Techniques for wearable-based bidirectional data sharing

Abstract

A method, system, and device for wearable-based bidirectional data sharing is described. The system may receive instructions from a group of users to send and receive physiological data between each user of the group. The system may then aggregate user-specific physiological data for each user in the group, the physiological data collected via a wearable device associated with each 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 distribute the calculated score to each user of the group.

Description

[Technical Field]

[0001] [Cross reference] This patent application claims priority to 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 are assigned to the present assignee and expressly incorporated herein by reference.

[0002] [Technical field to which the invention belongs] The following relates to wearable devices and data processing, including techniques for wearable-based two-way sharing of data. [Background technology]

[0003] Some wearable devices may be configured to collect data from a user so that the user's user device can determine various health and wellness information for the user based on the data. Improved ways of sharing health and wellness information between users may be desirable. [Brief explanation of the drawings]

[0004] [Figure 1] 1 illustrates an example of a system supporting techniques for wearable-based two-way sharing of data according to aspects of the present disclosure. [Figure 2] 1 illustrates an example of a system supporting techniques for wearable-based two-way sharing of data according to aspects of the present disclosure. [Figure 3] 1 illustrates an example of a system supporting techniques for wearable-based two-way sharing of data according to aspects of the present disclosure. [Figure 4]1 illustrates an example of a process flow supporting techniques for wearable-based two-way sharing of data according to aspects of the present disclosure. [Figure 5] 1 illustrates a block diagram of an apparatus supporting techniques for wearable-based two-way sharing of data according to aspects of the present disclosure. [Figure 6] 1 illustrates a block diagram of a wearable application supporting techniques for wearable-based two-way sharing of data according to aspects of the present disclosure. [Figure 7] 1 illustrates a diagram of a system including a device supporting techniques for wearable-based two-way sharing of data according to aspects of the present disclosure. [Figure 8] 1 shows a flowchart illustrating a method for supporting techniques for wearable-based two-way sharing of data according to aspects of the present disclosure. DETAILED DESCRIPTION OF THE INVENTION

[0005] A user may wear a wearable device, such as a wearable ring device, that collects data, such as physiological data, from the user to determine various health and wellness information for the user. Additionally, some users may wish to receive health and wellness information from other users, such as parents, grandparents, spouses, children, and close friends. However, indiscriminately sharing large amounts of health and wellness information may compromise privacy or make it difficult for users to view and analyze, thereby reducing the usability and therefore value of the shared information. This problem is compounded when a user wishes to receive health and wellness information from multiple users, such as multiple family members. As a result, a user may be limited in their ability to interact with, manage, or support groups of people based on their health and wellness.

[0006] According to the techniques described herein, data about a group of people may be obtained and used to generate one or more composite health and wellness scores or insights for the group, which may be used to generate one or more recommendations for the group. For example, a user may join a group of users who are authorized to share health and wellness data (e.g., by their user devices), thereby generating composite health and wellness information for the group using data collected by the users' wearable devices. The composite score calculated for the group may be used to efficiently convey information about the group's overall health, the group's overall mood or emotions, etc. In some examples, the group's composite health and wellness information may also be used as a basis for generating one or more recommendations for the group. Such techniques may enable improved community interaction and support. Furthermore, by aggregating user-specific data and generating a composite health or wellness score representative of the entire group, the techniques described herein may improve users' ability to view and act on health and wellness data for the entire group of users, as well as for individual users within the group.

[0007] Additionally or alternatively, the person-specific data for a group of people may be displayed on an individual basis so that others in the group can provide reactions (e.g., encouragement, suggestions) or modify their own behavior in response to viewing the person-specific data of others. For example, displaying a first user's person-specific health and wellness information to a second user may cause the second user's user device to prompt the second user to send a message (e.g., text, emoji) to the first user based on the person-specific health and wellness information.

[0008] Aspects of the present disclosure are first described in the context of a system that supports physiological data collection from a user via a wearable device. Aspects of the present disclosure are further illustrated by and described with reference to system and process flows. Aspects of the present disclosure are further illustrated by and described with reference to apparatus diagrams, system diagrams, and flowcharts relating to techniques for wearable-based bidirectional sharing of data.

[0009] 1 illustrates an example of a system 100 that supports techniques for wearable-based interactive sharing of data according to aspects of the present disclosure. System 100 includes multiple electronic devices (e.g., wearable devices 104, user devices 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.

[0010] The electronic devices may include any electronic devices known in the art, such as wearable devices 104 (e.g., ring wearable devices, wristwatch wearable devices, etc.), user devices 106 (e.g., smartphones, laptops, tablets), etc. The electronic devices associated with each 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 to the user 102 (e.g., via a GUI) based on the processed data, and 5) communicating data with each other and / or other computing devices. Different electronic devices may perform one or more of these functions.

[0011] Exemplary wearable devices 104 may include wearable computing devices such as a ring computing device (hereinafter, “ring”) configured to be worn on the finger of the user 102, a wrist computing device (e.g., a smartwatch, fitness band, or bracelet) configured to be worn on the wrist of the user 102, and / or a head-mounted computing device (e.g., eyeglasses / goggles). The wearable devices 104 may also include bands, straps (e.g., flexible or non-flexible bands or straps), stick-on sensors, etc., which may be positioned in other locations such as bands around the head (e.g., a forearm band and / or a bicep band), and / or bands around the leg (e.g., a thigh or calf band), behind the ear, under the arm, etc. The wearable devices 104 may be attached to or included in clothing. For example, the wearable devices 104 may be included in a pocket and / or pouch of the clothing. As another example, the wearable device 104 may be clipped and / or pinned to clothing or otherwise held within proximity of the user 102. Examples of clothing may include, but are not limited to, hats, shirts, gloves, pants, socks, outerwear (e.g., jackets), and underwear. In some implementations, the wearable device 104 may be included in other types of devices, such as training / sports devices used during physical activity. For example, the wearable device 104 may be attached to or included in a bicycle, skis, tennis racket, golf club, and / or training weights.

[0012] Much of the present disclosure may be described in the context of a ring wearable device 104. Accordingly, terms such as "ring 104," "wearable device 104," and the like may be used interchangeably unless otherwise noted herein. However, use of the term "ring 104" should not be considered limiting, as it is contemplated herein that aspects of the present disclosure may be implemented using other wearable devices (e.g., wristwatch wearable devices, necklace wearable devices, bracelet wearable devices, earring wearable devices, anklet wearable devices, etc.).

[0013] In some aspects, the user devices 106 may include handheld mobile computing devices such as smartphones and tablet computing devices. The user devices 106 may also include personal computers such as laptops and desktop computing devices. Other exemplary user devices 106 may include server computing devices that may communicate with other electronic devices (e.g., via the Internet). In some implementations, the computing devices may include medical devices such as external wearable computing devices (e.g., Holter monitors). Medical devices may also include implantable medical devices such as pacemakers and cardioverter-defibrillators. Other exemplary user devices 106 may include home computing devices such as Internet of Things (IoT) devices (e.g., IoT devices), smart TVs, smart speakers, smart displays (e.g., video calling displays), hubs (e.g., wireless communication hubs), security systems, smart appliances (e.g., thermostats and refrigerators), and fitness equipment.

[0014] Some electronic devices (e.g., wearable device 104, user device 106) may measure physiological parameters of each user 102, such as photoplethysmography waveform, continuous skin temperature, pulse waveform, respiration rate, heart rate, heart rate variability (HRV), actigraphy, galvanic skin response, pulse oximetry, and / or other physiological parameters. Some electronic devices that measure physiological parameters may also perform some / all of the calculations described herein. Some electronic devices may not measure physiological parameters and 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 received physiological data measured by other devices.

[0015] In some implementations, the user 102 may operate or be associated with multiple electronic devices, some of which may measure physiological parameters and others of which may process the measured physiological parameters. In some implementations, the user 102 may have a ring (e.g., a wearable device 104) that measures physiological parameters. The user 102 may also have or be associated with a user device 106 (e.g., a mobile device, a smartphone), where the wearable device 104 and the user device 106 are communicatively coupled to each other. In some cases, the user device 106 may receive data from the wearable device 104 and perform some / all of the calculations described herein. In some implementations, the user device 106 may also measure physiological parameters described herein, such as motion / activity parameters.

[0016] 1 , a first user 102-a (user 1) may operate or be associated with a wearable device 104-a (e.g., ring 104-a) and a user device 106-a, which may operate as described herein. In this example, the user device 106-a associated with user 102-a may process / store physiological parameters measured by the ring 104-a. In comparison, a second user 102-b (user 2) may be associated with a ring 104-b, a wristwatch wearable device 104-c (e.g., watch 104-c), and a user device 106-b, and the user device 106-b associated with user 102-b may process / store physiological parameters measured by the ring 104-b and / or watch 104-c. Additionally, an nth user 102-n (user N) may be associated with an arrangement of electronic devices (e.g., ring 104-n, user device 106-n) described herein. In some aspects, wearable devices 104 (e.g., ring 104, watch 104) and other electronic devices may be communicatively coupled to the user device 106 of each user 102 via Bluetooth, Wi-Fi, and other wireless protocols.

[0017] In some implementations, the ring 104 (e.g., the wearable device 104) of the system 100 may be configured to collect physiological data from each user 102 based on arterial blood flow within the user's finger. In particular, the ring 104 may utilize one or more light-emitting components, such as LEDs (e.g., red LEDs, green LEDs) that emit light toward the palm side of the user's finger to collect physiological data based on the arterial blood flow within the user's finger. In general, the terms light-emitting component, light-emitting element, and the like may include, but are not limited to, LEDs, micro-LEDs, mini-LEDs, laser diodes (LDs) (e.g., vertical-cavity surface-emitting lasers (VCSELs)), and the like.

[0018] In some cases, system 100 may be configured to collect physiological data from each user 102 based on diffused blood flow within the skin's microvascular bed, which includes capillaries and arterioles. For example, system 100 may collect PPG data based on measured amounts of diffused blood in the microvasculature of capillaries and arterioles. In some implementations, ring 104 may acquire physiological data using a combination of both green and red LEDs. The physiological data may include any physiological data known in the art, including, but not limited to, temperature data, accelerometer data (e.g., movement / motion data), heart rate data, HRV data, blood oxygen level data, or any combination thereof.

[0019] The use of both red and green LEDs may offer several advantages over other solutions, as red and green LEDs have been found to each have their own distinct advantages, such as when acquiring physiological data over different parts of the body under different conditions (e.g., light / dark, activity / inactivity). For example, green LEDs have been found to perform better during exercise. Furthermore, the use of multiple LEDs (e.g., green and red LEDs) distributed around the ring 104 has been found to perform better than wearable devices that utilize LEDs placed closely together, such as in a wristwatch wearable device. Furthermore, blood vessels (e.g., arteries, capillaries) in the fingers are more easily accessible via LEDs compared to blood vessels in the wrist. In particular, wrist arteries are located on the lower part of the wrist (e.g., the palm side of the wrist), which means that only capillaries are accessible at the upper part of the wrist (e.g., the back side of the wrist), where wearable watch devices and similar devices are typically worn. As such, utilizing LEDs and other sensors within the ring 104 has been found to provide superior performance compared to wearable devices worn on the wrist, as the ring 104 has greater access to arteries (as compared to capillaries), which can result in stronger signals and more useful physiological data.

[0020] The electronic devices of the system 100 (e.g., the user device 106, the wearable device 104) may be communicatively coupled to one or more servers 110 via wired or wireless communication protocols. For example, as shown in FIG. 1 , the electronic devices (e.g., the user device 106) may be communicatively coupled to one or more servers 110 via a network 108. The network 108 may implement a Transmission Control Protocol and Internet Protocol (TCP / IP), such as the Internet, or may implement other network 108 protocols. The network connection between the network 108 and each electronic device may facilitate the transfer of data via email, web, text message, mail, or any other suitable form of interaction within the computer network 108. For example, in some implementations, a ring 104-a associated with a first user 102-a may be communicatively coupled to a user device 106-a, which is communicatively coupled to the server 110 via the network 108. In additional or alternative cases, the wearable device 104 (e.g., ring 104, watch 104) may be directly communicatively coupled to the network 108.

[0021] The system 100 may provide on-demand database services between the user devices 106 and one or more servers 110. In some cases, the servers 110 may receive data from the user devices 106 over the network 108 and may store and analyze the data. Similarly, the servers 110 may provide data to the user devices 106 over the network 108. In some cases, the servers 110 may be located in one or more data centers. The servers 110 may be used for data storage, management, and processing. In some implementations, the servers 110 may provide a web-based interface to the user devices 106 via a web browser.

[0022] In some embodiments, the system 100 may detect periods during which the user 102 is asleep and classify the periods during which the user 102 is asleep into one or more sleep stages (e.g., sleep stage classification). For example, as shown in FIG. 1, the user 102-a may be associated with a wearable device 104-a (e.g., a ring 104-a) and a user device 106-a. In this example, the ring 104-a may collect physiological data associated with the user 102-a, including temperature, heart rate, HRV, respiratory rate, etc. In some embodiments, the data collected by the ring 104-a may be input into a machine learning classifier, which is configured to determine periods during which the user 102-a is asleep (or was asleep). Furthermore, the machine learning classifier may be configured to classify the periods into different sleep stages, including a wake sleep stage, a rapid eye movement (REM) sleep stage, a light sleep stage (non-REM), and a deep sleep stage (NREM). In some aspects, the classified sleep stages may be displayed to the user 102-a via a GUI of the user device 106-a. The sleep stage classification may be used to provide the user 102-a with feedback regarding the user's sleep patterns, such as a recommended bedtime, a recommended wake-up time, etc. Additionally, in some implementations, the sleep stage classification techniques described herein may be used to calculate a score for each user, such as a sleep score, a readiness score, etc.

[0023] In some embodiments, the system 100 may utilize features derived from circadian rhythms to further improve physiological data collection, data processing procedures, and other techniques described herein. The term circadian rhythm may refer to the natural internal process that regulates an individual's sleep-wake cycle, which repeats approximately every 24 hours. In this regard, the techniques described herein may utilize a circadian rhythm adjustment model to improve physiological data collection, analysis, and data processing. For example, the circadian rhythm adjustment model may be input into a machine learning classifier along with physiological data collected from the user 102-a via the wearable device 104-a. In this example, the circadian rhythm adjustment model may be configured to “weight” or adjust the physiological data collected throughout the user's natural approximately 24-hour circadian rhythm. In some implementations, the system may initially start with a “baseline” circadian rhythm adjustment model and use physiological data collected from each user 102 to modify the baseline model and generate an adjusted, individual circadian rhythm adjustment model specific to each respective user 102.

[0024] In some embodiments, system 100 may utilize other biological rhythms to further improve physiological data collection, analysis, and processing according to the phases of these other rhythms. For example, if a weekly rhythm is detected in an individual's baseline data, the model may be configured to adjust the "weight" of the data by day of the week. Biological rhythms that may require model adjustment in this manner include: 1) ultradian rhythms (rhythms faster than a day, including sleep cycles during sleep states and oscillations in measured physiological variables with periodicity of less than an hour to several hours during wakefulness); 2) circadian rhythms; 3) non-endogenous diurnal rhythms that have been shown to be imposed on circadian rhythms, such as work schedules; 4) weekly rhythms or other exogenously imposed artificial time periodicities (e.g., a hypothetical culture with a 12-day "week" might use a 12-day rhythm); 5) multiday ovarian rhythms in women and spermatogenic rhythms in men; 6) lunar rhythms (relevant to individuals living with little or no artificial light); and 7) seasonal rhythms.

[0025] Biological rhythms are not necessarily stationary. For example, many women experience variability in ovarian cycle length across cycles, and ultradian rhythms are unlikely to occur at exactly the same time or periodicity across days, even within a single user. Therefore, signal processing methods sufficient to quantify the frequency components while maintaining the temporal resolution of these rhythms in physiological data can be used to improve detection of these rhythms and assign a phase for each rhythm to each measured time point, thereby modifying adjustment models and comparisons of time intervals. Biological rhythm adjustment models and parameters can be added in linear or nonlinear combinations as needed to more accurately capture the dynamic physiological baseline of an individual or group of individuals.

[0026] In some examples, a user device 106 of a user 102 may receive information collected by the wearable devices of other users 102, allowing the user 102 to view information about the other users 102. However, in some cases, the user device 106 may process and display information on a per-user basis, which may prevent the user 102 from gaining a holistic view of the health and well-being of other users as a group (e.g., a sports team, a family unit, a workgroup). Furthermore, large amounts of data received from other users 106 in a group may be difficult for the user 102 to view and analyze, which may reduce the usability and, therefore, value of the received data. As a result, the user 102 may not be able to manage, interact with, or support the group in a way that considers the overall health and well-being of the group.

[0027] According to the techniques described herein, a user device 106 may receive user-specific information collected by the wearable devices 104 of a group of authorized users and generate composite health and wellness information for the group of users based on that information. To receive information from other users in the group, the user device 106 may allow the sharing of information collected about the user 102 of the user device 106 (e.g., the user may join or start / create a group as a participant whose information is exchanged with other members of the group). Although described with reference to a single group, the user 102 may be part of multiple groups, each of which may have a respective composite score and insight generated based on the information collected by the wearable devices 104 of users in that group. In some examples, a group of users who have allowed in-group information sharing may be referred to as a circle, a trusted circle, or other suitable term.

[0028] Additionally or alternatively, user devices 106 in a group may display user-specific information for each user so that group members can track each other's health and wellness, which may encourage constructive intra-group interactions and induce improved individual behaviors. For example, a user device 106 displaying user-specific sleep scores for group members may prompt the user of the user device 106 to provide feedback on the sleep score (e.g., via the user device 106) and / or recommend sleep-specific suggestions (e.g., an earlier bedtime) to the user based on the sleep score. A first user's user-specific health and wellness information sent to a second user may be compressed and displayed differently (e.g., in an easier-to-parse format or with enhanced privacy protection) on the second user's user device compared to the first user's user device.

[0029] Those skilled in the art will appreciate that one or more aspects of the present disclosure may be implemented in system 100 to additionally or alternatively solve problems other than those discussed above. Furthermore, aspects of the present disclosure may provide technical improvements over the "conventional" systems or processes described herein. However, the description and accompanying drawings only include exemplary technical improvements resulting from implementing aspects of the present disclosure and therefore may not represent all of the technical improvements provided within the scope of the claims.

[0030] 2 illustrates an example of a system 200 that supports techniques for wearable-based two-way sharing of data according to aspects of the present disclosure. System 200 may implement or be implemented by system 100. In particular, system 200 illustrates an example of a ring 104 (e.g., wearable device 104), a user device 106, and a server 110, as described with reference to FIG.

[0031] In some embodiments, the ring 104 may be configured to be worn on a user's finger and may determine one or more user physiological parameters when worn on the user's finger. Exemplary measurements and determinations may include, but are not limited to, user skin temperature, pulse waveform, respiratory rate, heart rate, HRV, blood oxygen level, etc.

[0032] The system 200 further includes a user device 106 (e.g., a smartphone) that communicates with the ring 104. For example, the ring 104 may be in wireless and / or wired communication with the user device 106. In some implementations, the ring 104 may transmit measured and processed data (e.g., temperature data, photoplethysmography (PPG) data, motion / accelerometer data, ring input data, etc.) to the user device 106. The user device 106 may also transmit data to the ring 104, such as firmware / configuration updates for the ring 104. The user device 106 may process the data. In some implementations, the user device 106 may transmit the data to the server 110 for processing and / or storage.

[0033] The ring 104 may include a housing 205, which may include an inner housing 205-a and an outer housing 205-b. In some embodiments, the housing 205 of the ring 104 may store or otherwise contain various components of the ring, including, but not limited to, the device electronics, a power source (e.g., a battery 210 and / or a capacitor), one or more boards (e.g., printable circuit boards) interconnecting the device electronics and / or the power source, etc. The device electronics may include device modules (e.g., hardware / software) such as a processing module 230-a, a memory 215, a communication module 220-a, a power module 225, etc. The device electronics may also include one or more sensors. Exemplary sensors may include one or more temperature sensors 240, a PPG sensor assembly (e.g., a PPG system 235), and one or more motion sensors 245.

[0034] The sensors may include associated modules (not shown) configured to communicate with the respective components / modules of ring 104 and generate signals associated with the respective sensors. In some aspects, each of the components / modules of ring 104 may be communicatively coupled to one another via a wired or wireless connection. Additionally, ring 104 may include additional and / or alternative sensors or other components configured to collect physiological data from the user, including optical sensors (e.g., LEDs), oximeters, etc.

[0035] The ring 104 shown and described with reference to FIG. 2 is provided for illustrative purposes only. As such, the ring 104 may include additional or alternative components such as those shown in FIG. 2. Other rings 104 may be manufactured that provide the functionality described herein. For example, rings 104 may be manufactured with fewer components (e.g., sensors). In a specific example, a ring 104 may be manufactured with a single temperature sensor 240 (or other sensor), a power source, and device electronics configured to read the single temperature sensor 240 (or other sensor). In another specific example, the temperature sensor 240 (or other sensor) may be attached to a user's finger (e.g., using a clamp, a spring-loaded clamp, etc.). In this case, the sensor may be wired to another computing device, such as a wrist-worn computing device, that reads the temperature sensor 240 (or other sensor). In other examples, rings 104 may be manufactured that include additional sensors and processing capabilities.

[0036] The housing 205 may include one or more housing 205 components. The housing 205 may include an outer housing 205-b component (e.g., a shell) and an inner housing 205-a component (e.g., a molding). The housing 205 may include additional components (e.g., additional layers) not explicitly shown in FIG. 2 . For example, in some implementations, the ring 104 may include one or more insulating layers that electrically insulate the device electronics and other conductive materials (e.g., electrical traces) from the outer housing 205-b (e.g., a metal outer housing 205-b). The housing 205 may provide structural support to the device electronics, battery 210, board(s), and other components. For example, the housing 205 may protect the device electronics, battery 210, and board(s) from mechanical forces such as pressure and impact. The housing 205 may also protect the device electronics, battery 210, and board(s) from water and / or other chemicals.

[0037] The outer housing 205-b can be fabricated from one or more materials. In some implementations, the outer housing 205-b can include a metal such as titanium, which can provide strength and wear resistance while being relatively lightweight. The outer housing 205-b can also be manufactured from other materials, such as polymers. In some implementations, the outer housing 205-b can be decorative as well as protective.

[0038] The inner housing 205-a may be configured to interface with a user's finger. The inner housing 205-a may be formed from a polymer (e.g., a medical-grade polymer) or other material. In some implementations, the inner housing 205-a may be transparent. For example, the inner housing 205-a may be transparent to light emitted by a PPG light-emitting diode (LED). In some implementations, the inner housing 205-a components may be molded onto the outer housing 205-b. For example, the inner housing 205-a may include a polymer molded (e.g., injection molded) to fit into the metal shell of the outer housing 205-b.

[0039] The ring 104 may include one or more substrates (not shown). The device electronics and battery 210 may be included on the one or more substrates. For example, the device electronics and battery 210 may be mounted on one or more substrates. An exemplary substrate may include one or more printed circuit boards (PCBs), such as a flexible PCB (e.g., polyimide). In some implementations, the electronics / battery 210 may include a surface-mounted device (e.g., a surface-mount technology (SMT) device) on a flexible PCB. In some implementations, the one or more substrates (e.g., one or more flexible PCBs) may include electrical traces that provide electrical communication between the device electronics. The electrical traces may also connect the battery 210 to the device electronics.

[0040] The device electronics, battery 210, and substrate may be arranged in a variety of ways within ring 104. In some implementations, one substrate containing the device electronics may be mounted along the bottom (e.g., bottom half) of ring 104 so that sensors (e.g., PPG system 235, temperature sensor 240, motion sensor 245, and other sensors) interface with the underside of a user's finger. In these implementations, battery 210 may be included along the top of ring 104 (e.g., on a separate substrate).

[0041] The various components / modules of ring 104 represent functions (e.g., circuits and other components) that may be included in ring 104. A module may include any discrete and / or integrated electronic circuit components that implement analog and / or digital circuits capable of producing the functions attributed to the module herein. For example, a module may include analog circuitry (e.g., amplification circuitry, filtering circuitry, analog-to-digital conversion circuitry, and / or other signal conditioning circuitry). A module may also include digital circuitry (e.g., combinational or sequential logic circuitry, memory circuitry, etc.).

[0042] The memory 215 (memory module) of the ring 104 may include any volatile, nonvolatile, magnetic, or electrical medium, such as random access memory (RAM), read-only memory (ROM), nonvolatile RAM (NVRAM), electrically erasable programmable ROM (EEPROM), flash memory, or any other memory device. The memory 215 may store any of the data described herein. For example, the memory 215 may be configured to store data (e.g., motion data, temperature data, PPG data) collected by the respective sensors and the PPG system 235. Additionally, the memory 215 may include instructions that, when executed by one or more processing circuits, cause the modules to perform various functions attributed to the modules herein. The device electronics of the ring 104 described herein are merely exemplary device electronics. As such, the types of electronic components used to implement the device electronics may vary based on design considerations.

[0043] The functionality attributed to the modules of ring 104 described herein may be embodied as one or more processors, hardware, firmware, software, or any combination thereof. The depiction of different features as modules is intended to emphasize different functional aspects and does not necessarily imply that such modules must be realized by separate hardware / software components. Rather, the functionality associated with one or more modules may be performed by separate hardware / software components or integrated within a common hardware / software component.

[0044] The processing module 230-a of the ring 104 may include one or more processors (e.g., processing units), microcontrollers, digital signal processors, systems-on-chips (SoCs), and / or other processing devices. The processing module 230-a communicates with the modules included in the ring 104. For example, the processing module 230-a may send / receive data to / from other components of the ring 104, such as modules and sensors. As described herein, the modules may be implemented by various circuit components. Thus, the modules may also be referred to as circuits (e.g., communication circuits and power circuits).

[0045] The processing module 230-a may be in communication with the memory 215. The memory 215 may include computer-readable instructions that, when executed by the processing module 230-a, cause the processing module 230-a to perform various functions attributed to the processing module 230-a herein. In some implementations, the processing module 230-a (e.g., a microcontroller) may include additional features associated with other modules, such as communication capabilities provided by the communication module 220-a (e.g., an integrated Bluetooth Low Energy transceiver) and / or additional on-board memory 215.

[0046] The communication module 220-a may include circuitry for providing wireless and / or wired communication with the user device 106 (e.g., the communication module 220-b of the user device 106). In some implementations, the communication modules 220-a, 220-b may include wireless communication circuitry such as Bluetooth circuitry and / or Wi-Fi circuitry. In some implementations, the communication modules 220-a, 220-b may include wired communication circuitry such as Universal Serial Bus (USB) communication circuitry. Using the communication module 220-a, the ring 104 and the user device 106 may be configured to communicate with each other. The ring's processing module 230-a may be configured to send / receive data to / from the user device 106 via the communication module 220-a. Exemplary data may include, but is not limited to, motion data, temperature data, pulse waveforms, heart rate data, HRV data, PPG data, and status updates (e.g., charging status, battery charge level, and / or ring 104 configuration settings). The ring processing module 230-a may also be configured to receive updates (eg, software / firmware updates) and data from the user device 106.

[0047] The ring 104 may include a battery 210 (e.g., a rechargeable battery 210). An exemplary battery 210 may include a lithium-ion or lithium polymer type battery 210, although various battery 210 options are possible. The battery 210 may be wirelessly recharged. In some implementations, the ring 104 may include a power source other than the battery 210, such as a capacitor. The power source (e.g., the battery 210 or capacitor) may have a curved geometry that matches the curved surface of the ring 104. In some aspects, the charger or other power source may include additional sensors that may be used to collect data in addition to or supplemental to data collected by the ring 104 itself. Additionally, the charger or other power source for the ring 104 may function as a user device 106, in which case the charger or other power source for the ring 104 may be configured to receive data from the ring 104, store and / or process data received from the ring 104, and communicate data between the ring 104 and the server 110.

[0048] In some aspects, the ring 104 includes a power module 225 that can control charging of the battery 210. For example, the power module 225 can interface with an external wireless charger that charges the battery 210 when interfaced with the ring 104. The charger can include reference structures that mate with reference structures on the ring 104 to create a designated orientation with the ring 104 during charging. The power module 225 can also regulate the voltage(s) of the device electronics, regulate the power output to the device electronics, and monitor the state of charge of the battery 210. In some implementations, the battery 210 can include a protection circuit module (PCM) that protects the battery 210 from high-current discharge, overvoltage during charging, and undervoltage during discharging. The power module 225 can include electrostatic discharge (ESD) protection.

[0049] One or more temperature sensors 240 may be electrically coupled to the processing module 230-a. The temperature sensor 240 may be configured to generate a temperature signal (e.g., temperature data) indicative of a temperature read or sensed by the temperature sensor 240. The processing module 230-a may determine the user's temperature at the location of the temperature sensor 240. For example, in the ring 104, the temperature data generated by the temperature sensor 240 may indicate the user's temperature (e.g., skin temperature) at the user's finger. In some implementations, the temperature sensor 240 may contact the user's skin. In other implementations, a portion of the housing 205 (e.g., the inner housing 205-a) may form a barrier (e.g., a thin thermally conductive barrier) between the temperature sensor 240 and the user's skin. In some implementations, the portion of the ring 104 configured to contact the user's finger may have a thermally conductive portion and a thermally insulating portion. The thermally conductive portion may conduct heat from the user's finger to the temperature sensor 240. The insulating portion may insulate portions of the ring 104 (eg, the temperature sensor 240) from the ambient temperature.

[0050] In some implementations, the temperature sensor 240 may generate a digital signal (e.g., temperature data) that the processing module 230-a may use to determine the temperature. As another example, if the temperature sensor 240 includes a passive sensor, the processing module 230-a (or the temperature sensor 240 module) may measure the current / voltage generated by the temperature sensor 240 and determine the temperature based on the measured current / voltage. An exemplary temperature sensor 240 may include a thermistor, such as a negative temperature coefficient (NTC) thermistor, or other types of sensors including resistors, transistors, diodes, and / or other electrical / electronic components.

[0051] The processing module 230-a may sample the user's temperature over time. For example, the processing module 230-a may sample the user's temperature according to a sampling rate. An exemplary sampling rate may include 1 sample / second, although the processing module 230-a may be configured to sample the temperature signal at other sampling rates higher or lower than 1 sample / second. In some implementations, the processing module 230-a may sample the user's temperature continuously throughout the day and night. Sampling at a sufficient rate (e.g., 1 sample / second) throughout the day may provide sufficient temperature data for the analysis described herein.

[0052] The processing module 230-a may store the sampled temperature data in the memory 215. In some implementations, the processing module 230-a may process the sampled temperature data. For example, the processing module 230-a may determine an average temperature value over a period of time. In one example, the processing module 230-a may determine an average temperature value every minute by summing all temperature values ​​collected in one minute and dividing by the number of samples in one minute. In a specific example where temperatures are sampled at one sample per second, the average temperature may be the sum of all temperatures sampled in that minute divided by 60 seconds. The memory 215 may store average temperature values ​​over time. In some implementations, the memory 215 may store average temperatures (e.g., one per minute) instead of sampled temperatures to conserve memory 215.

[0053] The sampling rate, which may be stored in memory 215, may be configurable. In some implementations, the sampling rate may be the same throughout the day and night. In other implementations, the sampling rate may vary throughout the day / night. In some implementations, the ring 104 may filter / reject temperature readings, such as large spikes in temperature (e.g., temperature spikes from a hot shower), that are not indicative of physiological changes. In some implementations, the ring 104 may 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).

[0054] The ring 104 (e.g., a communications module) may transmit the sampled and / or average temperature data to the user device 106 for storage and / or further processing. The user device 106 may forward the sampled and / or average temperature data to the server 110 for storage and / or further processing.

[0055] Although the ring 104 is shown as including a single temperature sensor 240, the ring 104 may include multiple temperature sensors 240 in one or more locations, such as disposed along the inner housing 205-a near the user's finger. In some implementations, the temperature sensor 240 may be a stand-alone temperature sensor 240. Additionally or alternatively, one or more temperature sensors 240 may be included with (e.g., packaged with) other components, such as an accelerometer and / or a processor.

[0056] The processing module 230-a may 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, the processing module 230 may individually sample, average, and store temperature data from each of the multiple temperature sensors 240. In other examples, the processing module 230-a may sample the sensors at different rates and average / store different values ​​for the different sensors. In some implementations, the processing module 230-a may be configured to determine a single temperature based on an average of two or more temperatures determined by two or more temperature sensors 240 at different locations on the finger.

[0057] The temperature sensor 240 on the ring 104 may acquire a distal temperature at a user's finger (e.g., any finger). For example, one or more temperature sensors 240 on the ring 104 may acquire the user's temperature from the underside of the finger or at different locations on the finger. In some implementations, the ring 104 may continuously acquire the distal temperature (e.g., at a sampling rate). Although distal temperatures measured by the ring 104 at the finger are described herein, other devices may 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 location. Additionally, the distal temperature measured at a user's finger (e.g., "shell" temperature) may differ from the user's core temperature. As such, the ring 104 may provide a useful temperature signal that may not be acquired at other internal / external body locations. In some cases, continuous temperature measurement at the finger may capture temperature fluctuations (e.g., small or large fluctuations) that may not be apparent in the core temperature. For example, continuous temperature measurements at the finger may capture minute-by-minute or hour-by-hour temperature fluctuations, providing additional insight that may not be provided by other temperature measurements elsewhere on the body.

[0058] The ring 104 may include a PPG system 235. The PPG system 235 may include one or more optical transmitters that transmit light. The PPG system 235 may also include one or more optical receivers that receive light transmitted by the one or more optical transmitters. The optical receivers may generate a signal (hereinafter, a "PPG" signal) that indicates the amount of light received by the optical receivers. The optical transmitters 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. The processing module 230-a may sample the PPG signal and determine the user's pulse waveform based on the PPG signal. The processing module 230-a may determine various physiological parameters, such as the user's respiratory rate, heart rate, HRV, oxygen saturation, and other circulatory parameters, based on the user's pulse waveform.

[0059] In some implementations, the PPG system 235 may be configured as a reflective PPG system 235 in which optical receiver(s) receive transmitted light reflected through a region of the user's finger. In some implementations, the PPG system 235 may be configured as a transmissive PPG system 235 in which optical transmitter(s) and optical receiver(s) are arranged opposite each other so that light is transmitted directly through a portion of the user's finger to the optical receiver(s).

[0060] The number and ratio of transmitters and receivers included in the PPG system 235 may vary. Exemplary optical transmitters may include light-emitting diodes (LEDs). The optical transmitters may transmit light in the infrared spectrum and / or other spectrums. Exemplary optical receivers may include, but are not limited to, optical sensors, phototransistors, and photodiodes. The optical receivers may be configured to generate PPG signals in response to wavelengths received from the optical transmitters. The locations of the transmitters and receivers may vary. Additionally, a single device may include a reflective and / or transmissive PPG system 235.

[0061] 2 may, in some implementations, include a reflective PPG system 235. In these implementations, the PPG system 235 may include a centrally located optical receiver (e.g., at the bottom of the ring 104) and two optical transmitters located on either side of the optical receiver. In this implementation, the PPG system 235 (e.g., the optical receiver) may generate a PPG signal based on light received from one or both of the optical transmitters. In other implementations, other arrangements, combinations, and / or configurations of one or more optical transmitters and / or optical receivers are contemplated.

[0062] The processing module 230-a may control one or both of the optical transmitters to transmit light while sampling the PPG signal generated by the optical receiver. In some implementations, the processing module 230-a may cause the optical transmitter with a stronger received signal to transmit light while sampling the PPG signal generated by the optical receiver. For example, the selected optical transmitter may emit light continuously while the PPG signal is sampled at a sampling rate (e.g., 250 Hz).

[0063] Sampling the PPG signal generated by the PPG system 235 can result in a pulse waveform, which can be referred to as a "PPG." The pulse waveform can indicate blood pressure versus time for multiple cardiac cycles. The pulse waveform can include peaks indicative of cardiac cycles. Additionally, the pulse waveform can include respiratory-induced variations, which can be used to determine respiratory rate. The processing module 230-a, in some implementations, can store the pulse waveform in memory 215. The processing module 230-a can process the pulse waveform as it is generated and / or from memory 215 to determine physiological parameters of the user as described herein.

[0064] The processing module 230-a may determine the user's heart rate based on the pulse waveform. For example, the processing module 230-a may determine the heart rate (e.g., beats per minute) based on the time between peaks in the pulse waveform. The time between peaks may be referred to as the interbeat interval (IBI). The processing module 230-a may store the determined heart rate value and IBI value in the memory 215.

[0065] The processing module 230-a may determine HRV over time. For example, the processing module 230-a may determine HRV based on variations in IBI. The processing module 230-a may store the HRV values ​​over time in memory 215. Additionally, the processing module 230-a may determine the user's respiration rate over time. For example, the processing module 230-a may determine the respiration rate based on frequency modulation, amplitude modulation, or baseline modulation of the user's IBI value over a period of time. The respiration rate may be calculated in breaths per minute or as another respiration rate (e.g., breaths per 30 seconds). The processing module 230-a may store the user's respiration values ​​over time in memory 215.

[0066] The ring 104 may include one or more motion sensors 245, such as one or more accelerometers (e.g., 6D accelerometers) and / or one or more gyroscopes (gyros). The motion sensors 245 may generate motion signals indicative of sensor movement. For example, the ring 104 may include one or more accelerometers that generate acceleration signals indicative of acceleration of the accelerometer. As another example, the ring 104 may include one or more gyro sensors that generate gyro signals indicative of angular motion (e.g., angular velocity) and / or changes in orientation. The motion sensors 245 may be included in one or more sensor packages. An exemplary accelerometer / gyro sensor is a Bosch BM1160 inertial microelectromechanical system (MEMS) sensor that can measure angular velocity and acceleration in three perpendicular axes.

[0067] The processing module 230-a may sample the motion signals at a sampling rate (e.g., 50 Hz) and determine the movement of the ring 104 based on the sampled motion signals. For example, the processing module 230-a may sample the acceleration signals to determine the acceleration of the ring 104. As another example, the processing module 230-a may sample the gyro signals to determine the angular motion. In some implementations, the processing module 230-a may store the motion data in the memory 215. The motion data may include sampled motion data and motion data (e.g., acceleration values ​​and angle values) calculated based on the sampled motion signals.

[0068] The ring 104 may store various data described herein. For example, the ring 104 may store temperature data, such as raw sampled temperature data and calculated temperature data (e.g., average temperature). As another example, the ring 104 may store PPG signal data, such as pulse waveforms and data calculated based on the pulse waveforms (e.g., heart rate values, IBI values, HRV values, and respiration values). The ring 104 may also store motion data, such as sampled motion data indicative of linear and angular motion.

[0069] The ring 104 or other computing device may calculate and store additional values ​​based on the sampled / calculated physiological data. For example, the processing module 230 may calculate and store various metrics, such as sleep metrics (e.g., sleep scores), activity metrics, and readiness metrics. In some implementations, the additional values / metrics may be referred to as “derived values.” The ring 104, or other computing / wearable device, may calculate various values / metrics related to movement. Exemplary derived values ​​of motion data may include, but are not limited to, a movement count value, a regularity value, an intensity value, a metabolic equivalence of task values ​​(METs), and an orientation value. The movement count, regularity value, intensity value, and METs may indicate the amount of user movement (e.g., speed / acceleration) over time. The orientation value may indicate how the ring 104 is oriented on the user's finger and whether the ring 104 is worn on the left or right hand.

[0070] In some implementations, the motion count and regularity value may be determined by counting the number of acceleration peaks within one or more time periods (e.g., one or more time periods of 30 seconds to 1 minute). The intensity value may indicate the number of motions and the associated intensity of the motions (e.g., acceleration values). The intensity values ​​may be classified as low, medium, and high depending on the associated threshold acceleration value. The MET may be determined based on the intensity of the motions, the regularity / irregularity of the motions, and the number of motions associated with different intensities during a period (e.g., 30 seconds).

[0071] In some implementations, the processing module 230-a may compress data stored in the memory 215. For example, the processing module 230-a may perform calculations based on the sampled data and then delete the sampled data. As another example, the processing module 230-a may average data over a longer period to reduce the number of values ​​stored. In a specific example, if a user's average temperature for one minute is stored in the memory 215, the processing module 230-a may calculate the average temperature over a five-minute period for storage and then erase the one-minute average temperature data thereafter. The processing module 230-a may compress data based on various factors, such as the total amount of used / available memory 215 and / or the time elapsed since the ring 104 last transmitted data to the user device 106.

[0072] The user's physiological parameters may be measured by sensors included on the ring 104, although other devices may measure the user's physiological parameters. For example, the user's temperature may be measured by temperature sensor 240 included on the ring 104, although other devices may measure the user's temperature. In some examples, other wearable devices (e.g., wrist devices) may include sensors that measure the user's physiological parameters. Additionally, medical devices, such as external medical devices (e.g., wearable medical devices) and / or implantable medical devices, may measure the user's physiological parameters. One or more sensors on any type of computing device may be used to implement the techniques described herein.

[0073] The physiological measurements may be taken continuously throughout the day and / or night. In some implementations, the physiological measurements may be taken during portions of the day and / or portions of the night. In some implementations, the physiological measurements may be taken in response to determining that the user is in a particular state, such as an active state, a resting state, and / or a sleeping state. For example, the ring 104 may take physiological measurements in a resting / sleeping state to obtain a cleaner physiological signal. In one example, the ring 104 or other device / system may detect when the user is resting and / or sleeping and obtain physiological parameters (e.g., temperature) for the detected state. The device / system may use the resting / sleeping physiological data and / or other data when the user is in other states to implement the techniques of this disclosure.

[0074] In some implementations, the ring 104 may be configured to collect, store, and / or process data, as previously described herein, and may forward any of the data described herein to the user device 106 for storage and / or processing. In some aspects, the user device 106 includes a wearable application 250, an operating system (OS) 285, a web browser application (e.g., web browser 280), one or more additional applications, and a GUI 275. The user device 106 may further include other modules and components, including sensors, audio devices, haptic feedback devices, etc. The wearable application 250 may include an example of an application (e.g., an “app”) that may be installed on the user device 106. The wearable application 250 may be configured to acquire data from the ring 104, store the acquired data, and process the acquired data, as described herein. For example, the wearable application 250 may include a user interface (UI) module 255, an acquisition module 260, a processing module 230-b, a communication module 220-b, and a storage module (e.g., a database 265) configured to store application data.

[0075] The various data processing operations described herein may be performed by the ring 104, the user devices 106, the server 110, or any combination thereof. For example, in some cases, data collected by the ring 104 may be pre-processed and transmitted to the user devices 106. In this example, the user devices 106 may perform some data processing operations on the received data, transmit the data to the server 110 for data processing, or both. For example, in some cases, the user devices 106 may perform processing operations that require relatively low processing power and / or operations that require relatively low latency, while the user devices 106 may transmit data to the server 110 for processing operations that require relatively high processing power and / or operations that can tolerate relatively high latency.

[0076] In some embodiments, the ring 104, user device 106, and server 110 of system 200 may be configured to evaluate a user's sleep patterns. In particular, each component of system 200 may be used to collect data from the user via the ring 104 and generate one or more scores (e.g., a sleep score, a readiness score) for the user based on the collected data. For example, as described previously herein, the ring 104 of system 200 may be worn by the user to collect data from the user, including temperature, heart rate, HRV, etc. The data collected by the ring 104 may be used to determine when the user is asleep to evaluate the user's sleep for a given "sleep day." In some embodiments, a score may be calculated for the user for each sleep day, such that a first sleep day is associated with a first set of scores, a second sleep day is associated with a second set of scores, and so on. A score may be calculated for each sleep day based on the data collected by the ring 104 during each respective sleep day. The scores may include, but are not limited to, a sleep score, a readiness score, etc.

[0077] In some cases, "sleep days" may correspond to traditional calendar days, such that a given sleep day is from midnight to midnight on the respective calendar day. In other cases, sleep days may be offset relative to the calendar day. For example, a sleep day may run from 6:00 PM (18:00) on a calendar day to 6:00 PM (18:00) on the next calendar day. In this example, 6:00 PM may serve as a "cutoff time," such that data collected from the user before 6:00 PM is counted toward the current sleep day, and data collected from the user after 6:00 PM is counted toward the next sleep day. Due to the fact that most individuals sleep most at night, offsetting sleep days relative to the calendar day allows system 200 to evaluate the user's sleep patterns in a manner consistent with the user's sleep schedule. In some cases, users may be able to selectively adjust the timing of sleep days relative to the calendar day (e.g., via a GUI), thereby aligning sleep days with the duration each user typically sleeps.

[0078] In some implementations, each overall score (e.g., sleep score, readiness score) for a user for each respective day may be determined / calculated based on one or more “contributors,” “factors,” or “contributing factors.” For example, a user's overall sleep score may be calculated based on a set of contributing factors including total sleep, efficiency, restfulness, REM sleep, deep sleep, latency, timing, or any combination thereof. A sleep score may include any number of contributing factors. A “total sleep” contributing factor may refer to the sum of all sleep periods on a sleep day. An “efficiency” contributing factor may reflect the proportion of time asleep compared to awake time while in bed and may be calculated using an efficiency average of long sleep periods (e.g., main sleep periods) on a sleep day, weighted by the duration of each sleep period. A “restfulness” contributing factor may indicate how restful a user's sleep is and may be calculated using an average of all sleep periods on a sleep day, weighted by the duration of each period. The restfulness contributors may be based on "wake count" (e.g., the sum of all wake-ups (when the user wakes up) detected during different sleep periods), excessive movement, and "got up count" (e.g., the sum of all get-ups (when the user gets out of bed) detected during different sleep periods).

[0079] The "REM sleep" contribution factor may refer to the sum of REM sleep duration across all sleep periods on a sleep day, including REM sleep. Similarly, the "deep sleep" contribution factor may refer to the sum of deep sleep duration across all sleep periods on a sleep day, including deep sleep. The "latency" contribution factor may represent the time it takes a user to fall asleep (e.g., average, median, longest) and may be calculated using an average of long sleep periods across a sleep day, weighted by the duration of each period and the number of such periods (e.g., the integration of a given sleep stage or stages may be its own contribution factor or may weight other contribution factors). Finally, the "timing" contribution factor may refer to the relative timing of sleep periods within a sleep day and / or calendar day, and may be calculated using an average of all sleep periods on a sleep day, weighted by the duration of each period.

[0080] As another example, a user's overall readiness score may be calculated based on a set of contributing factors, including sleep, sleep balance, heart rate, HRV balance, recovery index, temperature, activity, activity balance, or any combination thereof. A readiness score may include any number of contributing factors. A "sleep" contributing factor may refer to the combined sleep score of all sleep periods within a sleep day. A "sleep balance" contributing factor may refer to the cumulative duration of all sleep periods within a sleep day. In particular, sleep balance may indicate to a user whether the sleep a user has received over a period of time (e.g., the past two weeks) is balanced with the user's needs. Typically, adults require 7 to 9 hours of sleep per night to be healthy, alert, and perform at their best mentally and physically. However, occasional poor sleep days are normal, and therefore, the sleep balance contributing factor considers long-term sleep patterns to determine whether each user's sleep needs are being met. The "resting heart rate" contributor may indicate the lowest heart rate from the longest sleep period (eg, the main sleep period) of the sleep day and / or the lowest heart rate from a nap occurring after the main sleep period.

[0081] Continuing with reference to readiness score "contributors" (e.g., factors, contributors), the "HRV balance" contributor may indicate the highest average HRV from the primary sleep period and the sleep period that occurs after the primary sleep period. The HRV balance contributor may help a user track their recovery status by comparing their HRV trend over a first period (e.g., two weeks) with their average HRV over a second, longer period (e.g., three months). The "recovery index" contributor may be calculated based on the longest sleep period. The recovery index measures the time it takes for a user's resting heart rate to stabilize during the night. A sign of very good recovery is when a user's resting heart rate stabilizes during the first half of the night, at least six hours before the user wakes up, leaving the body time to recover for the next day. The "body temperature" contributor may be calculated based on the longest sleep period (e.g., primary sleep period) or based on the sleep period that occurs after the longest sleep period if the user's highest body temperature during that sleep period is at least 0.5°C higher than the highest body temperature during the longest sleep period. In some embodiments, the ring may measure the user's temperature while the user is asleep, and the system 200 may display the user's average temperature relative to the user's baseline temperature. If the user's temperature is outside of the normal range (e.g., significantly higher or lower than 0.0), the temperature contributor may be highlighted (e.g., go to a "Pay attention" state) or otherwise generate an alert to the user.

[0082] In some aspects, the system 200 may support techniques for generating group-based health and wellness scores and insights. For example, the user device 106 may receive user-specific information (e.g., user-specific physiological data, user-specific scores) collected by the wearable device 104 for a group of users who are allowed intra-group information sharing (e.g., two-way data sharing). The user device 106 may use the user-specific information of the users in the group to generate group-specific scores or insights, which may be used to generate group-specific recommendations.

[0083] Additionally or alternatively, the user device 106 may display user-specific information (or a subset of user-specific information) on an individual basis so that members of the group can monitor each other's health and wellness and take action accordingly (e.g., provide responses via electronic means and update health and wellness goals).

[0084] 3 illustrates an example of a system 300 that supports techniques for wearable-based two-way sharing of data according to aspects of the present disclosure. System 300 may implement or be implemented by aspects of system 100, system 200, or both. 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 an example of wearable device 104 as described with reference to FIGS. 1 and 2, and user device 306 may be an example of user device 106 as described with reference to FIGS. 1 and 2.

[0085] System 300 may implement techniques described herein for two-way data sharing used to generate group-specific health and wellness information based on user-specific data collected by wearable devices 304. For example, system 300 may generate group-specific health and wellness information for a group of users 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, within a threshold distance of each other) or may be geographically dispersed (e.g., in different neighborhoods, different cities, different countries).

[0086] User-specific data used to generate group-specific health and wellness information may be collected by the wearable devices 304 of each of the users 302 in the group. For example, wearable device 304-a may collect physiological data about user 302-a and communicate the physiological data to user device 306-a. Similarly, wearable devices 304-b and 304-c may collect physiological data about users 302-b and 302-c and communicate the physiological data to their respective user devices 306-b and 306-c. User-specific data may be exchanged by wireless devices (e.g., wearable devices 304, user devices 306) in the group so that group-specific health and wellness information may be generated. In other words, physiological data for each user 302 in the group may be shared (e.g., two-way sharing) with other users 302 in the group. User-specific data exchanged between user devices 306 may be updated over time (e.g., shared repeatedly) to reflect trends and / or the most recent user-specific data for members of the group.

[0087] In some examples, a user device 306 (e.g., user device 306-c) may perform a handshake procedure with other user devices 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 device 306 associated with a user of a group, user device 306-c may transmit a request (e.g., via wireless electronic communication) to establish a wireless electronic communication link (e.g., a Bluetooth link) with that user device 306. Upon receiving a message following the request, user device 306-c may exchange electronic wireless communication signaling with user device 306 to establish the wireless electronic communication link with user device 306. Once the wireless electronic communication link with user device 306 is established, user device 306-c may receive instructions (from an application associated with user device 306) including permission to send and receive (e.g., using the wireless electronic communication link) physiological data information collected by the associated wearable device 304. In some cases, one or more servers 310 may be configured to facilitate the exchange of signaling for a "handshake procedure" used to establish a group of trusted users, thereby facilitating the two-way exchange of physiological data.

[0088] A user 302 may join a group by authorizing their user device 306 to exchange user-specific information with other user devices 306 in the group. For example, upon receiving authorization from user 302-c, an application on user device 306-c may exchange user-specific information with other applications on user devices 306 in the group. The user-specific information communicated 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). The user devices 306 may communicate directly (e.g., via peer-to-peer wireless communication) or indirectly (e.g., via a network 308).

[0089] In some cases, a user 302 may manually create a group of users with whom the user 302 wishes to share data by sending a request to other users 302. Additionally or alternatively, the system 300 may recommend that users form a group or circle for sharing data with each other based on the geographic locations of each user 302, the physiological characteristics of the users 302, etc. For example, the system 300 may determine spatial relationships between the users 302 (e.g., determine that the users 302 are located near each other, such as in the same apartment complex) and, based on the determined spatial relationships, send a prompt / recommendation for the users 302 to form a group for two-way sharing. As another example, the system 300 may identify users 302 with similar physiological characteristics (e.g., similar circadian rhythms, similar chronotypes, etc.) and send a prompt / recommendation for the users 302 to form a group for two-way sharing.

[0090] Upon forming a group (e.g., a circle, a trusted circle, etc.), the system 300 may aggregate physiological data from each respective user 302 (e.g., via the wearable device 304) and distribute the collected physiological data to other users 302 in the group. In this regard, each user 302 may share their 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, the system 300 (e.g., server 310, user device 306-c) may receive user-specific information of users 302 in the group. For example, user device 306-c may receive user-specific information of user 302-a from an application on user device 306-a and user-specific information of user 302-b from an application on user device 306-b. In some aspects, the physiological data for each respective user 302 in the group may be aggregated at the respective user device 306, may be aggregated at the server 310 and then distributed to the users 302 in the group, or both.

[0091] Physiological data may be collected from users 302 in a group at predetermined times (e.g., 9:00 AM and 9:00 PM), based on a particular event (e.g., after each user wakes up, after completing a workout, etc.), based on the physiological data meeting some threshold (e.g., based on identifying some threshold change in the user's physiological data), or any combination thereof. In this regard, physiological data of users 302 in a group may be "pushed" and / or "pulled" to aggregate data for the group.

[0092] The system 300 (e.g., server 310, user device 306-c) may generate one or more scores or insights for the group using user-specific information of the users in the group. For example, the system 300 may generate a composite readiness score or composite sleep score for the group that is a function of the group's user-specific information (e.g., a composite sleep score for the group may be calculated as the mean or median sleep score for each respective user 302 in the group). Additionally or alternatively, the system 300 may generate an activity score for the group that indicates the group's collective (e.g., average) activity level. Additionally or alternatively, the system 300 may generate an anxiety score for the group that indicates the group's collective anxiety level. In some examples, the system 300 may use a machine learning (ML) model to generate the composite score(s). The system 300 (e.g., server 310, user device 306-c) may transmit (e.g., via wireless electronic communication) control signaling (e.g., to a user device 306 associated with the group) that causes the user device 306 associated with the group to display an indication of the group score or insight.

[0093] In some aspects, the composite score calculated for the group may be used to convey information about the overall health, well-being, and / or stress of the entire group. In some cases, the scores calculated for individual users 302 and / or the composite score calculated for the group may be used as a "status" on, for example, a social media application, a messaging application (e.g., a workplace messaging application).

[0094] In some aspects, the system 300 may enable users 302 in a group to share messages with other users in the group, to “react” to the scores and / or physiological data of other users 302 in the group (e.g., responding with custom responses, emojis, or other predefined responses), etc. In this regard, the techniques described herein may enable users 302 to proactively respond and engage other users 302 in a group to encourage healthy habits and to encourage each other to reach their fitness goals.

[0095] In addition to (or instead of) generating a group-specific score, the system 300 (e.g., the server 310, the user device 306-c) may determine insights about the group. For example, the system 300 may determine that the group has an unusual score (e.g., a score outside a standard deviation range) compared to past scores for the group. In some examples, the insights may be based on activities or events shared among users of the group. For example, the user device 306-c may determine that the group is not sufficiently rested to perform an activity scheduled for the group (e.g., a strength training session). A "score" may include a quantitative value representing a characteristic of the group, and an "insight" may be an observation or assessment that conveys qualitative or descriptive information about the characteristic of the group. In some examples, the system 300 may use an ML model to determine the insights for the group.

[0096] In some examples, the system 300 (e.g., the server 310, the user devices 306-c) may determine group-specific recommendations based on the group-specific health and wellness information (e.g., one or more group-specific scores, one or more group-specific insights). For example, the system 300 may suggest an activity (e.g., take a walk, take a nap, have a coffee) for the users of the group, suggest an activity change (e.g., shorten a training session, reduce sports practice), recommend a schedule change (e.g., postpone a meeting), etc. Making a recommendation may include the system 300 (e.g., the server 310, the user devices 306-c) sending (e.g., via wireless electronic communication) control signaling (e.g., to the user devices associated with the group) that causes the user devices associated with the group to display indications of the recommendation. In some examples, the system 300 may use an ML model to determine the group-specific recommendations.

[0097] In some cases, the system 300 may make recommendations or insights to a group of users based on the calendar information of each respective user 302. For example, the system 300 may aggregate calendar information for each user 302, e.g., from a calendar application executable on each user device 306. In this example, the system 300 may recognize that users in the group are scheduled to meet with each other at 9:00 AM based on the retrieved calendar information, but may also recognize that the group did not sleep well last night (e.g., the group exhibits a low sleep score and / or a low composite sleep score). Thus, the system 300 may recognize that each user in the group has a time slot available from 1:00 PM to 1:30 PM (e.g., based on the retrieved calendar information) and therefore may provide a recommendation for the group to delay the meeting to 9:00 AM to 1:00 PM based on the aggregated physiological information and calendar data.

[0098] In some examples, the system 300 may weight (e.g., scale) the user-specific data of some users 302 differently from other users 302. For example, the system 300 may weight the user-specific data of a user 302 based on a priority level associated with (e.g., assigned to) the user. Additionally or alternatively, the system 300 may selectively exclude the user-specific data of one or more users 302 (e.g., identified outliers, users who are absent or indicated as ill) from the data used to generate the group-specific health and wellness information. Thus, user-specific data for some or all of the users 302 in a group may contribute to the group-specific health and wellness information.

[0099] In some examples, the weight applied to a user's user-specific data may be based on how the user-specific data changes relative to past (e.g., baseline) user-specific data for that user, how the user-specific data changes relative to a statistical metric (e.g., average) of the user-specific data for the rest of the group, or both. In some examples, the weight applied to the user-specific data may be based on one or more inputs received from the user. For example, a user may request that the user-specific information of one or more users be applied with a relatively greater or lesser weight than other users in the group. In some cases, the weight applied to the user-specific data may be statically selected by system 300. In other cases, the weight applied to the physiological data for each respective user may be dynamically determined. In such cases, the weight for each respective user may be determined based on a comparison of each respective user's physiological data to its own baseline, the data of the rest of the users in the group, or 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), and 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, the second user's data may be weighted more heavily compared to the first user's data when calculating a composite score for that given day group.

[0100] In some examples, the system 300 may suggest a group for the user 302-c to join. For example, the system 300 (e.g., the server 310, the user device 306-c) may suggest a group for the user 302-c to join based on a spatial relationship (e.g., proximity) between the user 302-c and the other users 302 in the group, based on one or more physiological characteristics (e.g., circadian rhythm, chronotype) shared by the user 302-c and the other users 302 in the group, based on demographic characteristics (e.g., same gender, similar age, etc.) that the user 302-c shares with the other users 302 in the group, or based on other commonalities between the user 302-c and the other users in the group (e.g., shared fitness goals, similar activity patterns, similar sleep patterns).

[0101] The user-specific information shared by the user device 306 may be selected by the user 302 of the user device 306. For example, the user 302-c may select the type of data to be shared with other user devices in a group. Illustratively, the user 302-c may choose to share sleep data with the group but not fertility data. If the user 302-c is part of two different groups, the user 302-c may choose to share different types of data with the two groups. If the user 302-c selects to share a first type of data with the first group (but not with the second group) and to share a second type of data with the second group (but not with the first group), the user device 306-c may A) determine that the first type of data is allowed to be shared with the first group but not with the second group, and B) transmit the first type of data to user devices associated with the first group (but not the second group). Similarly, the user device 306-c may A) determine that a second type of data is allowed to be shared with the second group but not with the first group, and B) transmit the second type of data to the user device associated with the second group (but not to the user device associated with the first group). In some examples, the user device 306-c may suggest a type(s) of data for the user 302-c to share with the group. Additionally or alternatively, the user 302-c may choose to share data collected during some time periods (e.g., data collected during weekdays) but not data collected during other time periods (e.g., data collected during weekends). In some examples, the user 302-c may instruct the user device 306-c to anonymize data shared with the group. In some examples, the user 302-c may indicate specific users whose data should be anonymized.

[0102] In some examples, the user device 306-c waits for authentication of the user 302-c before exchanging (e.g., sending or receiving) user-specific data with other user devices 306. For example, the user device 306-c may wait for the wearable device 304-c to authenticate the user 302-c before exchanging user-specific data with other user devices 306. Furthermore, in some implementations, other users 302 in the group may be required to approve or authorize the new user 302 before the user 302 is added to the group to conduct two-way sharing with the new user 302.

[0103] In some examples, the system 300 may identify one or more users 302 who are outliers in that they have user-specific data that deviates significantly (e.g., deviates by more than a threshold amount) from the user-specific data of other users 302 in the group. In other words, the system 300 may flag users 302 who exhibit physiological data or scores that deviate from the mean / median physiological data / score for the entire group. For example, the system 300 (e.g., the server 310, the user device 306-c) may identify user 302-a as an outlier based on the user 302-a having a sleep score that is x% lower than the next lowest sleep score or x% lower than the mean sleep score for the group. By doing so, the system 300 may actively reach out to or encourage users 302 in the group who may be struggling mentally, physically, and / or emotionally.

[0104] The system 300 may flag users 302 that are outliers and may generate user-specific recommendations for the outliers. In some examples, the system 300 may generate multiple group-specific scores or insights that vary based on the inclusion and exclusion of user-specific data for the outliers. For example, a user device 306-c may generate a "true" group-specific score or insight that reflects user-specific data from all users 302 in the group and an "adjusted" group-specific score that reflects user-specific data from a subset of users 302 in the group that excludes outliers (and may be a more accurate representation of the group's overall well-being).

[0105] In some examples, the system 300 may display user-specific data for one or more users next to group-specific data for comparison. For example, the user device 306-c may display user-specific data for the user 302-c (or one or more other users) next to group-specific data. Additionally or alternatively, the system 300 may rank and display the user-specific data for one or more users in descending or ascending order. Additionally or alternatively, the system 300 may display an indication of how the user of the user device 306-c compares to the group, how the user compares to the top or bottom z% of the group, or any combination thereof. In some examples, the system 300 may make one or more recommendations to the user of the user device 306-c based on how the user compares to the group or other members of the group. In some examples, the user of the user device 306-c may select particular individuals whose user-specific data the user wants to view. For example, the user may select individuals by name, relationship, or ranking (e.g., the user device 306-c may show user data for the top z% of the group).

[0106] In some examples, the system 300 (e.g., via the user device 306-c) may control one or more external devices in the vicinity of the group (e.g., if the group is co-located) based on group-specific health and wellness information. For example, the user device 306-c may modify the environment by changing the lumens or color of light output by one or more lights near the user based on a group sleep score for the user. As another example, the user device 306-c may adjust the temperature setting of a thermostat in a room where the group is gathered based on a group anxiety score for the user. As another example, the user device 306-c may adjust the volume of a speaker near the group based on a group sleep score for the user. As another example, the user device 306-c may adjust the position of smart window shades near the group based on a group readiness score for the user.

[0107] The user device 306-c may autonomously (e.g., without user input) change settings or operating parameters of nearby electronic devices. Alternatively, the user device 306-c may propose changes (e.g., by displaying an indication of the proposed changes) and wait to implement the changes until the user 302-c (or another user in the group) approves the changes (e.g., via user input). To enable wireless electronic communication with the electronic device for the purpose of changing the settings of the electronic device, the user device 306-c may perform a wireless synchronization procedure with the electronic device and then, once synchronized, send one or more instructions to the electronic device.

[0108] Thus, system 300 may 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, various operations described herein may be performed by server 310. Additionally, operations described herein may be performed by a single device of system 300 or may be distributed among (e.g., performed by) various devices of system 300.

[0109] 4 illustrates an example of a process flow 400 supporting techniques for wearable-based two-way sharing of data according to aspects of the present disclosure. Process flow 400 may be implemented by a device in a system, such as system 300 as described with reference to FIG. 3. The device may be a user device 306 or a server 310, among other options. According to the techniques described herein, the device may generate group-specific health and wellness information based on user-specific data collected by wearable devices associated with a group of users.

[0110] At 405, the device may identify and recommend a group for the user to join. For example, the device may identify a group of users for the user to join based on spatial relationships between the users, based on one or more shared (e.g., common) characteristics or similarities between the user and other users in the group, or both, and cause a GUI (e.g., the GUI of the user's user device) to display an indication of the group to the user. For example, the device may obtain baseline physiological data associated with some or all of the users in the group and identify one or more similarities between the baseline physiological data associated with each user. Based on identifying one or more similarities, the device may send a prompt for sharing physiological data among the group of users. Thus, upon identifying a group for the user to join, the device may send a prompt for sharing user-specific data among users in the group. Alternatively, the device may send or receive an invitation to join the group. In such an example, members of the group may be selected by users of the group.

[0111] At 410, the device may receive an indication of the group the user has selected to join. If the device is a user device, the device may receive the indication via user input. If the device is a server, the device may receive the indication from the user device.

[0112] At 415, the device may communicate with user devices of users in the group to establish permissions for data exchange. As part of the communication, the device may receive instructions (e.g., from applications of user devices associated with users in the group) that allow the exchange (e.g., sending and receiving) of user-specific data (e.g., physiological data, user-specific scores) between the applications. In some examples, the instructions received by the device may be based on (e.g., responding to) sending a prompt to share the user-specific data at 405.

[0113] At 420, the device may receive an indication of data sharing constraints or parameters for sharing user-specific data with the application. For example, the device may receive an indication of the type of data that is allowed to be exchanged. As another example, the device may receive an indication of the period of time that the exchange of collected data is allowed. If the device is a user device, the device may receive the indication at 420 via user input. If the device is a server, the device may receive the indication at 420 from the user device.

[0114] At 425, the device may obtain (e.g., wirelessly receive) user-specific data about the user collected by the user's wearable device. The device may obtain the user-specific data directly from the wearable device (e.g., via Bluetooth) or indirectly from the user device via the network 308. At 430, the device may provide authorized user-specific data to other user devices in the group based on the user selecting a group.

[0115] At 435, the device may obtain (e.g., wirelessly receive) user-specific data from one or more applications in the group. The device may obtain the user-specific data directly from user devices in the group (e.g., via Bluetooth) or over the network 308. At 440, the device may generate group-specific scores or insights based on the user-specific data for users in the group. For example, the device may calculate an average score for the group based on (e.g., as a function of) the individual scores of the users in the group. At 445, the device may determine recommendations for the group based on the group-specific scores and / or insights.

[0116] At 450, the device may cause one or more GUIs to display group-specific scores, group-specific insights, group-specific recommendations, or any combination thereof. The GUI(s) may include a GUI for the device, a GUI(s) for user devices in the group, or both. In some examples, the group-specific recommendations may be based on calendar data associated with users of the group.

[0117] At 455, the device may identify one or more users who are outliers of the group with respect to user-specific data. For example, the device may identify that physiological data associated with user y deviates from physiological data associated with the remaining users in the group by a threshold metric. At 460, the device may cause one or more GUIs to display instructions for the outlier user (e.g., user y), user-specific data for the outlier user, one or more recommendations for the outlier user, or any combination thereof. The GUI(s) may include a GUI for the device, a GUI(s) for user devices in the group, or both.

[0118] 5 shows a block diagram 500 of a device 505 supporting techniques for wearable-based two-way sharing of data according to aspects of the present disclosure. The device 505 may include an input module 510, an output module 515, and a wearable application 520. The device 505 may also include a processor. Each of these components may communicate with each other (e.g., via one or more buses).

[0119] The input module 510 may provide a means for receiving information such as packets associated with various information channels (e.g., a control channel, a data channel, an information channel related to disease detection techniques), user data, control information, or any combination thereof. The information may be passed to other components of the device 505. The input module 510 may utilize a single antenna or a set of multiple antennas.

[0120] The output module 515 may provide a means for transmitting signals generated by other components of the device 505. For example, the output module 515 may transmit information such as packets associated with various information channels (e.g., a control channel, a data channel, an information channel related to disease detection techniques), user data, control information, or any combination thereof. In some examples, the output module 515 may be co-located with the input module 510 in a transceiver module. The output module 515 may utilize a single antenna or a set of multiple antennas.

[0121] For example, the wearable application 520 may include a communications component 525, a processor 530, a graphics component 535, or any combination thereof. In some examples, the wearable application 520, or its various components, may be configured to perform various operations (e.g., receiving, monitoring, transmitting) using or otherwise cooperating with the input module 510, the output module 515, or both. For example, the wearable application 520 may receive information from the input module 510, transmit information to the output module 515, or be integrated in combination with the input module 510, the output module 515, or both to receive information, transmit information, or perform various other operations as described herein.

[0122] The wearable application 520 may support sharing physiological data among a group of users, according to examples as disclosed herein. The communication component 525 may be configured as or support a means for receiving instructions from one or more applications associated with the group of users, the instructions including permission to send and receive physiological data between the one or more applications, the physiological data being based at least in part on physiological measurements collected from each user of the group of users via the wearable device associated with the one or more applications. The communication component 525 may be configured as or support a means for acquiring physiological data from the one or more applications. The processor 530 may be configured as or support a means for generating a score indicative of a physiological metric representative of the group of users, based at least in part on the physiological data acquired from the one or more applications. The graphics component 535 may be configured as or support a means for displaying the score in at least one GUI of the user device associated with the one or more applications.

[0123] 6 shows a block diagram 600 of a wearable application 620 supporting techniques for wearable-based bidirectional sharing of data according to aspects of the present disclosure. The wearable application 620 may be an example of aspects of a wearable application or a wearable application 520, or both, as described herein. The wearable application 620, or various components thereof, may be an example of a means for performing various aspects of techniques for wearable-based bidirectional sharing of data as described herein. For example, the wearable application 620 may include a communications component 625, a processor 630, a graphics component 635, or any combination thereof. Each of these components may communicate directly or indirectly with one another (e.g., via one or more buses).

[0124] The wearable application 620 may support sharing physiological data among a group of users, according to examples as disclosed herein. The communication component 625 may be configured with or support a means for receiving instructions from one or more applications associated with the group of users, the instructions including permission to send and receive physiological data between the one or more applications, the physiological data being based at least in part on physiological measurements collected from each user of the group of users via the wearable device associated with the one or more applications. In some examples, the communication component 625 may be configured with or support a means for acquiring physiological data from one or more applications. The processor 630 may be configured with or support a means for generating a score indicative of a physiological metric representative of the group of users, based at least in part on the physiological data acquired from the one or more applications. The graphics component 635 may be configured with or support a means for displaying the score in at least one GUI of the user device associated with the one or more applications.

[0125] In some examples, the physiological data includes first physiological data associated with a first user of the group of users and additional physiological data associated with the remaining users of the group of users excluding the first user, and the processor 630 may be configured with or support a means 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 metric. In some examples, the physiological data includes the first physiological data associated with the first user of the group of users and the additional physiological data associated with the remaining users of the group of users excluding the first user, and the graphics component 635 may be configured with or support a means for causing at least one GUI of the device to display an indication of the first user based at least in part on the identifying.

[0126] In some examples, processor 630 may be configured with or support a means for identifying a spatial relationship between a group of users. In some examples, communication component 625 may be configured with or support a means for sending a prompt to share physiological data between a group of users based at least in part on identifying the spatial relationship, where receiving the instruction is based at least in part on sending the prompt.

[0127] In some examples, the communication component 625 may be configured with or support a means for obtaining baseline physiological data associated with multiple users, including a group of users. In some examples, the processor 630 may be configured with or support a means for identifying one or more similarities between baseline physiological data associated with each user from the group of users. In some examples, the communication component 625 may be configured with or support a means for sending a prompt to share physiological data among the group of users based at least in part on identifying the one or more similarities, wherein receiving the instruction is based at least in part on sending the prompt.

[0128] In some examples, the processor 630 may be configured with or support a means for identifying calendar data associated with each user of a group of users. In some examples, the graphics component 635 may be configured with or support a means for causing at least one GUI of a user device associated with one or more applications to display recommendations based at least in part on the scores and the calendar data.

[0129] In some examples, the communications component 625 may be configured as or support a means for receiving, via one or more applications associated with a first user of a group of users, an indication of one or more permitted physiological parameters, an indication of one or more permitted time periods, or both, wherein obtaining physiological data from the application associated with the user includes obtaining physiological data associated with the one or more permitted physiological parameters, obtaining physiological data within the one or more permitted time periods, or both.

[0130] In some examples, at least one wearable device associated with each user of the group of users includes a wearable ring device.

[0131] FIG. 7 shows a diagram of a system 700 including a device 705 supporting techniques for wearable-based two-way sharing of data according to aspects of the present disclosure. The device 705 may be or include an example of components of device 505 as described herein. The device 705 may include an example of user device 106, as previously described herein. The device 705 may include components for two-way communication, including components for sending and receiving communications with the wearable device 104 and server 110, such as a wearable application 720, a communication module 710, an antenna 715, a user interface component 725, a database (application data) 730, a memory 735, and a processor 740. These components may be in electronic communication or otherwise coupled (e.g., operatively, communicatively, functionally, electronically, electrically) via one or more buses (e.g., bus 745).

[0132] The communications module 710 may manage input and output signals for the device 705 via the antenna 715. The communications module 710 may include an example of the communications module 220-b of the user device 106 shown and described in FIG. 2. In this regard, the communications module 710 may manage communications with the ring 104 and the server 110, as shown in FIG. 2. The communications module 710 may also manage peripherals not integrated into the device 705. In some cases, the communications module 710 may represent a physical connection or port to an external peripheral. In some cases, the communications module 710 may utilize an operating system such as iOS®, ANDROID®, MS-DOS®, MS-WINDOWS®, OS / 2®, UNIX®, LINUX®, or another known operating system. In other cases, the communications module 710 may represent or interact with a wearable device (e.g., the ring 104), a modem, a keyboard, a mouse, a touchscreen, or similar devices. In some cases, the communications module 710 may be implemented as part of the processor 740. In some examples, a user may interact with the device 705 via the communications module 710, a user interface component 725, or via a hardware component controlled by the communications module 710.

[0133] In some cases, the device 705 may include a single antenna 715. However, in some other cases, the device 705 may have two or more antennas 715, which may enable it to simultaneously transmit or receive multiple wireless transmissions. The communications module 710 may communicate bidirectionally via one or more antennas 715, wired links, or wireless links, as described herein. For example, the communications module 710 may represent a wireless transceiver and may communicate bidirectionally with another wireless transceiver. The communications module 710 may also include a modem for modulating packets, providing the modulated packets to one or more antennas 715 for transmission, and demodulating packets received from the one or more antennas 715.

[0134] The user interface component 725 may manage the storage and processing of data in the database 730. In some cases, a user may interact with the user interface component 725. In other cases, the user interface component 725 may operate automatically without user interaction. The database 730 may be an example of a single database, a distributed database, multiple distributed databases, a data store, a data lake, or an emergency backup database.

[0135] Memory 735 may include RAM and ROM. Memory 735 may store computer-readable, computer-executable software including instructions that, when executed, cause processor 740 to perform various functions described herein. In some cases, memory 735 may include a BIOS, which may control basic hardware or software operations such as interaction with peripheral components or devices, among other things.

[0136] The processor 740 may include an intelligent hardware device (e.g., a general-purpose processor, a DSP, a CPU, a microcontroller, an ASIC, an FPGA, a programmable logic device, discrete gate or transistor logic components, discrete hardware components, or any combination thereof). In some cases, the processor 740 may be configured to operate a memory array using a memory controller. In other cases, the memory controller may be integrated into the processor 740. The processor 740 may be configured to execute computer-readable instructions stored in the memory 735 to perform various functions (e.g., functions or tasks supporting the methods and systems for sleep stage classification algorithms).

[0137] Wearable application 720 may support sharing physiological data among a group of users, according to examples as disclosed herein. For example, wearable application 720 may be configured with or support receiving instructions from one or more applications associated with the group of users, the instructions including permission to send and receive physiological data between the one or more applications, the physiological data being based at least in part on physiological measurements collected from each user of the group of users via a wearable device associated with the one or more applications. Wearable application 720 may be configured with or support obtaining physiological data from one or more applications. Wearable application 720 may be configured with or support generating a score indicative of a physiological metric representative of the group of users, based at least in part on physiological data obtained from the one or more applications. Wearable application 720 may be configured with or support displaying the score in at least one GUI of a user device associated with the one or more applications.

[0138] By including or configuring wearable applications 720 according to examples as described herein, device 705 may support techniques for improving the user experience.

[0139] The wearable applications 720 may include applications (e.g., “apps”), programs, software, or other components configured to facilitate communication with the ring 104, the server 110, other user devices 106, etc. For example, the wearable applications 720 may include applications executable on the user device 106 configured to receive data (e.g., physiological data) from the ring 104, perform processing operations on the received data, send and receive data from the server 110, and present the data to the user 102.

[0140] FIG. 8 shows a flowchart illustrating a method 800 supporting techniques for wearable-based two-way sharing of data according to aspects of the present disclosure. The operations of method 800 may be implemented by a user device or components thereof as described herein. For example, the operations of method 800 may be performed by a user device such as those described with reference to FIGS. 1-7. In some examples, the user device may execute a set of instructions to control functional elements of the user device to perform the described functions. Additionally or alternatively, the user device may use dedicated hardware to perform aspects of the described functions.

[0141] At 803, the method may include transmitting, via wireless electronic communications, one or more requests to establish one or more wireless electronic communications links with one or more user devices associated with the group of users. The operations of 803 may be performed according to examples disclosed herein. In some examples, aspects of the operations of 803 may be performed by communications component 625 as described with reference to FIG. 6.

[0142] At 805, the method may include receiving instructions from one or more applications associated with the group of users via one or more wireless electronic communications links based at least in part on transmitting one or more requests, the instructions including authorization to send and receive physiological data between the one or more applications, the physiological data being based at least in part on physiological measurements collected from each user of the group of users via a wearable device associated with the one or more applications. The operations of 805 may be performed according to examples disclosed herein. In some examples, aspects of the operations of 805 may be performed by a communications component 625 as described with reference to FIG. 6.

[0143] At 810, the method may include receiving physiological data from one or more applications based at least in part on the instructions via one or more wireless electronic communications links. The operations of 810 may be performed according to examples disclosed herein. In some examples, aspects of the operations of 810 may be performed by a communications component 625 as described with reference to FIG. 6.

[0144] At 815, the method may include generating a score indicative of a physiological metric representative of the group of users based at least in part on the physiological data obtained from the one or more applications. The operations of 815 may be performed according to examples disclosed herein. In some examples, aspects of the operations of 815 may be performed by a processor 630 such as described with reference to FIG. 6.

[0145] At 820, the method may include transmitting, via one or more wireless electronic communications links, a control signal to cause at least one GUI of 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. The operations of 820 may be performed according to examples disclosed herein. In some examples, aspects of the operations of 820 may be performed by a graphics component 635 as described with reference to FIG. 6.

[0146] It should be noted that the methods described above describe possible implementations, and that operations and steps may be rearranged or possibly modified, and that other implementations are possible. Furthermore, aspects from two or more of the methods may be combined.

[0147] 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, the instructions including permission to send and receive physiological data between the one or more applications, the physiological data being based at least in part on physiological measurements collected from each user of the group of users via a wearable device associated with the one or more applications; acquiring the physiological data from the one or more applications; generating a score indicative of a physiological metric representative of the group of users based at least in part on the physiological data acquired from the one or more applications; and causing at least one GUI of a user device associated with the one or more applications to display the score.

[0148] An apparatus for sharing physiological data among a group of users is described. The apparatus may include a processor, a memory coupled to the processor, and instructions stored in the memory. The instructions may be executable by the processor to cause the apparatus to receive instructions from one or more applications associated with the group of users, the instructions including permission to send and receive physiological data between the one or more applications, the physiological data based at least in part on physiological measurements collected from each user of the group of users via a wearable device associated with the one or more applications; acquire physiological data from the one or more applications; generate a score indicative of a physiological metric representative of the group of users based at least in part on the physiological data acquired from the one or more applications; and display the score on at least one GUI of a user device associated with the one or more applications.

[0149] Another apparatus for sharing physiological data among a group of users is described. The apparatus may include means for receiving instructions from one or more applications associated with the group of users, the instructions including permission to send and receive physiological data between the one or more applications, the physiological data based at least in part on physiological measurements collected from each user of the group of users via a wearable device associated with the one or more applications, means for acquiring the physiological data from the one or more applications, means for generating a score indicative of a physiological metric representative of the group of users based at least in part on the physiological data acquired from the one or more applications, and means for displaying the score on at least one GUI of a user device associated with the one or more applications.

[0150] A non-transitory computer-readable medium storing code for sharing physiological data among a group of users is described. The code may include instructions executable by a processor to receive instructions from one or more applications associated with the group of users, the instructions including permission to send and receive physiological data between the one or more applications, the physiological data being based at least in part on physiological measurements collected from each user of the group of users via a wearable device associated with the one or more applications; obtain the physiological data from the one or more applications; generate a score indicative of a physiological metric representative of the group of users based at least in part on the physiological data obtained from the one or more applications; and cause at least one GUI of a user device associated with the one or more applications to display the score.

[0151] In some examples of the methods, apparatus, and non-transitory computer-readable media described herein, the physiological data includes first physiological data associated with a first user of the group of users and additional physiological data associated with the remaining users of the group of users excluding the first user, and the methods, apparatus, and non-transitory computer-readable media may further include further operations, features, means, 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 metric and causing at least one GUI of the device to display instructions of the first user based at least in part on the identifying.

[0152] Some examples of the methods, apparatus, and non-transitory computer-readable media described herein may further include operations, features, means, or instructions for identifying a spatial relationship between the group of users and sending a prompt to share physiological data between the group of users based at least in part on identifying the spatial relationship, where receiving the instruction may be based at least in part on sending the prompt.

[0153] Some examples of the methods, devices, and non-transitory computer-readable media described herein may further include operations, features, means, or instructions for obtaining baseline physiological data associated with a plurality of users, including a group of users; identifying one or more similarities between the baseline physiological data associated with each user from the group of users; and sending a prompt to share the physiological data among the group of users based at least in part on identifying the one or more similarities, where receiving the instruction may be based at least in part on sending the prompt.

[0154] Some examples of the methods, apparatus, and non-transitory computer-readable media described herein may further include operations, features, means, or instructions for identifying calendar data associated with each user of a group of users and causing at least one GUI of a user device associated with one or more applications to display recommendations based at least in part on the scores and the calendar data.

[0155] Some examples of the methods, apparatus, and non-transitory computer-readable media described herein may further include operations, features, means, or instructions for receiving, via an application associated with a first user of a group of users, an indication of one or more permitted physiological parameters, an indication of one or more permitted time periods, or both, wherein acquiring physiological data from the application associated with the user includes acquiring physiological data associated with the one or more permitted physiological parameters, acquiring physiological data within the one or more permitted time periods, or both.

[0156] In some examples of the methods, apparatus, and non-transitory computer-readable media described herein, at least one wearable device associated with each user of a group of users includes a wearable ring device.

[0157] Some examples of the methods, apparatus, and non-transitory computer-readable media described herein may further include operations, features, means, or instructions for transmitting additional control signals to one or more external devices associated with an ambient environment of the group of users, the additional control signals configured to modify one or more operating parameters of the one or more external devices to modify one or more characteristics of the ambient environment of the group of users.

[0158] Some examples of the methods, apparatus, and non-transitory computer-readable media described herein may further include operations, features, means, or instructions for receiving calendar data associated with a group of users and transmitting additional control signals to adjust times of meetings associated with at least a subset of the group of users based at least in part on the calendar data and a score associated with the group of users, where the one or more recommendations or insights include recommendations to adjust times of meetings.

[0159] The descriptions set forth herein with reference to the accompanying drawings describe exemplary configurations and do not necessarily represent every example that may be implemented or fall within the scope of the claims. As used herein, the term "exemplary" means "serving as an example, instance, or illustration" and does not mean "preferred" or "advantageous over other examples." However, these techniques may be practiced without these specific details. In some instances, well-known structures and devices are shown in block diagram form in order to avoid obscuring the concepts of the described examples.

[0160] In the accompanying drawings, similar components or features may have the same reference label. Furthermore, various components of the same type may be distinguished by following the reference label with a dash and a second label that distinguishes among the similar components. If only a first reference label is used herein, the description is applicable to any one of the similar components having the same first reference label, regardless of the second reference label.

[0161] The information and signals described herein may be represented using any of a variety of different technologies and techniques. For example, the data, instructions, commands, information, signals, bits, symbols, and chips that may be referenced throughout the above description may be represented by voltages, currents, electromagnetic waves, magnetic fields or particles, optical fields or particles, or any combination thereof.

[0162] The various example blocks and modules described in connection with the disclosure herein may be implemented or performed using a general-purpose processor, a DSP, an ASIC, an 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. A general-purpose processor may be a microprocessor, but alternatively, the processor may be any conventional processor, controller, microcontroller, or state machine. A 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 in conjunction with a DSP core, or any other such configuration).

[0163] The functions described herein may be implemented in hardware, software executed by a processor, firmware, or any combination thereof. If implemented in software executed by a processor, the functions may be stored or transmitted as one or more instructions or code on a computer-readable medium. Other examples and implementations are within the scope of this disclosure and the appended claims. For example, due to the nature of the software, the functions described above may be implemented using software executed by a processor, hardware, firmware, hardwiring, or any combination thereof. Features implementing the functions may also be physically located in various locations, including being distributed so that portions of the functions are implemented in different physical locations. Also, as used herein, including in the claims, "or" used in a list of items (e.g., a list of items ending with a phrase such as "at least one of" or "one or more of") indicates an inclusive list, such as, 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). Also, as used herein, the phrase "based on" should not be construed as referring to a closed set of conditions. For example, an example step described as "based on condition A" may be based on both condition A and condition B without departing from the scope of the present disclosure. In other words, as used herein, the phrase "based on" shall be interpreted the same as the phrase "based at least in part on."

[0164] Computer-readable media includes both non-transitory computer storage media and communication media, including any medium that facilitates transfer of a computer program from one place to another. Non-transitory storage media may be any available medium that can be accessed by a general-purpose or special-purpose computer. By way of example, and not limitation, non-transitory computer-readable media may comprise RAM, ROM, Electrically Erasable Programmable Read Only Memory (EEPROM), Compact Disc (CD) ROM or other optical disk storage, magnetic disk storage or other magnetic storage devices, or any other non-transitory medium that can be used to carry or store desired program code means in the form of instructions or data structures and that can be accessed by a general-purpose or special-purpose computer or a general-purpose or special-purpose processor. Also, any connection is properly termed a computer-readable medium. 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, the coaxial cable, fiber optic cable, twisted pair, DSL, or wireless technologies such as infrared, radio, and microwave are included in the definition of medium. As used herein, disk and disc include CDs, laser discs, optical discs, digital versatile discs (DVDs), floppy disks, and Blu-ray discs, where disks typically reproduce data magnetically and discs reproduce data optically using lasers. Combinations of the above are also included within the scope of computer-readable media.

[0165] The description herein is provided to enable any person skilled in the art to make or use the disclosure. Various modifications to the disclosure will be readily apparent to those skilled in the art, and the general principles defined herein may be applied to other variations without departing from the scope of the disclosure. Thus, the 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. 1. A method for sharing physiological data, comprising: transmitting, via wireless electronic communications, one or more requests to establish a data sharing group associated with a group of users; receiving instructions from one or more applications associated with the group of users via one or more wireless electronic communications links based at least in part on transmitting the one or more requests, the instructions including authorization to send and receive physiological data between the one or more applications, the physiological data based at least in part on physiological measurements collected from each user in the group of users via a wearable device associated with the one or more applications; receiving the physiological data from the one or more applications based at least in part on the instructions via the one or more wireless electronic communication links; generating a score indicative of a physiological metric representative of the group of users based at least in part on the physiological data obtained from the one or more applications; transmitting, via the one or more wireless electronic communications links, a control signal 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; A method comprising:

2. The physiological data includes first physiological data associated with a first user of the group of users and additional physiological data associated with remaining users of the group of users excluding the first user, and the method includes: 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 metric; causing the at least one graphical user interface of the one or more user devices to display instructions of the first user based at least in part on the identifying; and The method of claim 1 further comprising:

3. identifying spatial relationships between said groups of users; transmitting a prompt to share the physiological data among the group of users based at least in part on identifying the spatial relationship, wherein the receiving instruction is based at least in part on transmitting the prompt; and The method of claim 1 further comprising:

4. obtaining baseline physiological data associated with a plurality of users, including the group of users; identifying one or more similarities between the baseline physiological data associated with each user from the group of users; transmitting a prompt to share the physiological data among the group of users based at least in part on identifying the one or more similarities, wherein the receiving instruction is based at least in part on transmitting the prompt; and The method of claim 1 further comprising:

5. identifying calendar data associated with each user of said group of users; causing the 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; and The method of claim 1 further comprising:

6. receiving, via an application associated with a first user of the group of users among the one or more applications, an indication of one or more permitted physiological parameters, an indication of one or more permitted time periods, or both, wherein receiving the physiological data from the one or more applications includes receiving the physiological data associated with the one or more permitted physiological parameters, receiving the physiological data within the one or more permitted time periods, or both; The method of claim 1 further comprising:

7. The method of claim 1 , wherein at least one wearable device associated with each user of the group of users includes a wearable ring device.

8. The physiological data includes a first subset of physiological data corresponding to a first user of the group of users, the first subset of physiological data being associated with the physiological metric, and the method further comprising: causing the at least one graphical user interface of the one or more user devices to display a comparison of a first subset of the physiological data associated with the first user and the score indicative of the physiological metric representative of a group of users. The method of claim 1 further comprising:

9. transmitting additional control signals to one or more external devices associated with an ambient environment of the group of users, the additional control signals being configured to modify one or more operating parameters of the one or more external devices to modify one or more characteristics of the ambient environment of the group of users. The method of claim 1 further comprising:

10. receiving calendar data associated with the group of users; transmitting additional control signals to adjust times of meetings associated with at least a subset of the group of users based at least in part on the calendar data and the scores associated with the group of users, wherein the one or more recommendations or insights include recommendations to adjust the times of the meetings; and The method of claim 1 further comprising:

11. 1. An apparatus for sharing physiological data, comprising: at least one processor; a memory coupled to the at least one processor; instructions stored in said memory; wherein the instructions cause the device to: transmitting, via wireless electronic communications, one or more requests to establish one or more wireless electronic communications links with one or more user devices associated with a group of users; receiving instructions from one or more applications associated with the group of users via the one or more wireless electronic communications links based at least in part on transmitting the one or more requests, the instructions including authorization to send and receive physiological data between the one or more applications, the physiological data based at least in part on physiological measurements collected from each user in the group of users via a wearable device associated with the one or more applications; receiving the physiological data from the one or more applications based at least in part on the instructions via the one or more wireless electronic communication links; generating a score indicative of a physiological metric representative of the group of users based at least in part on the physiological data obtained from the one or more applications; transmitting, via the one or more wireless electronic communications links, a control signal 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; the method being further executable by the at least one processor to cause

12. The physiological data includes first physiological data associated with a first user of the group of users and additional physiological data associated with remaining users of the group of users excluding the first user, and the instructions further cause the device to: 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 metric; causing the at least one graphical user interface of the one or more user devices to display instructions of the first user based at least in part on the identifying; and 12. The apparatus of claim 11, wherein the method is executable by the at least one processor to cause:

13. The instructions further cause the device to: identifying spatial relationships between said groups of users; transmitting a prompt to share the physiological data among the group of users based at least in part on identifying the spatial relationship, wherein the receiving instruction is based at least in part on transmitting the prompt; and 12. The apparatus of claim 11, wherein the method is executable by the at least one processor to cause:

14. The instructions further cause the device to: obtaining baseline physiological data associated with a plurality of users, including the group of users; identifying one or more similarities between the baseline physiological data associated with each user from the group of users; transmitting a prompt to share the physiological data among the group of users based at least in part on identifying the one or more similarities, wherein the receiving instruction is based at least in part on transmitting the prompt; and 12. The apparatus of claim 11, wherein the method is executable by the at least one processor to cause:

15. The instructions further cause the device to: identifying calendar data associated with each user of said group of users; causing the 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; and 12. The apparatus of claim 11, wherein the method is executable by the at least one processor to cause:

16. The instructions further cause the device to: receiving, via an application associated with a first user of the group of users among the one or more applications, an indication of one or more permitted physiological parameters, an indication of one or more permitted time periods, or both, wherein receiving the physiological data from the one or more applications includes receiving the physiological data associated with the one or more permitted physiological parameters, receiving the physiological data within the one or more permitted time periods, or both.

12. The apparatus of claim 11, wherein the method is executable by the at least one processor to cause:

17. The apparatus of claim 11 , wherein at least one wearable device associated with each user of the group of users includes a wearable ring device.

18. 1. An apparatus for sharing physiological data, comprising: means for transmitting, via wireless electronic communications, one or more requests to establish one or more wireless electronic communications links with one or more user devices associated with a group of users; means for receiving instructions from one or more applications associated with the group of users via the one or more wireless electronic communications links based at least in part on sending the one or more requests, the instructions including authorization to send and receive physiological data between the one or more applications, the physiological data based at least in part on physiological measurements collected from each user in the group of users via a wearable device associated with the one or more applications; means for receiving the physiological data from the one or more applications based at least in part on the instructions via the one or more wireless electronic communication links; means for generating a score indicative of a physiological metric representative of the group of users based at least in part on the physiological data obtained from the one or more applications; means for transmitting, via the one or more wireless electronic communications links, a control signal 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; An apparatus comprising:

19. the physiological data includes first physiological data associated with a first user of the group of users and additional physiological data associated with remaining users of the group of users excluding the first user, and the device: means 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 metric; means for causing the at least one graphical user interface of the one or more user devices to display instructions of the first user based at least in part on the identifying; and 20. The apparatus of claim 18, further comprising:

20. 1. A non-transitory computer-readable medium storing code for sharing physiological data, the code comprising: transmitting, via wireless electronic communications, one or more requests to establish one or more wireless electronic communications links with one or more user devices associated with a group of users; receiving instructions from one or more applications associated with the group of users via the one or more wireless electronic communications links based at least in part on transmitting the one or more requests, the instructions including authorization to send and receive physiological data between the one or more applications, the physiological data based at least in part on physiological measurements collected from each user in the group of users via a wearable device associated with the one or more applications; receiving the physiological data from the one or more applications based at least in part on the instructions via the one or more wireless electronic communication links; generating a score indicative of a physiological metric representative of the group of users based at least in part on the physiological data obtained from the one or more applications; transmitting, via the one or more wireless electronic communications links, a control signal 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; A non-transitory computer-readable medium comprising instructions executable by a processor to perform the steps of:

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