User authentication using wearable devices

Abstract

Methods, systems, and devices for operating a wearable device are described. The wearable device may determine that a user is wearing the wearable device. The wearable device may collect physiological data from the user based on determining that the user is wearing the wearable device. The wearable device may then determine the identity of the user based at least in part on a match of the collected physiological data to a physiological profile associated with the identity. The wearable device may then authenticate the user for actions by the wearable device that require user authentication.

Description

[Technical field]

[0001] [Cross reference] This patent application claims the benefit of U.S. patent application Ser. No. 18 / 087,590 by Tily et al., entitled "USER AUTHENTICATION BY A WEARABLE DEVICE," filed December 22, 2022, and U.S. Provisional Patent Application No. 63 / 295,040 by Tily et al., entitled "USER AUTHENTICATION BY A WEARABLE DEVICE," filed December 30, 2021, each of which is assigned to the assignee hereof and each of which is expressly incorporated by reference herein.

[0002] [Technical field] The following relates to wearable devices and data processing, including user authentication with wearable devices. [Background technology]

[0003] Some wearable devices may be configured to collect personal data from a user. For example, a wearable device may include one or more sensors that collect physiological data from a user. A wearable device may also be capable of performing various actions, such as payment transactions or access procedures. Improved techniques for performing actions by wearable devices may be desired. [Brief description of the drawings]

[0004] [Figure 1] 1 illustrates an example of a system that supports user authentication via a wearable device, according to an aspect of the present disclosure. [Diagram 2] 1 illustrates an example of a system that supports user authentication via a wearable device, according to an aspect of the present disclosure. [Diagram 3] 1 illustrates an example of a system that supports user authentication via a wearable device, according to an aspect of the present disclosure. [Figure 4] FIG. 1 illustrates a block diagram of an apparatus that supports user authentication via a wearable device, according to an aspect of the present disclosure. [Diagram 5] FIG. 1 illustrates a block diagram of a wearable device manager supporting user authentication by a wearable device according to an aspect of the disclosure. [Figure 6] FIG. 1 illustrates a diagram of a system including a device that supports user authentication via a wearable device, according to an aspect of the disclosure. [Figure 7] 1 shows a flowchart illustrating a method for supporting user authentication with a wearable device according to an aspect of the present disclosure. DETAILED DESCRIPTION OF THE PREFERRED EMBODIMENTS

[0005] A wearable device may be configured to perform various actions on behalf of a user, such as payment transactions or access procedures. In some cases, however, an unauthorized person may gain access to a wearable device and use the wearable device to perform actions that are restricted to authorized users. For example, an unauthorized person may use the wearable device to make fraudulent payments, sign in to an account, or access restricted areas. In accordance with techniques described herein, a wearable device may perform an authentication procedure before allowing a person to initiate actions that are restricted to authorized users of the wearable device.

[0006] To support the authentication procedure, the wearable device may collect physiological data for an authorized user such that the wearable device can build a physiological profile for the authorized user. When the wearable device detects that it is being worn by a person, the wearable device may collect physiological data from the person and compare the physiological data to the authorized user's physiological profile. If the physiological data from the person matches the authorized user's profile, the wearable device may identify the person as an authorized user and authenticate the person. If not (e.g., if the physiological data from the person does not match the authorized user's physiological profile), the wearable device may flag the person as an unauthorized user of the wearable device and prevent the person from initiating actions that require user authentication. The physiological profile may also be referred to as a physiological signature, a physiological pattern, or a biometric profile, among other suitable terms.

[0007] Aspects of the present disclosure are first described in the context of a system supporting physiological data collection from a user via a wearable device. Aspects of the present disclosure are further illustrated by and described with reference to apparatus diagrams, system diagrams, and flow charts relating to user authentication via a wearable device.

[0008] 1 illustrates an example of a system 100 supporting user authentication via wearable devices, according to an embodiment of the present disclosure. The system 100 includes multiple electronic devices (e.g., wearable device 104, user device 106) that may be worn and / or operated by one or more users 102. The system 100 further includes a network 108 and one or more servers 110.

[0009] The electronic devices may include any electronic devices known in the art, such as wearable devices 104 (e.g., ring wearable devices, watch 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 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.

[0010] Exemplary wearable devices 104 may include wearable computing devices such as a ring computing device (hereinafter, “ring”) configured to be worn on a finger of the user 102, a wrist computing device (e.g., a smart watch, fitness band, or bracelet) configured to be worn on the wrist of the user 102, and / or a head-mounted computing device (e.g., glasses / 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 placed in other locations such as bands around the head (e.g., a forehead headband), bands around the arms (e.g., a forearm band and / or a bicep band), and / or bands around the legs (e.g., a thigh or calf band), behind the ear, under the armpit, 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 items 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.

[0011] Much of the present disclosure may be described in the context of a ring wearable device 104. Thus, the terms "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., watch wearable devices, necklace wearable devices, bracelet wearable devices, earring wearable devices, anklet wearable devices, etc.).

[0012] 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.

[0013] Some electronic devices (e.g., wearable device 104, user device 106) may measure physiological parameters of the respective 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 terminal application, or a server computing device may process received physiological data measured by other devices.

[0014] In some implementations, the user 102 may operate or be associated with multiple electronic devices, some of which may measure physiological parameters and some of which may process the measured physiological parameters. In some implementations, the user 102 may have a ring (e.g., 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 terminal, 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.

[0015] For example, as shown in FIG. 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 the 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 watch wearable device 104-c (e.g., watch 104-c), and a user device 106-b, and the user device 106-b associated with the 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, the 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.

[0016] In some implementations, the ring 104 (e.g., wearable device 104) of the system 100 may be configured to collect physiological data from each user 102 based on arterial blood flow in the user's finger. In particular, the ring 104 may utilize one or more LEDs (e.g., red LEDs, green LEDs) that emit light to the palm side of the user's finger to collect physiological data based on arterial blood flow in the user's finger. In some implementations, the ring 104 may use a combination of both green and red LEDs to obtain physiological data. 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. In general, terms such as light emitting components, light emitting elements, etc. may include, but are not limited to, LEDs, micro LEDs, mini LEDs, laser diodes (LDs), etc.

[0017] In some cases, the system 100 may be configured to collect physiological data from each user 102 based on blood flow diffused into the microvascular bed of the skin having capillaries and arterioles. For example, the system 100 may collect PPG data based on a measured amount of blood diffused into the microvasculature of capillaries and arterioles. In some implementations, the ring 104 may obtain 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.

[0018] The use of both green and red LEDs may provide several advantages over other solutions, since red and green LEDs have been found to each have their own distinct advantages when acquiring physiological data through different parts of the body under different conditions (e.g., light / dark, active / inactive). 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 compared to wearable devices that use LEDs placed close to each other, such as in a watch wearable device. Furthermore, blood vessels (e.g., arteries, capillaries) in the fingers are easier to access via LEDs compared to blood vessels in the wrist. In particular, the arteries in the wrist are located on the lower part of the wrist (e.g., the palm side of the wrist), which means that capillaries are only accessible on the upper part of the wrist (e.g., the back side of the wrist) where wearable watch devices and similar devices are typically worn. In this manner, the use of 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 the arteries (compared to capillaries), which can result in a stronger signal and more informative physiological data.

[0019] The electronic devices (e.g., user device 106, wearable device 104) of the system 100 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., user device 106) may be communicatively coupled to one or more servers 110 via a network 108. The network 108 may implement a Transport Control Protocol and Internet Protocol (TCP / IP), such as the Internet, or other network 108 protocols. The network connection between the network 108 and the respective electronic devices may facilitate the transfer of data via e-mail, web, text message, mail, or any other suitable form of interaction within the computer network 108. For example, in some implementations, the ring 104-a associated with the first user 102-a may be communicatively coupled to the 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 communicatively coupled directly to the network 108.

[0020] The system 100 may provide on-demand database services between the user device 106 and one or more servers 110. In some cases, the servers 110 may receive data from the user device 106 over the network 108 and may store and analyze the data. Similarly, the servers 110 may provide data to the user device 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 device 106 via a web browser.

[0021] In some aspects, 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., 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, respiration rate, etc. In some aspects, 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.

[0022] In some aspects, 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 a 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.

[0023] In some embodiments, the 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 adjustment of the model in this manner include: 1) ultradian (rhythms faster than a day, including sleep cycles during sleep states and oscillations with periodicity of less than an hour to several hours in the measured physiological variables 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 artificial time periodicities that are exogenously imposed (e.g., a hypothetical culture with a 12-day "week" might use a 12-day rhythm), 5) daily ovarian rhythms in women and spermatogenic rhythms in men, 6) lunar rhythms (relevant to people living with little or no artificial light), and 7) seasonal rhythms.

[0024] Biological rhythms are not necessarily stationary rhythms. For example, many women experience variability in ovarian cycle length from cycle to cycle, and ultradian rhythms are not expected to occur at exactly the same time or periodicity across days, even within a user. Therefore, signal processing techniques sufficient to quantify the frequency content while maintaining the time resolution of these rhythms in the physiological data may be used to improve the detection of these rhythms, assigning the phase of each rhythm to each measured time point, and thereby modifying the adjustment models and comparison of time intervals. Biological rhythm adjustment models and parameters may be added in linear or nonlinear combinations as needed to more accurately capture the dynamic physiological baseline of an individual or group of individuals.

[0025] In some aspects, the wearable device 104 may be configured to authenticate the user 102 as an authorized user of the wearable device 104 (or as an authorized user for one or more actions) before allowing the user 102 to initiate an action restricted to authorized users. For example, upon determining that a person is wearing the wearable device 104, the wearable device 104 may collect physiological data of the person and compare the physiological data to a physiological profile associated with the authorized user. If the physiological data from the person matches the physiological profile of the authorized user, the wearable device 104 may authenticate the person as an authorized user. If the physiological data from the person does not match the physiological profile of the authorized user, the wearable device 104 may not authenticate the person as an authorized user.

[0026] Upon authenticating the person, the wearable device 104 may allow the person to initiate various actions that are restricted to authorized users. For example, the wearable device 104 may allow the person to initiate a payment procedure, an access procedure, or a sign-in procedure. To prevent unauthorized users from subsequently initiating such transactions using the wearable device 104, the wearable device 104 may perform an authentication procedure whenever the wearable device 104 senses that the wearable device 104 has been removed. For example, after authenticating a person, if the wearable device 104 determines that the wearable device 104 has been removed since authenticating the person, the wearable device 104 may perform the authentication procedure again.

[0027] Because physiological data is unique to a person, the use of physiological data to perform user authentication may require less effort from the user and may be more reliable than other techniques (e.g., techniques that require input from the user and rely on passcodes that may be used by unauthorized users). The use of physiological data to perform user authentication may also ensure that physiological data collected about a person (e.g., for insurance rate or rebate purposes, clinical trial purposes) is associated with the correct person.

[0028] It should be understood by those skilled in the art that one or more aspects of the present disclosure may additionally or alternatively be implemented in the system 100 to solve problems other than those described above. Furthermore, aspects of the present disclosure may provide technical improvements over "conventional" systems or processes as described herein. However, the description and accompanying drawings only include exemplary technical improvements resulting from implementing aspects of the present disclosure, and therefore do not necessarily represent all of the technical improvements provided within the scope of the claims.

[0029] 2 illustrates an example of a system 200 supporting user authentication via a wearable device, according to an aspect 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.

[0030] 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, and the like.

[0031] 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.

[0032] 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 house 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 substrates (e.g., printable circuit boards) that interconnect the device electronics and / or the power source, and the like. 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, and the like. 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.

[0033] The sensors may include associated modules (not shown) configured to communicate with the respective components / modules of the ring 104 and generate signals associated with the respective sensors. In some aspects, each of the components / modules of the ring 104 may be communicatively coupled to one another via a wired or wireless connection. Additionally, the ring 104 may include additional and / or alternative sensors or other components configured to collect physiological data from the user, including light sensors (e.g., LEDs), oximeters, etc.

[0034] 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.

[0035] 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., the metal outer housing 205-b). The housing 205 may provide structural support to the device electronics, the battery 210, the substrate(s), and other components. For example, the housing 205 may protect the device electronics, the battery 210, and the substrate(s) from mechanical forces such as pressure and impact. The housing 205 may also protect the device electronics, the battery 210, and the substrate(s) from water and / or other chemicals.

[0036] The outer housing 205-b may be fabricated from one or more materials. In some implementations, the outer housing 205-b may include a metal such as titanium, which may provide strength and wear resistance while being relatively lightweight. The outer housing 205-b may also be manufactured from other materials, such as polymers. In some implementations, the outer housing 205-b may be decorative as well as protective.

[0037] 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-a. 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.

[0038] 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. Exemplary substrates may include one or more printed circuit boards (PCBs), such as a flexible PCB (e.g., polyimide). In some implementations, the electronics / battery 210 may include surface mounted devices (e.g., surface mount technology (SMT) devices) on a flexible PCB. In some implementations, the one or more substrates (e.g., one or more flexible PCBs) may include electrical traces that provide electrical communication between the device electronics. The electrical traces may also connect the battery 210 to the device electronics.

[0039] The device electronics, battery 210, and substrate may be arranged in a variety of ways within the ring 104. In some implementations, one substrate containing the device electronics may be mounted along the bottom (e.g., bottom half) of the ring 104 such that the sensors (e.g., PPG system 235, temperature sensor 240, motion sensor 245, and other sensors) interface with the underside of the user's finger. In these implementations, the battery 210 may be included (e.g., on a separate substrate) along an upper portion of the ring 104.

[0040] 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 implementing 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.).

[0041] The memory 215 (memory module) of the ring 104 may include any volatile, non-volatile, magnetic, or electrical media, such as random access memory (RAM), read only memory (ROM), non-volatile RAM (NVRAM), electrically erasable programmable ROM (EEPROM), flash memory, or any other memory device. The memory 215 may store any of the data described herein. For example, the memory 215 may be configured to store data (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.

[0042] The functionality attributed to the modules of the 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 highlight different functional aspects and does not necessarily imply that such modules must be realized by separate hardware / software components. Rather, functionality associated with one or more modules may be performed by separate hardware / software components or integrated within a common hardware / software component.

[0043] 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 the modules and other components of the ring 104, such as 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).

[0044] 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.

[0045] The communication module 220-a may include circuitry to provide 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 processing module 230-a of the ring may be configured to send / receive data to / from the user device 106 via the communication module 220-a. Exemplary data may include, but are 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.

[0046] 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 charged. 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 curvature 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.

[0047] In some aspects, the ring 104 includes a power module 225 that may control charging of the battery 210. For example, the power module 225 may interface with an external wireless charger that charges the battery 210 when interfaced with the ring 104. The charger may include a reference structure that mates with the ring 104 reference structure to create a specified orientation with the ring 104 during 104 charging. The power module 225 may 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 may include a protection circuit module (PCM) that protects the battery 210 from high current discharge, overvoltage during 104 charging, and undervoltage during 104 discharging. The power module 225 may also include electrostatic discharge (ESD) protection.

[0048] 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 temperature of the user 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 thermally insulating portion may insulate portions of the ring 104 (eg, the temperature sensor 240) from the ambient temperature.

[0049] 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. Exemplary temperature sensors 240 may include thermistors, such as negative temperature coefficient (NTC) thermistors, or other types of sensors including resistors, transistors, diodes, and / or other electrical / electronic components.

[0050] 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.

[0051] 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 a minute and dividing by the number of samples in that minute. In a particular example where the temperature is sampled at 1 sample / second, the average temperature may be the sum of all sampled temperatures in a minute divided by 60 seconds. The memory 215 may store the average temperature values ​​over time. In some implementations, the memory 215 may store the average temperature instead of the sampled temperatures (e.g., 1 per minute) to conserve the memory 215.

[0052] 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 be changed throughout the day / night. In some implementations, the ring 104 may filter / reject temperature readings, such as large spikes in temperature that are not indicative of a physiological change (e.g., a temperature spike from a hot shower). In some implementations, the ring 104 may filter / reject temperature readings that may be unreliable due to other factors, such as excessive movement during 104 exercise (e.g., as indicated by the motion sensor 245).

[0053] 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.

[0054] 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, the one or more temperature sensors 240 may be included with (e.g., packaged with) other components, such as an accelerometer and / or a processor.

[0055] The processing module 230-a may obtain 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 sample, average, and store temperature data from each of the multiple temperature sensors 240 individually. 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.

[0056] 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 at the finger by the ring 104 are described herein, other devices may measure temperatures at the same / different locations. In some cases, the distal temperature measured at the 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 the 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 locations on the body. In some cases, continuous temperature measurements at the finger may capture temperature fluctuations (e.g., small or large fluctuations) that may not be evident in the core temperature. For example, continuous temperature measurements at a finger can 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.

[0057] 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 receiver may generate a signal (hereinafter, a "PPG" signal) that indicates the amount of light received by the optical receiver. The optical transmitter 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.

[0058] In some implementations, the PPG system 235 may be configured as a reflective PPG system 235 in which the optical receiver(s) receive transmitted light reflected through 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 the optical transmitter(s) and optical receiver(s) are arranged opposite one another such that light is transmitted directly through a portion of the user's finger to the optical receiver(s).

[0059] 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 reflective and / or transmissive PPG systems 235.

[0060] 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., 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.

[0061] 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).

[0062] Sampling the PPG signal generated by the PPG system 235 may result in a pulse waveform, which may be referred to as a "PPG." The pulse waveform may indicate blood pressure versus time for multiple cardiac cycles. The pulse waveform may include peaks indicative of cardiac cycles. Additionally, the pulse waveform may include respiratory induced variations, which may be used to determine respiratory rate. The processing module 230-a, in some implementations, may store the pulse waveform in the memory 215. The processing module 230-a may process the pulse waveform as it is generated and / or from the memory 215 to determine user physiological parameters as described herein.

[0063] 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 the IBI value in the memory 215.

[0064] The processing module 230-a may determine HRV over time. For example, the processing module 230-a may determine HRV based on the variation of IBl. The processing module 230-a may store the HRV values ​​over time in the 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 the memory 215.

[0065] 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 the movement of the sensor. For example, the ring 104 may include one or more accelerometers that generate acceleration signals indicative of the 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 may measure angular velocity and acceleration in three perpendicular axes.

[0066] 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.

[0067] 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.

[0068] 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 score), 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 regarding motion. Exemplary derived values ​​for motion data may include, but are not limited to, a motion count value, a regularity value, an intensity value, a metabolic equivalence of task (MET) value, and an orientation value. The motion count, regularity value, intensity value, and MET may indicate the amount (e.g., speed / acceleration) of the user's motion 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.

[0069] 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 one 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).

[0070] 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 the data over a longer period of time to reduce the number of values ​​stored. In a particular example, if the average temperature of a user 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. The processing module 230-a may compress the data based on various factors, such as the total amount of used / available memory 215 and / or the time since the ring 104 last transmitted data to the user device 106.

[0071] The user's physiological parameters may be measured by a sensor provided on the ring 104, although other devices may measure the user's physiological parameters. For example, the user's temperature may be measured by a 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.

[0072] Physiological measurements may be taken continuously throughout the day and / or night. In some implementations, physiological measurements may be taken during portions of the day and / or portions of the night 104. In some implementations, physiological measurements may be taken in response to a determination 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.

[0073] 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, and the like. The wearable application 250 may include examples of applications (e.g., “apps”) that may be installed on the user device 106. The wearable application 250 may be configured to obtain data from the ring 104, store the obtained data, and process the obtained 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.

[0074] Various data processing operations described herein may be performed by the ring 104, the user device 106, the server 110, or any combination thereof. For example, in some cases, data collected by the ring 104 may be pre-processed and transmitted to the user device 106. In this example, the user device 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 device 106 may perform processing operations that require relatively low processing power and / or operations that require relatively low latency, while the user device 106 may transmit data to the server 110 for processing operations that require relatively high processing power and / or operations that can tolerate relatively high latency.

[0075] In some aspects, the ring 104, the user device 106, and the server 110 of the system 200 may be configured to evaluate a user's sleep patterns. In particular, each component of the system 200 may be used to collect data from the user via the ring 104 and generate one or more scores (e.g., sleep score, readiness score) for the user based on the collected data. For example, as previously described herein, the ring 104 of the 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 aspects, 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 and a second sleep day is associated with a second set of scores. A score may be calculated for each sleep day based on the data collected by the ring 104 during each sleep day. The scores may include, but are not limited to, a sleep score, a readiness score, etc.

[0076] In some cases, the "sleep days" may coincide with traditional calendar days, such that a given sleep day is from midnight to midnight on the respective calendar day. In other cases, the sleep days may be offset relative to the calendar days. For example, a sleep day may be from 6:00pm (18:00) on a calendar day to 6:00pm (18:00) on the next calendar day. In this example, 6:00pm may serve as a "cutoff time" such that data collected from the user before 6:00pm is counted into the current sleep day and data collected from the user after 6:00pm is counted into the next sleep day. Due to the fact that most individuals sleep best at night, offsetting the sleep days relative to the calendar days allows the system 200 to evaluate the user's sleep patterns in a manner that is consistent with the user's sleep schedule. In some cases, the user may be able to selectively adjust the timing of the sleep days relative to the calendar days (e.g., via a GUI) to align the sleep days with the duration that the respective user typically sleeps.

[0077] In some implementations, the user's respective overall score (e.g., sleep score, readiness score) for each day may be determined / calculated based on one or more "contributors," "factors," or "contributing factors." For example, the 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 of 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) of a sleep day, weighted by the duration of each sleep period. A "restfulness" contributing factor may indicate how restful the user's sleep is and may be calculated using an average of all sleep periods of 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 wakeups (when the user wakes up) detected during different sleep periods), excessive movement, and "got up count" (e.g., the sum of all wakeups (when the user gets out of bed) detected during different sleep periods).

[0078] The "REM sleep" contributor may refer to the sum of REM sleep duration across all sleep periods of a sleep day, including REM sleep. Similarly, the "deep sleep" contributor may refer to the sum of deep sleep duration across all sleep periods of a sleep day, including deep sleep. The "latency" contributor 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 throughout 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 contributor or may weight other contributors). Finally, the "timing" contributor 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 of a sleep day, weighted by the duration of each period.

[0079] 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, body temperature, activity, activity balance, or any combination thereof. The readiness score may include any number of contributing factors. The "sleep" contributing factor may refer to the combined sleep score of all sleep periods within a sleep day. The "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 had over a period of duration (e.g., the past two weeks) is balanced with the user's needs. Typically, an adult requires 7-9 hours of sleep per night to be healthy, alert, and performing at their best mentally and physically. However, it is normal to have occasional bad sleep days, and therefore the sleep balance contributing factor takes into account long-term sleep patterns to determine whether each user's sleep needs are being met. The "resting heart rate" contributor may indicate the minimum heart rate from the longest sleep period (eg, the main sleep period) of a sleep day and / or the minimum heart rate from a nap occurring after the main sleep period.

[0080] Continuing with reference to the "contributing factors" (e.g., factors, contributors) of the readiness score, the "HRV balance" contributor may indicate the highest HRV average from the main sleep period and the sleep period that occurs after the main sleep period. The HRV balance contributor may help the user track their recovery status by comparing the user's HRV trend over a first period (e.g., 2 weeks) to the average HRV over some second longer period (e.g., 3 months). The "recovery index" contributor may be calculated based on the longest sleep period. The recovery index measures how long it takes for the user's resting heart rate to stabilize during the night. A sign of very good recovery is that the user's resting heart rate stabilizes during the first half of the night, at least 6 hours before the user wakes up, leaving time for the body to recover for the next day. The "body temperature" contributor may be calculated based on the longest sleep period (e.g., main sleep period) or based on the sleep period that occurs after the longest sleep period if the user's highest body temperature during the sleep period is at least 0.5°C higher than the highest body temperature during the longest period. In some aspects, 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 above or below 0.0), the temperature contributor may be highlighted (e.g., go to a "Pay attention" state) or otherwise generate an alert to the user.

[0081] In some aspects, the system 200 may support techniques for authenticating a user. For example, the ring 104 may collect physiological data of an authorized user (e.g., over a period of time) and use the physiological data to build a physiological profile of the authorized user. The ring 104 may then use the physiological profile to authenticate a user of the ring 104. The ring 104 may store the physiological profile in a memory of the ring 104 (e.g., memory 215), may communicate the physiological profile to the user device 106, or may do both. Storing the physiological profile in memory 215 allows the ring 104 to perform an authentication procedure using the physiological profile even in the absence of a wireless connection (e.g., the ring 104 may perform an authentication procedure using the physiological profile without communicating with another device, such as the user device 106). If the ring 104 communicates the physiological profile to the user device 106 (which allows the ring 104 to reserve space in memory 215), the ring 104 may request (and receive) the physiological profile from the user device 106 so that the ring 104 can perform the authentication procedure.

[0082] Because the ring 104 is a wearable device that collects physiological data continuously or over time, the physiological profile constructed by the ring 104 may be more comprehensive (e.g., including more user-specific biometric factors), robust (e.g., more difficult to fake), and / or reliable (e.g., more consistent) than other physiological profiles that are based on snapshots of physiological data. Although described with reference to a wearable ring device, the authentication techniques described herein may be implemented using any type of wearable device.

[0083] 3 illustrates an example of a system 300 supporting user authentication via a wearable device, according to an aspect of the disclosure. The system 300 may include a wearable device 304 and an associated user device 306. The system 300 may also include a payment terminal 308 that may be configured to wirelessly perform payment transactions, an access terminal 310 that may be configured to wirelessly grant access to restricted areas (e.g., buildings, rooms, vehicles) or electronic devices (e.g., computers, phones), and a wearable device 312 that may be similar to the wearable device 304.

[0084] The wearable device 304 may use the physiological data to perform an authentication procedure for the user 302, in which the identity of the user 302 is determined. For example, upon determining that a person (e.g., the user 302) is wearing the wearable device 304 (or in response to a prompt by another device, such as the user device 306), the wearable device 304 may collect physiological data from the user 302 and compare the collected physiological data to a physiological profile of an authorized user of the wearable device 304. If the physiological data is sufficiently similar to the physiological profile (e.g., the physiological data matches or is within a margin of error with the physiological profile), the wearable device 304 may authenticate the user 302 (e.g., the wearable device 304 may determine the identity of the user 302 as that of an authorized user). The wearable device 304 may collect the physiological data of the user 302 using one or more sensors that interface with the skin of the user 302.

[0085] In some examples, the physiological profile may be based on or include PPG data, which may also be referred to as a PPG signal pattern or other suitable terminology. The physiological profile may include various characteristics of the authorized user, such as heart rate, heart rate variability, blood pressure, oxygen saturation, respiration, artery stiffness, body impedance, appendage size (e.g., finger size), temperature (e.g., basal body temperature), pulse characteristics (e.g., systolic amplitude, systolic width, rise width, ratio of pulse length to systolic amplitude, rise time), or any combination thereof.

[0086] The physiological characteristics may be based on or derived from PPG data or other physiological data collected by the wearable device. Some physiological characteristics may also be based on or derived from data received from other devices. For example, the wearable device 304 may determine the impedance of an authorized user based on data from another wearable device (e.g., a ring, watch, ankle bracelet) worn by the authorized user. In some examples, the wearable device 304 may use impedance to determine other physiological characteristics of the user 302 that can be used for authentication, such as body composition (e.g., percentage of muscle, fat, water).

[0087] For comparison, physiological data collected for the user 302 that corresponds to the physiological characteristics includes the physiological profile of an authorized user. For example, if the physiological profile of an authorized user includes PPG data such as heart rate, body temperature, and impedance, the physiological data collected for the user 302 may include PPG data of the same physiological characteristics (e.g., heart rate, body temperature, and impedance).

[0088] In some examples, the wearable device 304 may use a neural network, such as a deep neural network, to perform authentication using physiological data. For example, the wearable device 304 may use a Siamese neural network that includes two sister networks. Each sister network may include multiple hidden layers and may use the same weights while operating in tandem on two different input vectors. The Siamese neural network may operate on collected physiological data about the user 302 and physiological data from the physiological profile of authorized users and output a value (e.g., a binary value) indicating whether the user 302 is an authorized user. For example, the Siamese neural network may operate on pairs of pulses (where each pair includes a pulse for the user 302 and a pulse for an authorized user) to extract pulse characteristics that are used to authenticate the user 302. The physiological characteristics may also be referred to as physiological features.

[0089] To train the Siamese neural network, a pulse pair input may be formed by iterating through each of the pulses in the training set, selecting the current pulse as an anchor, and pairing the anchor with one positive example and one negative example. Each positive example may be randomly sampled from among the pulses of the same user, except for the anchor pulse, and each negative example may be randomly sampled from among the pulses of other users. The same procedure may be repeated for the validation set. Other examples of neural networks and training are contemplated and are within the scope of this disclosure.

[0090] In some examples, the wearable device 304 may normalize physiological data collected for the user 302 before comparing the physiological data to the physiological profile of an authorized user. Normalizing the physiological data may refer to scaling the physiological data. By normalizing the physiological data, the wearable device 304 may compensate for differences in the physiological data that occur when the user 302 is in a different condition (e.g., sick vs. healthy), performing a different activity (e.g., exercising vs. resting), or in a different environment (e.g., at a higher altitude vs. a lower altitude) compared to when the physiological profile was constructed. Thus, the wearable device 304 may normalize the physiological data of the user 302 based on the condition of the user 302, based on the activity being performed by the user 302, based on the environment of the user 302, or based on any combination thereof.

[0091] In some examples, the physiological profile may include one or more acceleration or motion patterns for the authorized user. For example, the physiological profile may include a hand motion pattern routinely performed by the authorized user, or a walking pattern of the authorized user (e.g., based on cadence, arm speed, arm angle, arm swing profile), which may be based on the authorized user's accelerometer data and / or gyroscope data.

[0092] As another example, the physiological profile may include one or more hand gestures predefined by the user 302. The hand gesture may be a swinging pattern, a tapping pattern (e.g., tapping the wearable device 304 with a finger or tapping a surface with a ring-finger or ring-hand), or a rotational pattern (e.g., rotating the wearable device 304 around the user's 302 limb, such as turning the dial of a combination lock). For example, the user 302 may activate the wearable device 304 in a first orientation and then rotate the wearable device 304 back and forth around the user's finger a certain number of times and / or at a certain angle / degrees.

[0093] In addition to physiological characteristics and movement patterns, the wearable device 304 may authenticate the user 302 using other factors (e.g., geographic location, proximity to a user device). For example, the wearable device 304 may authenticate the user 302 if the user 302 is in an expected geographic location at a particular time (e.g., as part of the user's commute). The wearable device 304 may determine the location of the user 302 by communicating with the user device or one or more nearby devices with a known geographic location. Additionally or alternatively, the wearable device 304 may authenticate the user 302 if the user 302 (and thus the wearable device 304) is within a threshold distance of a user device 306 associated with an authorized user.

[0094] After authenticating the user 302, the wearable device 304 may continue to consider the user 302 an authorized user for a threshold period of time or until a triggering event causes the wearable device 304 to perform a new authentication procedure. Examples of triggering events include the completion of an action that requires authentication or the removal of the wearable device 304 from the user 302.

[0095] The wearable device 304 may determine that the wearable device 304 has been removed based on a discontinuity in a signal sensed by a sensor of the wearable device 304. For example, the wearable device 304 may determine that the wearable device 304 has been removed if the wearable device 304 determines that it has failed to detect a physiological signal (such as a pulse) from the user 106 for a threshold time. Additionally or alternatively, the wearable device 304 may determine that the wearable device 304 has been removed based on detecting a rotation of the wearable device 304, an axial rotation of the wearable device 304, or both. Additionally or alternatively, the wearable device 304 may determine that the wearable device 304 has been removed (e.g., slid from an authorized user's finger to a fake one) based on a change in the quality of the PPG data, a change in light, a change in temperature, or a change in air pressure. For example, the wearable device 304 may include a light detector disposed opposite the light transmitter (e.g., on an inner surface of the inner housing 205-a) such that the light detector can detect light emitted by the light transmitter unless an obstruction (e.g., a user's finger) blocks the light. In such an example, the wearable device 304 may detect removal of the wearable device 304 based on a disruption of the light detected by the light detector.

[0096] After authorizing the user 302, the wearable device 304 may activate a communication component (e.g., the communication module 220-a). The wearable device 304 may activate the communication component in response to authorizing the user 302, in response to an unlocking action by the user 302, or both. The wearable device 304 may also allow the user 302 to initiate various actions that require authentication (e.g., actions that are limited to authorized users). For example, the wearable device 304 may enable the user 302 to initiate a payment transaction with the payment terminal 308 (e.g., using the communication component). As another example, the wearable device 304 may enable the user 302 to initiate an access procedure with the access terminal 310 (e.g., using the communication component). As another example, the wearable device 304 may enable the user 302 to initiate a data transfer with the user device 306, the wearable device 312, or both. In some examples (e.g., in a two-factor authentication scenario), the wearable device 304 may send an indication to another device (e.g., the user device 306) that the user 302 has been authenticated, so that the other device can grant the user 302 access to areas, electronic devices, accounts, or applications that are restricted to authorized users.

[0097] To prevent the user 302 from inadvertently initiating an action (e.g., activating a communication component, making a payment) after the user 302 is authenticated, the wearable device 304 may require the user 302 to perform an unlocking action before the wearable device 304 initiates the action. For example, even if the user 302 is authenticated, the wearable device 304 may not initiate a payment transaction unless the user 302 performs a predefined gesture (such as tapping the wearable device 304 on the payment terminal 308, waving the wearable device 304 in a predefined pattern over the payment terminal 308, or using a finger to tap the wearable device 304 in a predefined pattern or tempo, or rotating the wearable device 304 in a predefined pattern, etc.).

[0098] In some examples, the wearable device 304 may prevent the user 302 from initiating an action until the wearable device 304 authenticates the user 302's status (even if the user 302 is authenticated and performs the required unlocking action). For example, the wearable device 304 may prevent the user 302 from accessing the automobile if the user 302 is intoxicated or drowsy. The wearable device 304 may prevent the user 302 from initiating an action by deactivating a communication component or by refraining from communicating with a gatekeeper device (e.g., the access terminal 310). Alternatively, the wearable device 304 may prevent the action by alerting the gatekeeper device of the user 302's status (so that the gatekeeper device rejects an attempt by the user 302 to initiate the action). In some examples, the wearable device 304 may alert the user 302 of the user's status. For example, the wearable device 304 may vibrate or output a signal (e.g., a visual signal, an audible signal) indicating the user's condition, or the wearable device 304 may communicate the condition to the user device 306 so that the user device 306 can alert the user 302.

[0099] In addition to authenticating the user 302 to initiate certain actions, the wearable device 304 may also authenticate the user 302 so that the wearable device 304 can autonomously perform certain actions specific to authorized users. For example, the wearable device 304 may authenticate the user 302 as the correct person to collect data from before collecting physiological data for insurance or clinical trial purposes (which may prevent the wearable device 304 from collecting physiological data for an imposter). Additionally or alternatively, the wearable device 304 may authenticate the user 302 before collecting physiological data for use by the wearable device 304 or before collecting physiological data to update an authorized user's physiological profile.

[0100] As mentioned above, the wearable device 304 may include a communication component configured to wirelessly communicate with other devices. In some examples, the communication may be an NFC component that may help prevent accidental initiation of actions due to NFC range limitations. The use of an NFC component may also enable charging of the wearable device 304 and may be easier to implement relative to other wireless communication technologies. However, the communication component is not limited to NFC technology and may implement other types of wireless communication technologies such as Wi-Fi and Bluetooth, among others.

[0101] In some examples, the communication component may be used to transfer data between the wearable device 304 and the other device (e.g., the user device 306, the wearable device 312). As described above, authentication of the user 302 (and possibly an unlocking action by the user 302) may activate the communication component. After the communication component is activated, a trigger action (e.g., tapping the wearable device 304 against the other device) may prompt the wearable device 304 to exchange data with the other device. The trigger action may also initiate a direct token exchange between the wearable device 304 and the other device, which may be used by the user device 306 (or some other device or application) to authenticate the user (of the wearable device 304 and the other device) and initiate data transfer. In some cases, the user 302 may tap the wearable device 304 against the other device to trigger some action by the other device (such as putting the other device into airplane mode).

[0102] 4 illustrates a block diagram 400 of a device 405 supporting user authentication by a wearable device, according to an embodiment of the disclosure. The device 405 may include an input module 410, an output module 415, and a wearable device manager 420. The device 405 may also include a processor. Each of these components may communicate with each other (e.g., via one or more buses).

[0103] For example, the wearable device manager 420 may include a processing module 425, a sensing circuit 430, or any combination thereof. In some examples, the wearable device manager 420 or various components thereof may be configured to perform various operations (e.g., receiving, monitoring, transmitting) using or otherwise cooperating with the input module 410, the output module 415, or both. For example, the wearable device manager 420 may receive information from the input module 410, transmit information to the output module 415, or may be integrated in combination with the input module 410, the output module 415, or both to receive information, transmit information, or perform various other operations as described herein.

[0104] The processing module 425 may be configured or otherwise support a means for determining, by the wearable device, that a user is wearing the wearable device on the user's finger. The sensing circuit 430 may be configured or otherwise support a means for collecting physiological data from the user based at least in part on determining that the user is wearing the wearable device. The processing module 425 may be configured or otherwise support a means for determining the identity of the user based at least in part on a match of the collected physiological data to a physiological profile associated with the identity. The processing module 425 may be configured or otherwise support a means for authenticating the user for actions by the wearable device that require user authentication.

[0105] 5 illustrates a block diagram 500 of a wearable device manager 520 supporting user authentication with a wearable device, according to an embodiment of the disclosure. The wearable device manager 520 may be an example of an embodiment of a wearable device manager or a wearable device manager 420, or both, as described herein. The wearable device manager 520, or various components thereof, may be an example of a means for performing various aspects of user authentication with a wearable device, as described herein. For example, the wearable device manager 520 may include a processing module 525, a sensing circuit 530, a communication component 535, a memory module 540, or any combination thereof. Each of these components may communicate directly or indirectly with each other (e.g., via one or more buses).

[0106] The processing module 525 may be configured or otherwise support a means for determining, by the wearable device, that a user is wearing the wearable device on the user's finger. The sensing circuit 530 may be configured or otherwise support a means for collecting physiological data from the user based at least in part on determining that the user is wearing the wearable device. In some examples, the processing module 525 may be configured or otherwise support a means for determining the identity of the user based at least in part on the matching of the collected physiological data to a physiological profile associated with the identity (e.g., the processing module 525 may determine that the user is an authorized user based on the matching of the collected physiological data to a physiological profile associated with an authorized user). In some examples, the processing module 525 may be configured or otherwise support a means for authenticating the user for actions by the wearable device that require user authentication.

[0107] In some examples, the communications component 535 may be configured with or otherwise support a means for initiating an action based at least in part on authenticating the user. In some examples, the processing module 525 may be configured with or otherwise support a means for determining that the wearable device has remained on the user's finger since authenticating the user, where the action is initiated based at least in part on determining that the wearable device has remained on the user's finger since authenticating the user.

[0108] In some examples, the action includes a payment transaction. In some examples, the action includes collecting additional physiological data about the identity.

[0109] In some examples, the processing module 525 may be configured as or otherwise support a means for activating a communication component based at least in part on authenticating a user and based at least in part on a gesture performed by the user or the proximity of the wearable device to the user.

[0110] In some examples, the processing module 525 may be configured as or otherwise support a means for deactivating a communications component based at least in part on a threshold period of time having elapsed since activating the communications component, based at least in part on completing an action, based at least in part on the proximity of the wearable device to the user exceeding a threshold distance, or any combination thereof.

[0111] In some examples, the gesture includes tapping the payment terminal with the wearable device, and the communications component 535 may be configured with or otherwise support as a means for communicating payment information to the payment terminal based at least in part on activating the communications component.

[0112] In some examples, the sensing circuitry 530 may be configured with or otherwise support a means for collecting accelerometer data about a user, and a gesture determined based at least in part on the accelerometer data.

[0113] In some examples, the processing module 525 may be configured with or otherwise support a means for determining a physiological profile over a period of time, hi some examples, the processing module 525 may be configured with or otherwise support a means for storing the physiological profile in a memory of the wearable device, communicating the physiological profile to a user device, or both.

[0114] In some examples, the physiological profile is determined in the absence of a wireless connection, the identity of the user is determined in the absence of a wireless connection, and the user is authenticated in the absence of a wireless connection.

[0115] In some examples, the physiological profile includes PPG data. In some examples, the processing module 525 may be configured with or otherwise support a means for determining one or more physiological characteristics of the user based at least in part on the PPG data, and an identity of the user is determined based at least in part on the one or more physiological characteristics.

[0116] In some examples, the one or more physiological characteristics include heart rate, heart rate variability, blood pressure, or a combination thereof. In some examples, the physiological data includes second PPG data, and the processing module 525 may be configured with or otherwise support a means for normalizing the second PPG data based at least in part on an activity being performed by the user, based at least in part on a condition associated with the user, or both.

[0117] In some examples, the physiological profile includes a movement pattern associated with a movement of the user. In some examples, the movement pattern includes a predefined hand gesture performed by the user. In some examples, the hand gesture includes a rotation pattern of the wearable device around a finger of the user.

[0118] In some examples, the processing module 525 may be configured with or otherwise support a means for determining a geographic location of a user, where the identity of the user is determined based at least in part on the geographic location of the user.

[0119] In some examples, the processing module 525 may be configured with or otherwise support a means for determining the proximity of the wearable device to a user device associated with an identity, where the identity of the user is determined based at least in part on the proximity of the wearable device to the user device.

[0120] In some examples (e.g., when authenticating the user is part of a first authentication procedure), the processing module 525 may be configured or otherwise support as a means for determining that the user has removed the wearable device after authenticating the user. In such examples, the processing module 525 may be configured or otherwise support as a means for performing a second authentication procedure for the user based at least in part on determining that the user has removed the wearable device after authenticating the user.

[0121] In some examples, the processing module 525 may be configured with or otherwise support a means for activating a communications component based at least in part on authenticating a user. In some examples, the communications component 535 may be configured with or otherwise support a means for performing an access procedure or a sign-in procedure using the communications component.

[0122] In some examples, the processing module 525 may be configured with or otherwise support a means for activating a communications component based at least in part on authenticating a user. In some examples, the communications component 535 may be configured with or otherwise support a means for initiating a data transfer with another device based at least in part on activating the communications component.

[0123] In some examples, the processing module 525 may be configured with or otherwise support a means for determining that the wearable device is within a threshold distance of another device, where data transfer is initiated based at least in part on the wearable device determining that it is within a threshold distance of the other device.

[0124] In some examples, the physiological data is collected using one or more sensors of the wearable device, and the memory module 540 may be configured as or otherwise support a means for storing the physiological data in the memory of the wearable device.

[0125] In some examples, the wearable device includes a wearable ring device.

[0126] In some examples, the wearable device collects physiological data based on arterial blood flow.

[0127] FIG. 6 illustrates a diagram of a system 600 including a device 605 supporting user authentication by a wearable device, according to an embodiment of the disclosure. The device 605 may be or include an example of the components of the device 405 as described herein. The device 605 may include an example of the wearable device 104 as previously described herein. The device 605 may include components for bidirectional communication, including components for transmitting and receiving communications with the user device 106 and the server 110, such as a wearable device manager 620, a communication module 610, an antenna 615, a sensor component 625, a power module 630, a memory 635, a processor 640, and a wireless device 650. 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 645).

[0128] For example, the wearable device manager 620 may be configured or otherwise support a means for determining, by the wearable device, that a user is wearing the wearable device on the user's finger. The wearable device manager 620 may be configured or otherwise support a means for collecting physiological data from a user based at least in part on determining that the user is wearing the wearable device. The wearable device manager 620 may be configured or otherwise support a means for determining a user's identity based at least in part on a match of the collected physiological data to a physiological profile associated with the identity. The wearable device manager 620 may be configured or otherwise support a means for authenticating a user for actions by the wearable device that require user authentication.

[0129] By including or configuring a wearable device manager 620 according to examples described herein, the device 605 may support techniques for user authentication by a wearable device.

[0130] FIG. 7 shows a flowchart illustrating a method 700 of supporting user authentication by a wearable device according to an aspect of the present disclosure. The operations of method 700 may be implemented by a wearable device or components thereof as described herein. For example, the operations of method 700 may be performed by a wearable device as described with reference to FIGS. 1-6. In some examples, the wearable device may execute a set of instructions to control functional elements of the wearable device to perform the described functions. Additionally or alternatively, the wearable device may use dedicated hardware to perform aspects of the described functions.

[0131] At 705, the method may include determining, by the wearable device, that a user is wearing the wearable device on the user's finger. The operations of 705 may be performed according to examples disclosed herein. In some examples, aspects of the operations of 705 may be performed by processing module 525, as described with reference to FIG.

[0132] At 710, the method may include collecting physiological data from the user based at least in part on determining that the user is wearing the wearable device. The operations of 710 may be performed according to examples disclosed herein. In some examples, aspects of the operations of 710 may be performed by sensing circuitry 530, as described with reference to FIG.

[0133] At 715, the method may include determining an identity of the user based at least in part on a match of the collected physiological data to a physiological profile associated with the identity. The operations of 715 may be performed according to examples disclosed herein. In some examples, aspects of the operations of 715 may be performed by processing module 525, as described with reference to FIG.

[0134] At 720, the method may include authenticating a user for actions by the wearable device that require user authentication. The operations of 720 may be performed according to examples disclosed herein. In some examples, aspects of the operations of 720 may be performed by processing module 525, as described with reference to FIG.

[0135] It should be noted that the methods described above describe possible implementations, and that the operations and steps may be rearranged or otherwise modified, and other implementations are possible. Additionally, aspects from two or more of the methods may be combined.

[0136] A method is described that may include determining, by a wearable device, that a user is wearing the wearable device on the user's finger, collecting physiological data from the user based at least in part on determining that the user is wearing the wearable device, determining an identity of the user based at least in part on a match of the collected physiological data to a physiological profile associated with the identity, and authenticating the user for actions by the wearable device that require user authentication.

[0137] An apparatus is described that may include a processor, a memory coupled to the processor, and instructions stored in the memory. The instructions are executable by the processor to cause the apparatus to determine, with a wearable device, that a user is wearing the wearable device on the user's finger, collect physiological data from the user based at least in part on determining that the user is wearing the wearable device, determine an identity of the user based at least in part on a match of the collected physiological data to a physiological profile associated with the identity, and authenticate the user for actions by the wearable device that require user authentication.

[0138] Another apparatus is described that may include means for determining, by a wearable device, that a user is wearing the wearable device on the user's finger, means for collecting physiological data from the user based at least in part on determining that the user is wearing the wearable device, means for determining an identity of the user based at least in part on a match of the collected physiological data to a physiological profile associated with the identity, and means for authenticating the user for actions by the wearable device that require user authentication.

[0139] A non-transitory computer readable medium storing code is described that may include instructions executable by a processor to determine, by a wearable device, that a user is wearing the wearable device on the user's finger, collect physiological data from the user based at least in part on determining that the user is wearing the wearable device, determine an identity of the user based at least in part on a match of the collected physiological data to a physiological profile associated with the identity, and authenticate the user for actions by the wearable device that require user authentication.

[0140] Some examples of the methods, apparatus, and non-transitory computer-readable media described herein may further include operations, features, means, or instructions for initiating an action based at least in part on authenticating a user.

[0141] Some examples of the methods, apparatus, and non-transitory computer-readable media described herein may further include operations, features, means, or instructions for determining that the wearable device may remain worn on the user's finger since authenticating the user, and an action may be initiated based at least in part on determining that the wearable device may remain worn on the user's finger since authenticating the user.

[0142] In some examples of the methods, apparatus, and non-transitory computer-readable media described herein, the action includes a payment transaction.

[0143] In some examples of the methods, apparatus, and non-transitory computer-readable media described herein, the action includes collecting additional physiological data about the identity.

[0144] Some examples of the methods, apparatus, and non-transitory computer-readable media described herein may further include operations, features, means, or instructions for activating a communication component based at least in part on authenticating the user and based at least in part on a gesture performed by the user or the proximity of the wearable device to the user.

[0145] Some examples of the methods, apparatus, and non-transitory computer-readable media described herein may further include operations, features, means, or instructions for deactivating the communications component based at least in part on a threshold period of time having elapsed since activating the communications component, based at least in part on completing an action, based at least in part on the proximity of the wearable device to the user exceeding a threshold distance, or any combination thereof.

[0146] In some examples of the methods, apparatus, and non-transitory computer-readable media described herein, the gesture includes tapping a payment terminal with the wearable device, and the methods, apparatus, and non-transitory computer-readable media may include further operations, features, means, or instructions for communicating payment information to the payment terminal based at least in part on activating the communication component.

[0147] Some examples of the methods, apparatus, and non-transitory computer-readable media described herein may further include operations, features, means, or instructions for collecting accelerometer data about the user, and gestures may be determined based at least in part on the accelerometer data.

[0148] Some examples of the methods, apparatus, and non-transitory computer-readable media described herein may further include operations, features, means, or instructions for determining a physiological profile over a period of time and storing the physiological profile in a memory of the wearable device, communicating the physiological profile to a user device, or both.

[0149] In some examples of the methods, apparatus, and non-transitory computer-readable media described herein, a physiological profile may be determined in the absence of a wireless connection, a user's identity may be determined in the absence of a wireless connection, and a user may be authenticated in the absence of a wireless connection.

[0150] In some examples of the methods, devices, and non-transitory computer-readable media described herein, the physiological profile includes PPG data. Some examples of the methods, devices, and non-transitory computer-readable media described herein may further include operations, features, means, or instructions for determining one or more physiological characteristics of the user based at least in part on the PPG data, and the identity of the user may be determined based at least in part on the one or more physiological characteristics.

[0151] In some examples of the methods, devices, and non-transitory computer-readable media described herein, the one or more physiological characteristics include heart rate, heart rate variability, blood pressure, or a combination thereof.

[0152] In some examples of the methods, devices, and non-transitory computer-readable media described herein, the physiological data includes second PPG data, and the methods, devices, and non-transitory computer-readable media may include further operations, features, means, or instructions for normalizing the second PPG data based at least in part on an activity being performed by the user, based at least in part on a condition associated with the user, or based on both.

[0153] In some examples of the methods, devices, and non-transitory computer-readable media described herein, the physiological profile includes a movement pattern associated with the user's movement.

[0154] In some examples of the methods, apparatus, and non-transitory computer-readable media described herein, the movement patterns include predefined hand gestures performed by the user.

[0155] In some examples of the methods, apparatus, and non-transitory computer-readable media described herein, the hand gesture includes a rotation pattern of the wearable device around the user's finger.

[0156] Some examples of the methods, apparatus, and non-transitory computer-readable media described herein may further include operations, features, means, or instructions for determining a geographic location of a user, and the identity of the user may be determined based at least in part on the user's geographic location.

[0157] Some examples of the methods, apparatus, and non-transitory computer-readable media described herein may further include operations, features, means, or instructions for determining the proximity of the wearable device to a user device associated with an identity, and the user's identity may be determined based at least in part on the proximity of the wearable device to the user device.

[0158] In some examples of the methods, apparatus, and non-transitory computer-readable media described herein (e.g., when authenticating the user is part of a first authentication procedure), the methods, apparatus, and non-transitory computer-readable media may include further operations, features, means, or instructions for determining that, after authenticating the user, the user may have removed the wearable device, and performing a second authentication procedure for the user based at least in part on determining that, after authenticating the user, the user may have removed the wearable device.

[0159] Some examples of the methods, apparatus, and non-transitory computer-readable media described herein may further include operations, features, means, or instructions for activating a communications component based at least in part on authenticating the user and performing an access procedure or a sign-in procedure using the communications component.

[0160] Some examples of the methods, apparatus, and non-transitory computer-readable media described herein may further include operations, features, means, or instructions for activating a communications component based at least in part on authenticating the user, and initiating a data transfer with another device based at least in part on activating the communications component.

[0161] Some examples of the methods, apparatus, and non-transitory computer-readable media described herein may further include operations, features, means, or instructions for determining that the wearable device is within a threshold distance of another device, and data transfer may be initiated based at least in part on determining that the wearable device may be within a threshold distance of the other device.

[0162] In some examples of the methods, apparatus, and non-transitory computer-readable media described herein, physiological data may be collected using one or more sensors of the wearable device, and the methods, apparatus, and non-transitory computer-readable media may include further operations, features, means, or instructions for storing the physiological data in a memory of the wearable device.

[0163] In some examples of the methods, apparatus, and non-transitory computer-readable media described herein, the wearable device includes a wearable ring device. In some examples of the methods, apparatus, and non-transitory computer-readable media described herein, the wearable device collects physiological data based on arterial blood flow.

[0164] The description set forth herein with respect to the accompanying drawings illustrates exemplary configurations and does not necessarily represent all examples that may be implemented or are within the scope of the claims. The term "exemplary" as used herein means "serving as an example, instance, or illustration" and does not mean "preferred" or "advantageous over other examples." The detailed description includes specific details for the purposes of providing an understanding of the described techniques. 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.

[0165] In the accompanying figures, 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 the similar components. If only a first reference label is used herein, the description is applicable to any of the similar components having the same first reference label, regardless of the second reference label.

[0166] 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.

[0167] 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).

[0168] The functions described herein may be implemented in hardware, software executed by a processor, firmware, or any combination thereof. When implemented in software executed by a processor, the functions may be stored or transmitted as one or more instructions or codes on a computer-readable medium. Other examples and implementations are within the scope of this disclosure and the 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. The features implementing the functions may also be physically located in various locations, including being distributed such that parts of the functions are implemented in different physical locations. Also, as used herein, including the claims, "or" used in a list of items (e.g., a list of items preceded by 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 a reference 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" is intended to be interpreted similarly to the phrase "based at least in part on."

[0169] Computer-readable media includes both communication media and non-transitory computer storage 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 is accessible by a general purpose or special purpose computer. By way of example and not limitation, non-transitory computer-readable media may include RAM, ROM, Electrically Erasable Programmable ROM (EEPROM), Compact Disk (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 the 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 the medium. As used herein, disk and disc include CDs, laser discs, optical discs, digital versatile discs (DVDs), floppy disks, and Blu-ray discs, where a disk typically reproduces data magnetically and a disc reproduces data optically with a laser. Combinations of the above are also included within the scope of computer readable media.

[0170] The description herein is provided to enable any person skilled in the art to make or use the present disclosure. Various modifications to the present 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 present disclosure. Thus, the present disclosure is not limited to the examples and designs described herein, but should be accorded the widest scope consistent with the principles and novel features disclosed herein.

Claims

1. A method in a wearable device, comprising: determining, by the wearable device, that a user is wearing the wearable device on the user's finger; collecting physiological data from the user based at least in part on determining that the user is wearing the wearable device; determining an identity of the user based at least in part on a match of the collected physiological data to a physiological profile associated with the identity; authenticating the user for actions by the wearable device that require user authentication; The method includes:

2. initiating the action based at least in part on authenticating the user, the action including a payment transaction or collecting additional physiological data about the identity. The method of claim 1 further comprising:

3. determining that the wearable device has remained on the user's finger since authenticating the user, the action being initiated based at least in part on determining that the wearable device has remained on the user's finger since authenticating the user. The method of claim 2 , further comprising:

4. activating a communication component based at least in part on authenticating the user and based at least in part on a gesture performed by the user or a proximity of the wearable device to the user. The method of claim 1 further comprising:

5. deactivating the communications component based at least in part on a threshold time period having elapsed since activating the communications component, based at least in part on completing the action, based at least in part on the proximity of the wearable device to the user exceeding a threshold distance, or any combination thereof. The method of claim 4 further comprising:

6. The gesture includes tapping a payment terminal with the wearable device, and the method further comprises: communicating payment information to the payment terminal based at least in part on activating the communication component. The method of claim 4 further comprising:

7. collecting accelerometer data about the user, the gesture being determined based at least in part on the accelerometer data; The method of claim 6 further comprising:

8. determining said physiological profile over a period of time; storing the physiological profile in a memory of the wearable device, communicating the physiological profile to a user device, or both; The method of claim 1 further comprising:

9. The physiological profile includes photoplethysmography (PPG) data, and the method further comprises: determining one or more physiological characteristics of the user based at least in part on the PPG data, wherein an identity of the user is determined based at least in part on the one or more physiological characteristics. The method of claim 1 further comprising:

10. The method of claim 9 , wherein the one or more physiological characteristics include heart rate, heart rate variability, blood pressure, or a combination thereof.

11. The physiological data includes second PPG data, and the method further comprises: normalizing the second PPG data based at least in part on an activity being performed by the user, based at least in part on a state associated with the user, or both. The method of claim 9 further comprising:

12. The method of claim 1 , wherein the physiological profile comprises a movement pattern associated with the user's movement.

13. The method of claim 12 , wherein the movement patterns include predefined hand gestures performed by the user.

14. determining a proximity of the wearable device to a user device associated with the identity, the identity of the user being determined at least in part based on the proximity of the wearable device to the user device; The method of claim 1 further comprising:

15. The step of authenticating the user is part of a first authentication procedure, and the method comprises: determining, after authenticating the user, that the user has removed the wearable device; performing a second authentication procedure for the user based at least in part on determining that the user has removed the wearable device after authenticating the user; The method of claim 1 further comprising:

16. activating a communications component based at least in part on authenticating the user; performing an access procedure or a sign-in procedure using said communications component; The method of claim 1 further comprising:

17. activating a communications component based at least in part on authenticating the user; initiating a data transfer with another device based at least in part on activating the communications component; The method of claim 1 further comprising:

18. The physiological data is collected using one or more sensors of the wearable device, and the method comprises: Storing the physiological data in a memory of the wearable device. The method of claim 1 further comprising:

19. A wearable device, A processor; a memory coupled to the processor; instructions stored in said memory; and the instructions cause the device to: determining, by the wearable device, that a user is wearing the wearable device on the user's finger; collecting physiological data from the user based at least in part on determining that the user is wearing the wearable device; and determining an identity of the user based at least in part on a match of the collected physiological data to a physiological profile associated with the identity; authenticating the user for actions by the wearable device that require user authentication; A wearable device, wherein the wearable device is executable by the processor to cause the wearable device to perform the above steps.

20. A non-transitory computer readable medium storing code, the code being configured to: determining, by the wearable device, that a user is wearing the wearable device on the user's finger; collecting physiological data from the user based at least in part on determining that the user is wearing the wearable device; and determining an identity of the user based at least in part on a match of the collected physiological data to a physiological profile associated with the identity; authenticating the user for actions by the wearable device that require user authentication; A non-transitory computer-readable medium comprising instructions executable by a processor to cause the

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