronic devices (e.g., without user input). Alternatively, user equipment 306-c may suggest changes (e.g., by displaying an indication of the suggested changes) and may wait for the changes to be implemented until user 302-c (or another user in the group) approves the changes (e.g., via user input). In order to wirelessly communicate with electronic devices to change the settings of the electronic devices, user equipment 306-c may perform a wireless synchronization procedure with the electronic devices and then send one or more instructions to the electronic devices after synchronization.

[0116] Therefore, system 300 can generate group-specific health and wellness information based on user-specific data collected by wearable device 304. Although described with reference to user device 306, the various operations described herein can be performed by server 310. Furthermore, the operations described herein can be performed by a single device of system 300, or can be distributed among the various devices of system 300 (e.g., performed by individual devices).

[0117] Figure 4 An example of a process flow 400 supporting a two-way data sharing technology based on wearable devices according to various aspects of this disclosure is shown. Process flow 400 can be generated by devices in the system (such as, referenced in...) Figure 3 The system described herein (300) is implemented. The device can be a user device (306) or a server (310), among other options. According to the techniques described herein, the device can generate group-specific health and wellness information based on user-specific data collected by wearable devices associated with a group of users.

[0118] At point 405, the device can identify and recommend groups for the user to join. For example, the device can identify the user group a user wants to join based on spatial relationships between users, one or more shared (common) characteristics or similarities between the user and other users in the group, or both, and can make the GUI (e.g., the GUI of the user's device) display instructions for the group to the user. For example, the device can acquire baseline physiological data associated with some or all users in the group and can identify one or more similarities between the baseline physiological data associated with each user. Based on the identified similarities, the device can send prompts to share physiological data among the user groups. Therefore, after identifying a group a user wants to join, the device can send prompts to share user-specific data among the users in the group. Alternatively, the device can send or receive invitations to join a group. In these examples, group members can be selected by the users of the group.

[0119] At point 410, the device can receive an indication that the user has selected a group to join. If the device is a user device, it can receive this indication via user input. If the device is a server, it can receive this indication from the user device.

[0120] At 415, the device can communicate with the user devices of users in the group to establish data exchange permissions. As part of the communication, the device can receive instructions (e.g., from applications on user devices associated with users in the group) to exchange (e.g., transmit and receive) user-specific data (e.g., physiological data, user-specific scores) between authorized applications. In some examples, the instructions received by the device may be based on (e.g., in response to) sending a prompt at 405 to share user-specific data.

[0121] At 420, the device may receive indications of data sharing constraints or parameters for sharing user-specific data with an application. For example, the device may receive indications of the types of data that are allowed to be exchanged. As another example, the device may receive indications of the time periods for which the collected data is allowed to be exchanged. If the device is a user device, it may receive indications at 420 via user input. If the device is a server, it may receive indications from a user device at 420.

[0122] At 425, the device can acquire (e.g., wirelessly receive) user-specific data collected by the user's wearable device. The device can acquire the user-specific data directly from the wearable device (e.g., via Bluetooth) or indirectly from the user device via network 308. At 430, the device can provide authorized user-specific data to other user devices in the group based on the user's selection of a group.

[0123] At 435, the device can acquire (e.g., wirelessly receive) user-specific data from one or more applications in the group. The device can acquire user-specific data directly from user devices in the group (e.g., via Bluetooth) or via network 308. At 440, the device can generate group-specific scores or insights based on the user-specific data of users in the group. For example, the device can calculate the group's average score based on the individual scores of group users (e.g., based on those individual scores). At 445, the device can determine recommendations for the group based on the group-specific scores and / or insights.

[0124] At point 450, the device may allow one or more GUIs to display group-specific scores, group-specific insights, group-specific recommendations, or any combination thereof. The GUI may include the device's GUI, the GUIs of users' devices within the group, or both. In some examples, group-specific recommendations may be based on calendar data associated with users in the group.

[0125] At 455, the device can identify one or more users whose user-specific data pertains to an anomaly within the group. For example, the device can identify physiological data associated with user y that deviates from a threshold metric compared to physiological data associated with the remaining users in the group. At 460, the device can cause one or more GUIs to display indications of the anomaly user (e.g., user y), the user-specific data of the anomaly user, one or more recommendations for the anomaly user, or any combination thereof. The GUI may include the device's GUI, the GUIs of the user devices in the group, or both.

[0126] Figure 5A block diagram 500 of a device 505 supporting bidirectional data sharing technology based on wearable devices according to various aspects of this disclosure is shown. Device 505 may include an input module 510, an output module 515, and a wearable application 520. Device 505 may also include a processor. Each of these components can communicate with each other (e.g., via one or more buses).

[0127] Input module 510 may provide means for receiving information (such as data packets, user data, control information, or any combination thereof) associated with various information channels (e.g., control channels, data channels, information channels related to disease detection technologies). The information may be transmitted to other components of device 505. Input module 510 may use a single antenna or a group of multiple antennas.

[0128] Output module 515 may provide means for transmitting signals generated by other components of device 505. For example, output module 515 may transmit information associated with various information channels (e.g., control channels, data channels, information channels related to disease detection technologies), such as data packets, user data, control information, or any combination thereof. In some examples, output module 515 may be co-located with input module 510 in a transceiver module. Output module 515 may use a single antenna or a group of multiple antennas.

[0129] For example, wearable application 520 may include communication component 525, processor 530, graphics component 535, or any combination thereof. In some examples, wearable application 520 or its various components may be configured to use input module 510, output module 515, or both, or otherwise cooperate with input module 510, output module 515, or both, to perform various operations (e.g., receiving, monitoring, transmitting). For example, wearable application 520 may receive information from input module 510, send information to output module 515, or be integrated with input module 510, output module 515, or both to receive information, transmit information, or perform various other operations as described herein.

[0130] Wearable application 520 may support the sharing of physiological data among a group of users, as illustrated in the examples disclosed herein. Communication component 525 may be configured or otherwise supported for receiving instructions from one or more applications associated with a group of users, wherein the instructions include authorization to send and receive physiological data between the one or more applications, wherein the physiological data is at least in part based on physiological measurements collected from each user in the user group via wearable devices associated with one or more applications. Communication component 525 may be configured or otherwise supported for acquiring physiological data from one or more applications. Processor 530 may be configured or otherwise supported for generating scores indicating physiological indicators representing the user group, based at least in part on the physiological data acquired from one or more applications. Graphics component 535 may be configured or otherwise supported for displaying the scores using at least one GUI on a user device associated with one or more applications.

[0131] Figure 6 A block diagram 600 of a wearable application 620 is shown, which supports bidirectional sharing technology based on wearable device data according to various aspects of this disclosure. Wearable application 620 may be an example of the wearable application described herein, or wearable application 520, or aspects of both. Wearable application 620 or its various components may be examples of devices for implementing various aspects of the bidirectional sharing technology based on wearable device data as described herein. For example, wearable application 620 may include communication component 625, processor 630, graphics component 635, or any combination thereof. Each of these components may communicate directly or indirectly with each other (e.g., via one or more buses).

[0132] Wearable application 620 may support sharing physiological data among a group of users according to the examples disclosed herein. Communication component 625 may be configured or otherwise supported for receiving instructions from one or more applications associated with the user group, wherein the instructions include authorization to send and receive physiological data between the one or more applications, wherein the physiological data is based at least in part on physiological measurements collected from each user in the user group via wearable devices associated with one or more applications. In some examples, communication component 625 may be configured or otherwise supported for acquiring physiological data from one or more applications. Processor 630 may be configured or otherwise supported for generating scores indicating physiological indicators representing the user group, based at least in part on physiological data acquired from one or more applications. Graphics component 635 may be configured or otherwise supported for displaying the scores using at least one GUI of the user devices associated with one or more applications.

[0133] In some examples, the physiological data includes first physiological data associated with a first user in the user group, and additional physiological data associated with the remaining users in the user group other than the first user, and the processor 630 may be configured or otherwise supported to enable means for identifying deviations of the first physiological data associated with the first user from the additional physiological data associated with the remaining users from a threshold measure. In some examples, the physiological data includes first physiological data associated with a first user in the user group, and additional physiological data associated with the remaining users in the user group other than the first user, and the graphics component 635 may be configured or otherwise supported to enable means for causing at least one GUI of the device to display an indication of the first user at least in part based on the identification.

[0134] In some examples, processor 630 may be configured or otherwise supported as a means for identifying spatial relationships between user groups. In some examples, communication component 625 may be configured or otherwise supported as a means for sending prompts for sharing physiological data among user groups, at least in part based on the identification of spatial relationships, wherein receiving such instructions is at least in part based on sending the prompts.

[0135] In some examples, communication component 625 may be configured or otherwise supported for acquiring baseline physiological data associated with multiple users, including user groups. In some examples, processor 630 may be configured or otherwise supported for identifying one or more similarities between baseline physiological data associated with each user in a user group. In some examples, communication component 625 may be configured or otherwise supported for sending a prompt to share physiological data among user groups, at least in part based on identifying one or more similarities, wherein receiving the instruction is at least in part based on sending the prompt.

[0136] In some examples, processor 630 may be configured or otherwise supported to enable means for identifying calendar data associated with each user in a user group. In some examples, graphics component 635 may be configured or otherwise supported to enable at least one GUI of a user device associated with one or more applications to display recommendations based at least in part on scores and calendar data.

[0137] In some examples, the communication component 625 may be configured or otherwise support a device for receiving indications of one or more authorized physiological parameters, one or more authorized time periods, or both, via an application in one or more applications associated with a first user in a user group, wherein obtaining physiological data from the application associated with the user includes obtaining physiological data associated with one or more authorized physiological parameters, obtaining physiological data within one or more authorized time periods, or both.

[0138] In some examples, at least one wearable device associated with each user in a user group includes a wearable ring device.

[0139] Figure 7 A diagram of a system 700 according to various aspects of this disclosure is shown, the system including a device 705 supporting a two-way sharing technology based on wearable device data. Device 705 may be an example of components of device 505 as described herein, or may include components of device 505 as described herein. Device 705 may include an example of user device 106, as described previously herein. Device 705 may include components for two-way communication, including components for sending and receiving communication with wearable device 104 and server 110, such as wearable application 720, communication module 710, antenna 715, user interface component 725, database (application data) 730, memory 735, and processor 740. These components may communicate electronically or otherwise (e.g., operable, communicative, functional, electronic, electrical) via one or more buses (e.g., bus 745).

[0140] The communication module 710 can manage the input and output signals of the device 705 via the antenna 715. The communication module 710 may include... Figure 2 An example of the communication module 220-b of the user equipment 106 shown and described. In this respect, the communication module 710 can manage communication with the ring 104 and the server 110, such as Figure 2 As shown. The communication module 710 can also manage peripheral devices not integrated into the device 705. In some cases, the communication module 710 can represent a physical connection or port to an external peripheral device. In other cases, the communication module 710 can use, for example... Or an operating system of other known operating systems. In other cases, the communication module 710 may represent, or interact with, a wearable device (e.g., ring 104), modem, keyboard, mouse, touchscreen, or similar device. In some cases, the communication module 710 may be implemented as part of the processor 740. In some examples, a user can interact with the device 705 via the communication module 710, the user interface component 725, or via hardware components controlled by the communication module 710.

[0141] In some cases, device 705 may include a single antenna 715. However, in other cases, device 705 may have more than one antenna 715, which may be capable of transmitting or receiving multiple wireless transmissions concurrently. Communication module 710 may communicate bidirectionally via one or more antennas 715, wired or wireless links, as described herein. For example, communication module 710 may represent a wireless transceiver and may communicate bidirectionally with another wireless transceiver. Communication module 710 may also include a modem for modulating data packets, providing modulated data packets to one or more antennas 715 for transmission, and demodulating data packets received from one or more antennas 715.

[0142] User interface component 725 manages data storage and processing within database 730. In some cases, users can interact with user interface component 725. In other cases, user interface component 725 can operate automatically without user interaction. Database 730 can be an example of a single database, a distributed database, multiple distributed databases, a data storage area, a data lake, or an emergency backup database.

[0143] Memory 735 may include RAM and ROM. Memory 735 may store computer-readable, computer-executable software containing instructions that, when executed, cause processor 740 to perform the various functions described herein. In some cases, memory 735 may include a BIOS, which controls basic hardware or software operations, such as interaction with peripheral components or devices.

[0144] Processor 740 may include intelligent hardware devices (e.g., general-purpose processors, DSPs, CPUs, microcontrollers, ASICs, FPGAs, programmable logic devices, discrete gate or transistor logic components, discrete hardware components, or any combination thereof). In some cases, processor 740 may be configured to operate a memory array using a memory controller. In other cases, the memory controller may be integrated into processor 740. Processor 740 may be configured to execute computer-readable instructions stored in memory 735 to perform various functions (e.g., functions or tasks supporting methods and systems for sleep staging algorithms).

[0145] Wearable application 720 may support sharing physiological data among a group of users according to the examples disclosed herein. For example, wearable application 720 may be configured or otherwise support a device for receiving instructions from one or more applications associated with a user group, wherein the instructions include authorization to send and receive physiological data between the one or more applications, wherein the physiological data is based at least in part on physiological measurements collected from each user in the user group via wearable devices associated with one or more applications. Wearable application 720 may be configured or otherwise support a device for acquiring physiological data from one or more applications. Wearable application 720 may be configured or otherwise support a device for generating scores at least in part based on physiological data acquired from one or more applications, the scores indicating physiological indicators representative of the user group. Wearable application 720 may be configured or otherwise support a device for displaying the scores using at least one GUI of a user device associated with one or more applications.

[0146] By including or configuring the wearable application 720 according to the examples described herein, the device 705 can support technologies that improve the user experience.

[0147] Wearable application 720 may include applications (e.g., "app"), programs, software, or other components configured to facilitate communication with ring 104, server 110, other user devices 106, etc. For example, wearable application 720 may include an application executable on user device 106 configured to receive data (e.g., physiological data) from ring 104, perform processing operations on the received data, send and receive data with server 110, and cause data to be presented to user 102.

[0148] Figure 8A flowchart of a method 800 supporting a two-way data sharing technology based on wearable devices, according to various aspects of this disclosure, is shown. Operation of method 800 can be implemented by a user device or its components as described herein. For example, operation of method 800 can be implemented by, as referenced... Figures 1 to 7 The user equipment described is executed as follows. In some examples, the user equipment may execute a set of instructions to control the functional elements of the user equipment to perform the function. Alternatively, the user equipment may use dedicated hardware to perform aspects of the function.

[0149] At 803, the method may include sending one or more requests via wireless electronic communication to establish one or more wireless electronic communication links with one or more user equipments associated with a user group. Operation of 803 can be performed according to examples as disclosed herein. In some examples, aspects of the operation of 803 may be derived from references... Figure 6 The described communication component 625 is executed.

[0150] At 805, the method may include: receiving instructions from one or more applications associated with the user group via one or more wireless electronic communication links, at least in part based on sending one or more requests, wherein the instructions include authorization to send and receive physiological data between the one or more applications, wherein the physiological data is at least in part based on physiological measurements collected from each user in the user group via wearable devices associated with one or more applications. Operation of 805 may be performed according to examples as disclosed herein. In some examples, aspects of the operation of 805 may be derived from references... Figure 6 The described communication component 625 is executed.

[0151] At point 810, the method may include: receiving physiological data from one or more applications via one or more wireless electronic communication links, and at least in part based on instructions. Operation of 810 can be performed according to examples as disclosed herein. In some examples, aspects of the operation of 810 may be derived from references... Figure 6 The described communication component 625 is executed.

[0152] At point 815, the method may include: generating scores, at least in part, based on physiological data obtained from one or more applications, that scores indicate physiological indicators representative of the user group. The operation at point 815 can be performed according to examples as disclosed herein. In some examples, aspects of the operation at point 815 may be derived from references... Figure 6 The processor 630 described is executed.

[0153] At 820, the method may include: transmitting control signals via one or more wireless electronic communication links to cause at least one GUI of one or more user devices associated with one or more applications to display a score and one or more recommendations or insights associated with the score. Operation of 820 can be performed according to examples as disclosed herein. In some examples, aspects of the operation of 820 may be derived from references... Figure 6 The described graphics component 635 is executed.

[0154] It should be noted that the above methods only describe possible implementations, and their operation and steps can be repeated or modified in other ways, and other implementations are also possible. Furthermore, aspects of two or more methods can be combined.

[0155] A method for sharing physiological data among a group of users is described. The method may include: receiving instructions from one or more applications associated with the group of users, wherein the instructions include authorization to send and receive physiological data between the one or more applications, wherein the physiological data is based at least in part on physiological measurements collected from each user in the group via wearable devices associated with the one or more applications; acquiring the physiological data from one or more applications; generating a score based at least in part on the physiological data acquired from one or more applications, the score indicating a physiological indicator representative of the group of users; and causing at least one GUI of the user device associated with the one or more applications to display the score.

[0156] An apparatus for sharing physiological data among a user group is described. The apparatus may include a processor, memory coupled to the processor, and instructions stored in the memory. These instructions are executable by the processor to cause the apparatus to: receive instructions from one or more applications associated with the user group, wherein the instructions include authorization to send and receive physiological data between the one or more applications, wherein the physiological data is based at least in part on physiological measurements collected from each user in the user group via wearable devices associated with the one or more applications; acquire the physiological data from one or more applications; generate a score based at least in part on the physiological data acquired from one or more applications, the score indicating physiological indicators representative of the user group; and cause at least one GUI of the user device associated with the one or more applications to display the score.

[0157] Another apparatus for sharing physiological data among a user group is described. The apparatus may include: means for receiving instructions from one or more applications associated with the user group, wherein the instructions include authorization to send and receive physiological data between the one or more applications, wherein the physiological data is based at least in part on physiological measurements collected from each user in the user group via wearable devices associated with the one or more applications; means for acquiring the physiological data from one or more applications; means for generating scores indicating physiological indicators representing the user group based at least in part on the physiological data acquired from one or more applications; and means for causing at least one GUI of a user device associated with one or more applications to display the scores.

[0158] A non-transitory computer-readable medium is described, storing code for sharing physiological data among a user group. The code may include processor-executable instructions for: receiving instructions from one or more applications associated with the user group, wherein the instructions include authorization to send and receive physiological data between the one or more applications, wherein the physiological data is based at least in part on physiological measurements collected from each user in the user group via wearable devices associated with the one or more applications; acquiring the physiological data from one or more applications; generating a score based at least in part on the physiological data acquired from one or more applications, the score indicating physiological indicators representative of the user group; and causing at least one GUI of a user device associated with one or more applications to display the score.

[0159] In some examples of the methods, apparatuses, and nontransitory computer-readable media described herein, the physiological data includes first physiological data associated with a first user in a user group and additional physiological data associated with the remaining users in the user group other than the first user, and the methods, apparatuses, and nontransitory computer-readable media may include further operations, features, devices, or instructions for: identifying that the first physiological data associated with the first user deviates from the additional physiological data associated with the remaining users by a threshold measure; and causing at least one GUI of the device to display an instruction for the first user based at least in part on the identification.

[0160] Some examples of the methods, apparatuses, and non-transitory computer-readable media described herein may also include operations, features, devices, or instructions for identifying spatial relationships between user groups and, at least in part, sending prompts for sharing physiological data among user groups based on the identification of such spatial relationships, wherein receiving instructions may be at least in part based on sending the prompts.

[0161] Some examples of the methods, apparatuses, and nontransitory computer-readable media described herein may also include operations, features, devices, or instructions for acquiring baseline physiological data associated with multiple users, including user groups, identifying one or more similarities between baseline physiological data associated with each user in the user group, and sending prompts for sharing physiological data among user groups based at least in part on the identification of one or more similarities, wherein receiving instructions may be based at least in part on sending prompts.

[0162] Some examples of the methods, apparatuses, and non-transitory computer-readable media described herein may also include methods for identifying calendar data associated with each user in a user group and causing at least one GUI of a user device associated with one or more applications to display recommended operations, features, devices, or instructions based at least in part on scores and calendar data.

[0163] Some examples of the methods, apparatuses, and nontransitory computer-readable media described herein may also include operations, features, devices, or instructions for receiving instructions on one or more authorized physiological parameters, instructions on one or more authorized time periods, or both, via an application in one or more applications associated with a first user in a user group, wherein obtaining physiological data from the application associated with the user includes obtaining physiological data associated with one or more authorized physiological parameters, obtaining physiological data within one or more authorized time periods, or both.

[0164] In some examples of the methods, apparatuses, and non-transitory computer-readable media described herein, at least one wearable device associated with each user in a user group includes a wearable ring device.

[0165] Some examples of the methods, apparatuses, and non-transitory computer-readable media described herein may also include operations, features, devices, or instructions for sending additional control signals to one or more external devices associated with the environment surrounding the user group, the additional control signals being configured to modify one or more operating parameters of one or more external devices to modify one or more features of the environment surrounding the user group.

[0166] Some examples of the methods, apparatuses, and non-transitory computer-readable media described herein may also include operations, features, devices, or instructions for: receiving calendar data associated with a user group; and sending additional control signals to adjust the timing of meetings associated with at least a subset of the user group, based at least in part on the calendar data and scores associated with the user group, wherein one or more recommendations or insights include recommendations for adjusting meeting times.

[0167] The description herein, illustrated with reference to the accompanying drawings, describes exemplary configurations and does not represent all examples that can be implemented or that are within the scope of the claims. The term "exemplary" as used herein means "serving as an example, instance, or illustration," and not "preferred" or "superior to other examples." Detailed descriptions include specific details for the purpose of providing an understanding of the described techniques. However, these techniques can be practiced without these specific details. In some instances, well-known structures and devices are shown in block diagram form to avoid obscuring the concepts of the described examples.

[0168] In the accompanying drawings, similar components or features may have the same reference numerals. Furthermore, various components of the same type can be distinguished by a reference numeral marked with a dash and a second numeral to differentiate them. If only the first reference numeral is used in the specification, the description applies to any of the similar components having the same first reference numeral, without regard to the second reference numeral.

[0169] The information and signals described herein can be represented using any of a variety of different techniques and means. For example, data, instructions, commands, information, signals, bits, symbols, and chips referred to in the above description can be represented by voltage, current, electromagnetic waves, magnetic fields or magnetic particles, optical fields or optical particles, or any combination thereof.

[0170] The various illustrative boxes and modules described in connection with this disclosure may be implemented or performed using a general-purpose processor, DSP, ASIC, FPGA or other programmable logic device, discrete gate or transistor logic, discrete hardware components, or any combination thereof designed to perform the functions described herein. The general-purpose processor may be a microprocessor, but alternatively, it may be any conventional processor, controller, microcontroller, or state machine. The processor may also be implemented as a combination of computing devices (e.g., a combination of a DSP and a microprocessor, multiple microprocessors, one or more microprocessors incorporating a DSP core, or any other such configuration).

[0171] The functions described herein can be implemented in hardware, software executed by a processor, firmware, or any combination thereof. If implemented in software executed by a processor, the functions can be stored on or transmitted via a computer-readable medium as one or more instructions or code. Other examples and implementations are within the scope of this disclosure and the appended claims. For example, due to the nature of software, the functions described above can be implemented using software executed by a processor, hardware, firmware, hardwired, or any combination thereof. Features implementing the functions can also be physically located in various locations, including being distributed such that different parts of the functions are implemented in different physical locations. Furthermore, as used herein, including in the claims, the word "or" as used in a list of items (e.g., a list of items beginning with phrases such as "at least one of" or "one or more") indicates an inclusive list, such that, for example, a list of at least one of A, B, or C means A or B or C, or AB or AC or BC, or ABC (i.e., A and B and C). Moreover, as used herein, the phrase "based on" should not be construed as referring to a set of closing conditions. For example, without departing from the scope of this disclosure, an exemplary step described as "based on condition A" may be based on both condition A and condition B. In other words, as used herein, the phrase "based on" should be interpreted in the same way as the phrase "at least partially based on".

[0172] Computer-readable media includes both non-transitory computer storage media and communication media, including any media that facilitates the transfer of a computer program from one place to another. Non-transitory storage media can be any available medium accessible by a general-purpose or special-purpose computer. By way of example, and not limitation, non-transitory computer-readable media may include RAM, ROM, electrically erasable programmable ROM (EEPROM), disc-on-CD ROM or other optical disk storage, magnetic disk storage or other magnetic storage devices, or any other means of carrying or storing desired program code in the form of instructions or data structures and accessible by a general-purpose or special-purpose computer, or a general-purpose or special-purpose processor. Furthermore, any connection is appropriately referred to as computer-readable media. For example, if software is transmitted from a website, server, or other remote source using coaxial cable, fiber optic cable, twisted pair, digital subscriber line (DSL), or wireless technologies such as infrared, radio, and microwave, then coaxial cable, fiber optic cable, twisted pair, DSL, or wireless technologies such as infrared, radio, and microwave are included in the definition of media. As used in this article, disks and optical discs include CDs, laser discs, optical discs, digital versatile discs (DVDs), floppy disks, and Blu-ray discs, where disks typically reproduce data magnetically, while optical discs use lasers to reproduce data optically. Combinations of these are also included within the scope of computer-readable media.

[0173] The description herein is provided to enable those skilled in the art to make or use this disclosure. Various modifications to this disclosure will be apparent to those skilled in the art, and the general principles defined herein may be applied to other variations without departing from the scope of this disclosure. Therefore, this disclosure is not limited to the examples and designs described herein, but is to be accorded the widest scope consistent with the principles and novel features disclosed herein.

Claims

1. A method for sharing physiological data, comprising: Send one or more requests via wireless electronic communication to establish a data sharing group associated with a user group; At least in part based on sending the one or more requests, receiving instructions from one or more applications associated with the user group via one or more wireless electronic communication links, wherein the instructions include authorization to send and receive physiological data between the one or more applications, and wherein the physiological data is at least in part based on physiological measurements collected from each user in the user group via wearable devices associated with the one or more applications; The physiological data is received from the one or more applications via the one or more wireless electronic communication links and at least in part based on the instructions. At least in part, based on the physiological data obtained from the one or more applications, scores indicating physiological indicators representing the user group are generated; and Control signals are transmitted via the one or more wireless electronic communication links to cause at least one graphical user interface of the one or more user devices associated with the one or more applications to display the score and one or more recommendations or insights associated with the score.

2. The method according to claim 1, wherein, The physiological data includes first physiological data associated with a first user in the user group and additional physiological data associated with the remaining users in the user group other than the first user. The method further includes: Identify a deviation of the first physiological data associated with the first user from the additional physiological data associated with the remaining users by a threshold metric; and Based at least in part on the identification, at least one graphical user interface of the one or more user devices displays the instructions of the first user.

3. The method according to claim 1, further comprising: Identify the spatial relationships between the user groups; as well as The prompt for sharing the physiological data among the user groups is sent based at least in part on the recognition of the spatial relationships, wherein receiving the instruction is based at least in part on sending the prompt.

4. The method according to claim 1, further comprising: Acquire baseline physiological data associated with multiple users, including the user group mentioned above; Identify one or more similarities between the baseline physiological data associated with each user in the user group; as well as The prompt for sharing the physiological data among the user groups is sent based at least in part on identifying one or more similarities, wherein receiving the instruction is based at least in part on sending the prompt.

5. The method according to claim 1, further comprising: Identify calendar data associated with each user in the user group; as well as This causes at least one graphical user interface of the one or more user devices associated with the one or more applications to display recommendations based at least in part on the scores and the calendar data.

6. The method according to claim 1, further comprising: Receiving instructions for one or more authorized physiological parameters, instructions for one or more authorized time periods, or both, via an application in one or more applications associated with a first user in the user group, wherein receiving the physiological data from the one or more applications includes receiving the physiological data associated with the one or more authorized physiological parameters, receiving the physiological data within the one or more authorized time periods, or both.

7. The method according to claim 1, wherein, At least one wearable device associated with each user in the user group includes a wearable ring device.

8. The method according to claim 1, wherein, The physiological data includes a first subset of physiological data corresponding to a first user in the user group, wherein the first subset of physiological data is associated with the physiological indicator, and the method further includes: The graphical user interface of the one or more user devices displays a comparison between the first subset of physiological data associated with the first user and the score indicating the physiological indicator representing the user group.

9. The method according to claim 1, further comprising: Additional control signals are sent to one or more external devices associated with the user group’s surrounding environment. These additional control signals are configured to modify one or more operating parameters of the one or more external devices to modify one or more characteristics of the user group’s surrounding environment.

10. The method according to claim 1, further comprising: Receive calendar data associated with the user group; as well as Send additional control signals to adjust the timing of meetings associated with at least one subset of the user group, based at least in part on the calendar data and the scores associated with the user group, wherein one or more recommendations or insights include recommendations to adjust the meeting times.

11. An apparatus for sharing physiological data, comprising: At least one processor; A memory coupled to the at least one processor; as well as Instructions, which are stored in the memory and can be executed by the at least one processor, to cause the device to: Send one or more requests via wireless electronic communication to establish one or more wireless electronic communication links with one or more user equipments associated with a user group; At least in part, based on sending the one or more requests via the one or more wireless electronic communication links, receiving instructions from one or more applications associated with the user group, wherein the instructions include authorization to send and receive physiological data between the one or more applications, and wherein the physiological data is at least in part based on physiological measurements collected from each user in the user group via wearable devices associated with the one or more applications; The physiological data is received from the one or more applications via the one or more wireless electronic communication links and at least in part based on the instructions. At least in part, based on the physiological data obtained from the one or more applications, scores indicating physiological indicators representing the user group are generated; and Control signals are transmitted via the one or more wireless electronic communication links to cause at least one graphical user interface of the one or more user devices associated with the one or more applications to display the score and one or more recommendations or insights associated with the score.

12. The apparatus according to claim 11, wherein, The physiological data includes first physiological data associated with a first user in the user group and additional physiological data associated with the remaining users in the user group other than the first user, and the instructions are also executable by the at least one processor to cause the device to: Identify a deviation of the first physiological data associated with the first user from the additional physiological data associated with the remaining users by a threshold metric; as well as Based at least in part on the identification, the at least one graphical user interface of the one or more user devices displays the instructions of the first user.

13. The apparatus of claim 11, wherein the instructions are further executable by the at least one processor to cause the apparatus to: Identify the spatial relationships between the user groups; and The prompt for sharing the physiological data among the user groups is sent based at least in part on the recognition of the spatial relationships, wherein receiving the instruction is based at least in part on sending the prompt.

14. The apparatus according to claim 11, wherein, The instructions can also be executed by the at least one processor to cause the device to: Acquire baseline physiological data associated with multiple users, including the user group mentioned above; Identify one or more similarities between the baseline physiological data associated with each user in the user group; as well as The prompt for sharing the physiological data among the user groups is sent based at least in part on identifying one or more similarities, wherein receiving the instruction is based at least in part on sending the prompt.

15. The apparatus according to claim 11, wherein, The instructions can also be executed by the at least one processor to cause the device to: Identify calendar data associated with each user in the user group; and This causes at least one graphical user interface of the one or more user devices associated with the one or more applications to display recommendations based at least in part on the scores and the calendar data.

16. The apparatus of claim 11, wherein the instructions are further executable by the at least one processor to cause the apparatus to: Receiving instructions for one or more authorized physiological parameters, instructions for one or more authorized time periods, or both, via an application in one or more applications associated with a first user in the user group, wherein receiving the physiological data from the one or more applications includes receiving the physiological data associated with the one or more authorized physiological parameters, receiving the physiological data within the one or more authorized time periods, or both.

17. The apparatus according to claim 11, wherein, At least one wearable device associated with each user in the user group includes a wearable ring device.

18. An apparatus for sharing physiological data, comprising: Device for transmitting one or more requests via wireless electronic communication to establish one or more wireless electronic communication links with one or more user equipment associated with a user group; Device for receiving instructions from one or more applications associated with the user group via one or more wireless electronic communication links, at least in part based on sending the one or more requests, wherein the instructions include authorization to send and receive physiological data between the one or more applications, and wherein the physiological data is at least in part based on physiological measurements collected from each user in the user group via wearable devices associated with the one or more applications. Device for receiving the physiological data from the one or more applications via the one or more wireless electronic communication links and at least in part based on the instructions; Device for generating scores indicating physiological indicators representing the user group, based at least in part on the physiological data obtained from the one or more applications; and A device for transmitting control signals via the one or more wireless electronic communication links to display the score and one or more recommendations or insights associated with the score in at least one graphical user interface of the one or more user devices associated with the one or more applications.

19. The apparatus according to claim 18, wherein, The physiological data includes first physiological data associated with a first user in the user group and additional physiological data associated with the remaining users in the user group other than the first user. The device further includes: Devices for identifying deviations of the first physiological data associated with the first user from the additional physiological data associated with the remaining users by a threshold metric; and A device for causing at least one graphical user interface of the one or more user devices to display the instructions of the first user, based at least in part on the identification.

20. A non-transitory computer-readable medium storing code for sharing physiological data, the code including instructions executable by a processor to: Send one or more requests via wireless electronic communication to establish one or more wireless electronic communication links with one or more user equipments associated with a user group; At least in part, this is based on receiving instructions from one or more applications associated with the user group via one or more wireless electronic communication links after sending the one or more requests, wherein... The instructions include authorization to send and receive physiological data between the one or more applications, and wherein the physiological data is based at least in part on physiological measurements collected from each user in the user group via wearable devices associated with the one or more applications; The physiological data is received from the one or more applications via the one or more wireless electronic communication links and at least in part based on the instructions. At least in part based on the physiological data obtained from the one or more applications, generate scores indicating physiological indicators representing the user group; and Control signals are transmitted via the one or more wireless electronic communication links to cause at least one graphical user interface of the one or more user devices associated with the one or more applications to display the score and one or more recommendations or insights associated with the score.

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