Techniques for providing physiological state-related insights associated with a user

Abstract

Methods, systems, and devices are described for providing physiological state related insights associated with a user. One method includes receiving physiological data associated with a user from at least one wearable device, the physiological baseline providing reference user alertness data. The method also includes obtaining a physiological baseline associated with the user based at least in part on the baseline physiological data associated with the user, the physiological baseline providing reference user alertness data. The method also includes receiving additional physiological data associated with the user from the at least one wearable device. The method also includes obtaining current user alertness data based at least in part on the additional physiological data associated with the user. The method also includes identifying a trigger condition for providing a physiological state related insight associated with the user based at least in part on a comparison between the current user alertness data and the reference user alertness data, the physiological state related insight related to a travel event involving at least one vehicle. The method also includes causing a user device to provide the physiological state related insight associated with the user.

Description

Technical Field

[0001] This invention relates to wearable devices and data processing, including techniques for providing insights related to a user's physiological state. Background Technology

[0002] Some wearable devices can be configured to collect data from users related to exercise, sleep, and other factors. The collected data can provide further information about the user's alertness. For example, a user may have had poor sleep quality in the past few days, which could affect their alertness and thus influence the actions they will perform. Summary of the Invention

[0003] This summary is provided to introduce selected concepts in a simplified form, which will be further described in the detailed description below. This summary is not intended to identify key or essential features of the claimed subject matter, nor is it intended to limit the scope of the claimed subject matter.

[0004] According to a first aspect, a method for providing physiological state-related insights associated with a user includes: receiving baseline physiological data associated with the user from at least one wearable device; obtaining a physiological baseline associated with the user based at least in part on the baseline physiological data associated with the user, the physiological baseline providing reference user alertness data; receiving additional physiological data associated with the user from at least one wearable device; obtaining current user alertness data based at least in part on the additional physiological data associated with the user; identifying triggering conditions for providing physiological state-related insights associated with the user based at least in part on a comparison between the current user alertness data and the reference user alertness data, the physiological state-related insights being related to a travel event involving at least one mode of transportation; and causing the user device to provide the physiological state-related insights associated with the user.

[0005] In an example embodiment of the first aspect, identifying the triggering condition further includes identifying the triggering condition when the current user alertness data differs from the reference user alertness data by a predetermined threshold amount.

[0006] In an example embodiment of the first aspect, the travel event is a future travel event.

[0007] In an example embodiment of the first aspect, the travel event is the current travel event.

[0008] In an example embodiment of the first aspect, the physiological data includes accelerometer data, and the method further includes identifying that the user is driving at least one vehicle based at least in part on a comparison between the accelerometer data and reference accelerometer data; and detecting a travel event based at least in part on the comparison.

[0009] In an example embodiment of the first aspect, the method further includes establishing a valid local communication link between the user equipment and at least one vehicle; and detecting travel events based at least in part on the existence of a valid local communication link between the user equipment and at least one vehicle.

[0010] In an example embodiment of the first aspect, the method further includes receiving satellite positioning data from a user equipment; and detecting travel events based at least in part on the satellite positioning data from the user equipment.

[0011] In an example embodiment of the first aspect, the method further includes sending an instruction to at least one wearable device in response to detecting a travel event to send physiological data at a preset rate.

[0012] In an example embodiment of the first aspect, enabling a user device to provide physiological state-related insights associated with a user includes sending the physiological state-related insights to at least one vehicle via an effective local communication link between the user device and at least one vehicle.

[0013] In an example embodiment of the first aspect, enabling a user device to provide physiological state-related insights associated with a user includes enabling a graphical user interface of the user device to display physiological state-related insights.

[0014] In an example embodiment of the first aspect, enabling the user device to provide physiological state-related insights associated with the user includes enabling the user device to provide at least one of auditory alarms, tactile alarms, and visual alarms associated with the physiological state-related insights.

[0015] In an example embodiment of the first aspect, the method further includes receiving vehicle data associated with a user from at least one vehicle, wherein the vehicle data associated with the user includes user behavior data collected during a travel event, and wherein identifying triggering conditions includes identifying triggering conditions based at least in part on the vehicle data associated with the user.

[0016] In an example embodiment of the first aspect, the method further includes receiving meteorological data associated with a travel event; determining, based on the meteorological data associated with the travel event, that the meteorological data associated with the travel event affects the travel event; and wherein identifying triggering conditions includes identifying triggering conditions at least in part based on the meteorological data.

[0017] In an example embodiment of the first aspect, the method further includes receiving calendar data associated with a travel event; determining, based on the calendar data associated with the travel event, that the travel event is a future travel event; and wherein identifying triggering conditions includes identifying triggering conditions at least in part based on the determination result.

[0018] In an example embodiment of the first aspect, the method further includes receiving satellite positioning data associated with a travel event from a user device; determining, based on the satellite positioning data associated with the travel event, that the travel event is related to a route that the user has not traveled; and wherein identifying triggering conditions includes identifying triggering conditions at least in part based on the determination result.

[0019] In an example embodiment of the first aspect, the method further includes receiving route planning data associated with a travel event; wherein identifying triggering conditions includes identifying triggering conditions based at least in part on the route planning data.

[0020] According to a second aspect, an apparatus for providing physiological state-related insights associated with a user includes: a processor; a memory coupled to the processor; and instructions stored in the memory and executable by the processor, the instructions causing the apparatus to perform the following operations: receiving baseline physiological data associated with the user from at least one wearable device; obtaining a physiological baseline associated with the user based at least in part on the baseline physiological data associated with the user, the physiological baseline providing reference user alertness data; receiving additional physiological data associated with the user from at least one wearable device; obtaining current user alertness data based at least in part on the additional physiological data associated with the user; identifying triggering conditions for providing physiological state-related insights associated with the user based at least in part on a comparison between the current user alertness data and the reference user alertness data, the physiological state-related insights being related to a travel event involving at least one mode of transportation; and causing the user device to provide physiological state-related insights associated with the user.

[0021] In an example embodiment of the second aspect, when a trigger condition is identified, the instruction may also be executed by the processor to cause the device to identify the trigger condition when the current user alertness data differs from the reference user alertness data by a predetermined threshold amount.

[0022] In an example embodiment of the second aspect, the travel event is a future travel event.

[0023] In an example embodiment of the second aspect, the travel event is the current travel event.

[0024] In an example embodiment of the second aspect, the additional physiological data includes accelerometer data, and the instructions may also be executed by the processor to cause the device to identify, at least in part, that a user is driving at least one vehicle based on a comparison between the accelerometer data and reference accelerometer data; and to detect a travel event based at least in part on the comparison.

[0025] In an example embodiment of the second aspect, the instructions may also be executed by a processor to enable the device to establish a valid local communication link between the user equipment and at least one vehicle, and to detect travel events based at least in part on the existence of a valid local communication link between the user equipment and at least one vehicle.

[0026] In an example embodiment of the second aspect, the instructions may also be executed by a processor to cause the device to receive satellite positioning data from the user equipment and to detect travel events based at least in part on the satellite positioning data from the user equipment.

[0027] In an example embodiment of the second aspect, the instructions may also be executed by the processor to cause the device to send instructions to at least one wearable device in response to detecting a travel event, to send physiological data at a preset rate.

[0028] In an example embodiment of the second aspect, when enabling the user equipment to provide physiological state-related insights associated with the user, the instructions may also be executed by the processor to cause the device to send the physiological state-related insights to at least one vehicle via an effective local communication link between the user equipment and at least one vehicle.

[0029] In an example embodiment of the second aspect, when enabling the user device to provide physiological state-related insights associated with the user, the instructions may also be executed by the processor to cause the device to display the physiological state-related insights in the graphical user interface of the user device.

[0030] In an example embodiment of the second aspect, when the user device is made to provide physiological state-related insights associated with the user, the instructions may also be executed by the processor to make the device make the user device provide at least one of auditory alarms, tactile alarms, and visual alarms associated with the physiological state-related insights.

[0031] In an example embodiment of the second aspect, the instructions may also be executed by a processor to cause the device to receive vehicle data associated with a user from at least one vehicle, wherein the vehicle data associated with the user includes user behavior data collected during a travel event, and wherein identifying triggering conditions includes identifying triggering conditions based at least in part on the vehicle data associated with the user.

[0032] In an example embodiment of the second aspect, the instructions may also be executed by a processor to cause the device to receive meteorological data associated with a travel event; determine, based on the meteorological data associated with the travel event, that the meteorological data associated with the travel event affects the travel event; and wherein identifying triggering conditions for providing insights into the physiological state of the user related to the travel event includes identifying the triggering conditions at least in part based on the meteorological data.

[0033] In an example embodiment of the second aspect, the instructions may also be executed by a processor to cause the device to receive calendar data associated with a travel event; determine, based on the calendar data associated with the travel event, that the travel event is a future travel event; and wherein identifying triggering conditions for providing insights into the physiological state of the user related to the travel event includes identifying the triggering conditions at least in part based on the determination result.

[0034] In an example embodiment of the second aspect, the instructions may also be executed by a processor to cause the device to receive satellite positioning data associated with a travel event from a user equipment; determine, based on the satellite positioning data associated with the travel event, that the travel event is related to a route that the user has not traveled; and wherein identifying triggering conditions for providing insights into the physiological state of the user related to the travel event includes identifying the triggering conditions at least in part based on the determination result.

[0035] In an example embodiment of the second aspect, the instructions may also be executed by the processor to cause the device to receive route planning data associated with a travel event; wherein identifying triggering conditions for providing insights into the physiological state of the user associated with the travel event includes identifying the triggering conditions at least in part based on the route planning data.

[0036] According to a third aspect, a non-transitory computer-readable medium stores code including processor-executable instructions to perform the following operations: receiving baseline physiological data associated with a user from at least one wearable device; obtaining a user-associated physiological baseline based at least in part on the user-associated baseline physiological data, the physiological baseline providing reference user alertness data; receiving additional physiological data associated with the user from at least one wearable device; obtaining current user alertness data based at least in part on the user-associated additional physiological data; identifying triggering conditions for providing user-associated physiological state-related insights based at least in part on a comparison between the current user alertness data and the reference user alertness data, the physiological state-related insights being related to a travel event involving at least one mode of transportation; and causing the user device to provide user-associated physiological state-related insights.

[0037] According to a fourth aspect, a device for providing physiological state-related insights associated with a user includes means for: receiving baseline physiological data associated with the user from at least one wearable device; obtaining a physiological baseline associated with the user based at least in part on the baseline physiological data associated with the user, the physiological baseline providing reference user alertness data; receiving additional physiological data associated with the user from at least one wearable device; obtaining current user alertness data based at least in part on the additional physiological data associated with the user; identifying triggering conditions for providing physiological state-related insights associated with the user based at least in part on a comparison between the current user alertness data and the reference user alertness data, the physiological state-related insights being related to a travel event involving at least one mode of transportation; and causing the user device to provide physiological state-related insights associated with the user. Attached Figure Description

[0038] Figure 1 An example of a system is shown that supports the technologies for providing insights related to a user's physiological state, according to various aspects of this disclosure.

[0039] Figure 2 An example of a system is shown that supports the technologies for providing insights related to a user's physiological state, according to various aspects of this disclosure.

[0040] Figure 3 An example of a system is shown that supports the technologies for providing insights related to a user's physiological state, according to various aspects of this disclosure.

[0041] Figure 4 A block diagram of an apparatus for providing insights into a user’s physiological state, supported by various aspects of this disclosure, is shown.

[0042] Figure 5 A block diagram of a wearable application supporting technologies for providing insights related to a user's physiological state, according to various aspects of this disclosure, is shown.

[0043] Figure 6 A schematic diagram of a system according to various aspects of this disclosure is shown, the system including devices supporting technologies for providing insights related to a user's physiological state.

[0044] Figure 7 A flowchart is shown that illustrates a method for providing insights into a user’s physiological state, supported by various aspects of this disclosure.

[0045] Figure 8 A block diagram illustrating the relationship between data attributes measured and derived according to various aspects of this disclosure is shown. Detailed Implementation

[0046] Wearable devices (such as wearable rings) can be used to collect, monitor, and track user-related physiological data based on sensor measurements performed by the wearable device. Examples of physiological data that can be collected by wearable devices can include temperature data, heart rate data, photoplethysmography (PPG) data, blood oxygen saturation data, etc. Physiological data collected, monitored, and tracked via wearable devices can be used to obtain health insights about the user, such as sleep patterns, activity patterns, etc. However, health insights provided by many traditional wearable devices may be irrelevant to future or current travel events involving transportation, making it impossible for users to take action on health insights related to travel events, or for transportation to incorporate health insights into its monitoring of users during travel events, such as sharing health insights with the transportation system.

[0047] Therefore, aspects of this disclosure relate to technologies that enable user equipment to provide actionable guidance or insights related to travel events involving vehicles, so that users can receive guidance actively or passively.

[0048] For example, wearable devices can acquire baseline physiological data from users throughout the day, such as heart rate and temperature data. Baseline physiological data, including measured physiological parameters, can include any physiological parameters known in the art, including daytime heart rate data (e.g., heart rate when the user is awake), nighttime heart rate data (e.g., heart rate when the user is asleep), recovery time (e.g., time the user spends in a relaxed state), temperature (e.g., body temperature, skin temperature), respiratory rate, blood oxygen saturation, activity / movement, or any combination thereof. Baseline physiological data can be used to obtain a physiological baseline associated with the user, which provides reference user alertness data. Reference user alertness data can be derived from the baseline physiological data (i.e., actual measurements obtained from the wearable device, such as heart rate, skin temperature, blood oxygen saturation, activity / movement, etc.).

[0049] The user device can receive additional physiological data associated with the user from at least one wearable device. For example, the additional physiological data associated with the user may relate to time periods such as the most recent 24 hours, 48 ​​hours, or 72 hours, or any other applicable time period.

[0050] User devices can obtain current user alertness data, at least in part, based on additional physiological data associated with the user. Current user alertness data can be derived from additional physiological data (i.e., actual measurements taken from wearable devices, such as heart rate, skin temperature, blood oxygen saturation, activity / movement, etc.). This information can then be used when the user initiates a travel event or is about to initiate a travel event in the (near) future.

[0051] User devices can identify triggering conditions, at least in part, based on a comparison between current user alertness data and reference user alertness data. These triggering conditions are used to provide insights into the user's associated physiological state related to a travel event. For example, current user alertness data might indicate that the user has had poor sleep quality over the past three nights. This could result in the current user alertness data being lower than the reference user alertness data, triggering physiological state insights related to the user's travel event.

[0052] User devices can provide physiological state-related insights associated with the user. In one example, the user device itself can provide these insights, for instance, using its graphical user interface. For example, if a trip is a future trip, the user device can instruct the user to eat and / or sleep appropriately before the trip. In another example, the user device can send these physiological state-related insights to, for example, a vehicle (e.g., a car), and the vehicle can take these insights into account when monitoring the user. Therefore, additional information about the user's current alertness data can be provided to the vehicle, which may affect the user's driving performance, and the vehicle's driver monitoring system can take this information into account when monitoring the user.

[0053] For example, due to various reasons (such as lack of sleep, excessive exercise, irregular eating habits, etc.), a user's current physiological state (i.e., user alertness data) may differ from their normal alertness data (i.e., lower or weaker). When a user subsequently begins a travel event or plans to begin a travel event soon, their current alertness data may not be optimal for that event. The solution described in this article incorporates a user's current alertness data during the current travel event or before a future travel event, and provides physiological state-related insights based on this data.

[0054] Some aspects of this disclosure relate to techniques for providing physiological state-related insights associated with a user during a current travel event. For example, when a user device is aware of a user's alertness data prior to the travel event, the user device can instruct the user to rest and / or eat at certain points during the travel event. Some aspects of this disclosure relate to techniques for providing a vehicle with physiological state-related insights associated with a user, enabling the vehicle to determine actions based at least in part on these physiological state-related insights. This achieves a solution where, in addition to driver monitoring data provided by the vehicle itself, the vehicle receives additional information about the user's alertness data from the user device and can incorporate this information into its considerations. Therefore, this disclosure provides a solution for providing a response action (e.g., an instruction or alert message) to the user.

[0055] Some aspects of this disclosure relate to technologies for providing user-related physiological state insights about future travel events. This enables solutions for providing physiological state-related insights even before the start of a travel event, such as providing users with instructions or reminder messages related to future travel events. In other words, this enables solutions for providing proactive actions (e.g., "Take a nap before starting your travel event" or "Have a cup of coffee before starting your travel event") when a user is perceived as overly fatigued.

[0056] Some aspects of this invention relate to techniques for receiving vehicle data related to a user from a vehicle. This data can then be used to provide insights into the user's associated physiological state when triggering conditions are identified. For example, the vehicle can collect various types of sensor data to show the user's behavior while driving. For instance, the vehicle can detect how the user brakes, how long the user has been driving, collect lane-assist data, etc. This achieves a solution where, in addition to using physiological data collected by at least one wearable device, vehicle data can also be effective when triggering conditions are identified to provide insights into the user's associated physiological state.

[0057] Some aspects of this disclosure relate to techniques for providing physiological state-related insights via a graphical user interface of a user device. Additionally or alternatively, physiological state-related insights can be provided through auditory, tactile, and / or visual alerts (e.g., using lights). For example, an auditory or visual alert can instruct a user to rest during a driving event. In some embodiments, such as when the user device is in the user's pocket or when the user is not otherwise paying attention to the user device, tactile and / or visual alerts can be used to draw the user's attention. This achieves a solution where the user device can be used as a means of providing physiological state-related insights to the user.

[0058] The aspects of this disclosure are first described in the context of systems supporting the collection of physiological data from users via wearable devices. These aspects are further illustrated and described with reference to apparatus diagrams, system diagrams, and flowcharts relating to techniques for providing insights into physiological states associated with users.

[0059] Figure 1 An example of a system 100 supporting technologies for providing insights into a user's physiological state, according to various aspects of this disclosure, is shown. System 100 includes multiple electronic devices (e.g., wearable device 104, user device 106) that can be worn and / or operated by one or more users 102. System 100 also includes a network 108 and one or more servers 110.

[0060] Electronic devices may include any electronic devices known in the art, including wearable device 104 (e.g., ring-type wearable device, watch-type wearable device, etc.) and user device 106 (e.g., smartphone, laptop, tablet). Electronic devices associated with a corresponding user 102 may include one or more of the following functions: 1) measuring physiological data; 2) storing the measured data; 3) processing the data; 4) providing output to user 102 based on the processed data (e.g., via a GUI, auditory signals, tactile signals, visual signals); and 5) communicating data with each other and / or with other computing devices. Different electronic devices may perform one or more of these functions.

[0061] Exemplary wearable device 104 may include: wearable computing devices, such as ring computing devices configured to be worn on the finger of user 102 (hereinafter referred to as "ring"); wrist computing devices configured to be worn on the wrist of user 102 (e.g., smartwatches, fitness bands, or bracelets); and / or head-mounted computing devices (e.g., glasses / goggles). Wearable device 104 may also include straps, bands (e.g., flexible or non-flexible straps or bands), adhesive sensors, etc., which may be positioned in other locations, such as around the head (e.g., forehead band), around the arms (e.g., forearm bands and / or biceps bands) and / or around the legs (e.g., thigh or calf bands), behind the ears, under the armpits, etc. Wearable device 104 may also be attached to or contained in clothing. For example, wearable device 104 may be contained in pockets and / or pouches on clothing. As another example, wearable device 104 may be clipped and / or pinned to clothing, or may otherwise be held near user 102. Example items of clothing may include, but are not limited to, hats, shirts, gloves, trousers, socks, outerwear (e.g., jackets), and underwear. In some embodiments, wearable device 104 may be incorporated into other types of equipment, such as training / exercise equipment used during physical activity. For example, wearable device 104 may be attached to or incorporated into a bicycle, skis, tennis racket, golf club, and / or training weights.

[0062] Much of this disclosure can be described in the context of a ring-type wearable device 104. Therefore, the terms "ring 104," "wearable device 104," and similar terms are used interchangeably unless otherwise stated herein. However, the use of the term "ring 104" should not be considered limiting, as it is contemplated that aspects of this disclosure can be implemented using other wearable devices (e.g., watch-type wearable devices, necklace-type wearable devices, bracelet-type wearable devices, earring-type wearable devices, anklet-type wearable devices, etc.).

[0063] In some aspects, user equipment 106 may include handheld mobile computing devices, such as smartphones and tablets. User equipment 106 may also include personal computers, such as laptops and desktops. Other exemplary user equipment 106 may include server computing devices capable of communicating with other electronic devices (e.g., via the Internet). In some embodiments, the computing device may include medical devices, such as external wearable computing devices (e.g., Holter monitors). Medical devices may also include implantable medical devices, such as pacemakers and cardioverter defibrillators. Other exemplary user equipment 106 may include home computing devices, such as Internet of Things (IoT) devices (e.g., IoT devices), smart TVs, smart speakers, smart displays (e.g., video call displays), hubs (e.g., wireless communication hubs), security systems, smart appliances (e.g., thermostats and refrigerators), and fitness equipment.

[0064] Some electronic devices (e.g., wearable device 104, user device 106) can measure physiological parameters of the corresponding user 102, such as photoplethysmography waveforms, continuous skin temperature, pulse waveforms, respiratory rate, heart rate, heart rate variability (HRV), activity plethysmography, skin conductance, pulse oximetry, and / or other physiological parameters. Some electronic devices that measure physiological parameters can also perform some / all of the calculations described herein. Some electronic devices may not measure physiological parameters but can perform some / all of the calculations described herein. For example, a ring (e.g., wearable device 104), a mobile device application, or a server computing device can process received physiological data measured by other devices.

[0065] In some embodiments, user 102 may operate or be associated with multiple electronic devices, some of which can measure physiological parameters and others can process the measured physiological parameters. In some embodiments, user 102 may have a ring (e.g., wearable device 104) for measuring physiological parameters. User 102 may also have or be associated with user device 106 (e.g., a mobile device, smartphone), wherein wearable device 104 and user device 106 are communicatively coupled to each other. In some cases, user device 106 may receive data from wearable device 104 and perform some / all of the calculations described herein. In some embodiments, user device 106 may also measure the physiological parameters described herein, such as motion / activity parameters.

[0066] For example, such as Figure 1As shown, a first user 102-a (user 1) can operate, or be associated with, wearable device 104-a (e.g., ring 104-a) and user device 106-a, as described herein. In this example, user device 106-a associated with user 102-a can process / store physiological parameters measured by ring 104-a. In contrast, a second user 102-b (user 2) can be associated with ring 104-b, watch-wearable device 104-c (e.g., watch 104-c), and user device 106-b, wherein user device 106-b associated with user 102-b can process / store physiological parameters measured by ring 104-b and / or watch 104-c. Furthermore, an nth user 102-n (user N) can be associated with the arrangement of electronic devices described herein (e.g., ring 104-n, user device 106-n). In some respects, wearable devices 104 (e.g., rings 104, watches 104) and other electronic devices can be communicatively coupled to user equipment 106 of the corresponding user 102 via Bluetooth, Wi-Fi and other wireless protocols.

[0067] In some implementations, the ring 104 of system 100 (e.g., wearable device 104) can be configured to collect physiological data from a corresponding user 102 based on arterial blood flow within the user's finger. Specifically, the ring 104 can utilize one or more light-emitting components, such as LEDs (e.g., red LEDs, green LEDs) that emit light on the palm side of the user's finger, to collect physiological data based on arterial blood flow within the user's finger. Generally, terms such as light-emitting component, light-emitting element, etc., may include, but are not limited to, LEDs, micro LEDs, mini LEDs, laser diodes (LDs), etc.

[0068] In some cases, system 100 may be configured to collect physiological data from the corresponding user 102 based on blood flow diffusing into the skin's microvascular bed, which has capillaries and arterioles. For example, system 100 may collect PPG data based on measurements of blood volume diffusing into the microvascular system of capillaries and arterioles. In some embodiments, ring 104 may use a combination of green and red LEDs to acquire physiological data. Physiological data may include any physiological data known in the art, including but not limited to temperature data, accelerometer data (e.g., movement / exercise data), heart rate data, HRV data, blood oxygen level data, or any combination thereof.

[0069] Using green and red LEDs offers several advantages over other solutions, as they have been found to possess unique strengths in acquiring physiological data under different conditions (e.g., bright / dark, active / restless) and through different parts of the body. For example, green LEDs have been found to perform better during exercise. Furthermore, it has been found that using multiple LEDs (e.g., green and red LEDs) distributed around the ring 104 exhibits better performance than wearable devices that use LEDs placed close together (e.g., within a watch-type wearable device). Additionally, blood vessels in the fingers (e.g., arteries, capillaries) are more easily accessible via LEDs than those in the wrist. Specifically, arteries in the wrist are located at the base of the wrist (e.g., the palm side of the wrist), meaning that only capillaries at the top of the wrist (e.g., the back side of the wrist) are accessible, where watch-type wearable devices and similar devices are typically worn. Thus, it has been found that using LEDs and other sensors within the ring 104 exhibits superior performance compared to wearable devices worn on the wrist, because the ring 104 has better access to arteries (compared to capillaries), resulting in stronger signals and more valuable physiological data.

[0070] Electronic devices in system 100 (e.g., user equipment 106, wearable device 104) can be communicatively coupled to one or more servers 110 via wired or wireless communication protocols. For example, such as Figure 1 As shown, an electronic device (e.g., user device 106) may be communicatively coupled to one or more servers 110 via network 108. Network 108 may implement a transmit control protocol and Internet Protocol (TCP / IP), such as the Internet, or may implement other network 108 protocols. The network connection between network 108 and the corresponding electronic device may facilitate the transmission of data via email, websites, text messages, mail, or any other suitable form of interaction within computer network 108. For example, in some embodiments, a ring 104-a associated with a first user 102-a may be communicatively coupled to user device 106-a, wherein user device 106-a is communicatively coupled to server 110 via network 108. In additional or alternative cases, wearable device 104 (e.g., ring 104, watch 104) may be directly communicatively coupled to network 108.

[0071] System 100 can provide on-demand database services between user equipment 106 and one or more servers 110. In some cases, server 110 can receive data from user equipment 106 via network 108 and can store and analyze the data. Similarly, server 110 can provide data to user equipment 106 via network 108. In some cases, server 110 may be located in one or more data centers. Server 110 can be used for data storage, management, and processing. In some implementations, server 110 can provide a website-based interface to user equipment 106 via a web browser.

[0072] In some respects, system 100 can detect the sleep periods of user 102 and classify the sleep periods of user 102 into one or more sleep stages (e.g., sleep stage classification). For example, as Figure 1 As shown, user 102-a can be associated with wearable device 104-a (e.g., ring 104-a) and user device 106-a. In this example, ring 104-a can collect physiological data associated with user 102-a, including temperature, heart rate, HRV, respiratory rate, etc. In some aspects, the data collected by ring 104-a can be fed into a machine learning classifier, which is configured to determine the period of sleep that user 102-a is currently (or has been) sleeping. Furthermore, the machine learning classifier can be configured to classify the period into different sleep stages, including wakefulness sleep, rapid eye movement (REM) sleep, light sleep (non-REM (NREM)), and deep sleep (NREM). In some aspects, the classified sleep stages can be displayed to user 102-a via the GUI of user device 106-a. The sleep stage classification can be used to provide user 102-a with feedback on the user's sleep patterns, such as recommended bedtime, recommended wake-up time, etc. Furthermore, in some embodiments, the sleep stage classification techniques described herein can be used to calculate scores for the corresponding user, such as sleep scores, readiness scores, etc. Additionally, system 100 can detect, at least in part, whether user 102-a (user 1) has begun to transition to a sleep state (e.g., deep sleep) within a set of sleep states (e.g., awake sleep, REM sleep, NREM sleep). Any component of system 100 (including wearable device 104-a, user device 106-a associated with user 102-a (user 1), any combination of one or more servers 110 or above) can detect, at least in part, whether user 102-a (user 1) has begun to transition to a sleep state (e.g., deep sleep) within a set of sleep states based on the collected physiological data.

[0073] In some respects, system 100 can leverage circadian rhythm derivation features to further improve physiological data acquisition, data processing procedures, and other techniques described herein. The term circadian rhythm can refer to the natural, internal process that regulates an individual's sleep-wake cycle, repeating approximately every 24 hours. In this regard, the techniques described herein can utilize circadian rhythm regulation models to improve physiological data acquisition, analysis, and data processing. For example, the circadian rhythm regulation model can be fed into a machine learning classifier along with physiological data acquired from user 102-a via wearable device 104-a. In this example, the circadian rhythm regulation model can be configured to “weight” or regulate physiological data acquired during the user's natural, approximately 24-hour circadian rhythm. In some implementations, the system can initially start with a “baseline” circadian rhythm regulation model and can modify the baseline model using physiological data acquired from each user 102 to generate a customized, personalized circadian rhythm regulation model for each respective user 102.

[0074] In some respects, System 100 can leverage other circadian rhythms to further improve the acquisition, analysis, and processing of physiological data for phases of these other rhythms. For example, if a weekly rhythm is detected in an individual's baseline data, the model can be configured to adjust the "weights" of the data according to a particular day of the week. Circadian rhythms that may require adjustment of the model in this way include: 1) superdial rhythms (rhythms faster than a day, including sleep cycles during sleep and periodic fluctuations in physiological variables measured in the waking state ranging from less than an hour to several hours; 2) diurnal rhythms; 3) non-endogenous diurnal rhythms, which appear as imposed on diurnal rhythms (such as in a work schedule); 4) weekly rhythms, or other exogenously imposed artificial time cycles (e.g., a 12-day rhythm could be used in a hypothetical culture with a 12-day "week"); 5) polydiurnal ovarian rhythms in women and spermatogenesis rhythms in men; 6) monthly rhythms (associated with individuals living in environments with low or no artificial light); and 7) seasonal rhythms.

[0075] Biorhythms are not always stable. For example, the length of an ovarian cycle varies across multiple weeks in many women, and even for the same user, superluminal rhythms do not occur at exactly the same time or in the same cycle over multiple days. Thus, signal processing techniques sufficient to quantify frequency components while maintaining the temporal resolution of these rhythms in physiological data can be used to improve the detection of these rhythms, assigning phases of each rhythm to each moment of the measured time, thereby modifying the regulation model and comparisons of time intervals. Biorhythm regulation models and parameters can be appropriately added in linear or nonlinear combinations to more accurately capture the dynamic physiological baseline of an individual or a group of individuals.

[0076] Those skilled in the art will understand that one or more aspects of this disclosure may be implemented in system 100 to additionally or alternatively address other problems besides those described above. Furthermore, aspects of this disclosure may provide technical improvements to the "conventional" systems or processes described herein. However, the specification and drawings only include exemplary technical improvements resulting from implementing aspects of this disclosure and therefore do not represent all technical improvements provided within the scope of the claims.

[0077] Figure 2 An example of a system 200 supporting techniques for providing insights related to a user's physiological state, according to various aspects of this disclosure, is shown. System 200 may implement system 100 or be implemented by system 100. Specifically, system 200 is shown as referenced... Figure 1 Examples of the ring 104 (e.g., wearable device 104), user device 106, and server 110.

[0078] In some aspects, the ring 104 can be configured to be worn around a user's finger, and when worn around a user's finger, one or more user physiological parameters can be determined. Exemplary measurement results and determination results may include, but are not limited to, user skin temperature, pulse waveform, respiratory rate, heart rate, HRV, blood oxygen level, etc.

[0079] System 200 also includes a user device 106 (e.g., a smartphone) that communicates with ring 104. For example, ring 104 may communicate wirelessly and / or wiredly with user device 106. In some embodiments, ring 104 may send measurement and processing data (e.g., temperature data, photoplethysmography (PPG) data, motion / accelerometer data, ring input data, etc.) to user device 106. User device 106 may also send data to ring 104, such as ring 104 firmware / configuration updates. User device 106 may process the data. In some embodiments, user device 106 may send data to server 110 for processing and / or storage.

[0080] Ring 104 may include a housing 205, which may include an inner housing 205-a and an outer housing 205-b. In some aspects, the housing 205 of ring 104 may store or otherwise include various components of the ring, including but not limited to device electronics, power sources (e.g., battery 210 and / or capacitors), one or more substrates (e.g., printed circuit boards) interconnecting the device electronics and / or power sources, etc. Device electronics may include device modules (e.g., hardware / software), such as: processing module 230-a, memory 215, communication module 220-a, power module 225, etc. Device electronics may also include one or more sensors. Exemplary sensors may include one or more temperature sensors 240, PPG sensor assemblies (e.g., PPG system 235), and one or more motion sensors 245.

[0081] The sensor may include associated modules (not shown) configured to communicate with corresponding components / modules of ring 104 and generate signals associated with the corresponding sensor. In some aspects, each component / module of ring 104 may be communicatively coupled to each other via a wired or wireless connection. Furthermore, ring 104 may include additional and / or alternative sensors or other components configured to collect physiological data from the user, such as light sensors (e.g., LEDs), pulse oximeters, etc.

[0082] refer to Figure 2 The ring 104 shown and described is for illustrative purposes only. Thus, the ring 104 may include, for example... Figure 2 The additional or alternative components shown. Other rings 104 that provide the functionality described herein can be manufactured. For example, rings 104 with fewer components (e.g., sensors) can be manufactured. In a particular example, a ring 104 can be manufactured having a single temperature sensor 240 (or other sensor), a power supply, and device electronics configured to read the single temperature sensor 240 (or other sensor). In another specific example, the temperature sensor 240 (or other sensor) can be attached to a user's finger (e.g., using a clip, spring clip, etc.). In this case, the sensor can be wired to another computing device, such as a wrist-worn computing device that reads the temperature sensor 240 (or other sensor). In other examples, rings 104 can be manufactured that include additional sensors and processing functionality.

[0083] Housing 205 may include one or more housing 205 components. Housing 205 may include an outer shell 205-b component (e.g., a housing) and an inner shell 205-a component (e.g., a molded part). Housing 205 may include Figure 2Additional components not explicitly shown (e.g., additional layers). For example, in some embodiments, ring 104 may include one or more insulating layers that electrically insulate device electronics and other conductive materials (e.g., electrical traces) from housing 205-b (e.g., metal housing 205-b). Housing 205 may provide structural support for device electronics, battery 210, substrate, and other components. For example, housing 205 may protect device electronics, battery 210, and substrate from mechanical forces such as pressure and impact. Housing 205 may also protect device electronics, battery 210, and substrate from water and / or other chemicals.

[0084] The housing 205-b may be made of one or more materials. In some embodiments, the housing 205-b may include a metal (e.g., titanium), which can provide strength and abrasion resistance at a relatively light weight. The housing 205-b may also be made of other materials (e.g., polymers). In some embodiments, the housing 205-b may be both protective and decorative.

[0085] The inner shell 205-a can be configured to mate with a user's finger. The inner shell 205-a can be formed of a polymer (e.g., a medical-grade polymer) or other materials. In some embodiments, the inner shell 205-a can be transparent. For example, the inner shell 205-a can be transparent to light emitted by a PPG light-emitting diode (LED). In some embodiments, the inner shell 205-a component can be molded onto the outer shell 205-b. For example, the inner shell 205-a can include a polymer molded (e.g., injection molded) to fit into the metal shell of the outer shell 205-b.

[0086] Ring 104 may include one or more substrates (not shown). Device electronics and battery 210 may be included on one or more substrates. For example, device electronics and battery 210 may be mounted on one or more substrates. Exemplary substrates may include one or more printed circuit boards (PCBs), such as flexible PCBs (e.g., polyimide). In some embodiments, electronics / battery 210 may include surface mount devices (e.g., surface mount technology (SMT) devices) on a flexible PCB. In some embodiments, one or more substrates (e.g., one or more flexible PCBs) may include electrical traces providing electrical communication between device electronics. Electrical traces may also connect battery 210 to device electronics.

[0087] The device electronics, battery 210, and substrate can be arranged in a variety of ways within the ring 104. In some embodiments, a substrate including the device electronics may be mounted along the bottom (e.g., the lower half) of the ring 104, such that sensors (e.g., PPG system 235, temperature sensor 240, motion sensor 245, and other sensors) are positioned against the underside of the user's finger. In these embodiments, the battery 210 may be included along the top of the ring 104 (e.g., on another substrate).

[0088] The various components / modules of ring 104 may include functions (e.g., circuits and other components) within ring 104. A module may include any discrete and / or integrated electronic circuit components that implement analog and / or digital circuitry capable of generating the functions attributed to the module herein. For example, a module may include analog circuitry (e.g., amplifier circuitry, filter circuitry, analog-to-digital converter circuitry, and / or other signal conditioning circuitry). These modules may also include digital circuitry (e.g., combinational or sequential logic circuitry, memory circuitry, etc.).

[0089] The memory 215 (storage module) of ring 104 may include any volatile, non-volatile, magnetic, or electrical dielectric, such as random access memory (RAM), read-only memory (ROM), non-volatile RAM (NVRAM), electrically erasable programmable ROM (EEPROM), flash memory, or any other storage device. Memory 215 may store any data described herein. For example, memory 215 may be configured to store data acquired by the corresponding sensors and PPG system 235 (e.g., motion data, temperature data, PPG data). Furthermore, memory 215 may include instructions that, when executed by one or more processing circuits, cause the module to perform various functions belonging to the modules herein. The device electronics of ring 104 described herein are merely exemplary device electronics. Thus, the type of electronic components used to implement the device electronics may vary based on design considerations.

[0090] The functionality of the Ring 104 module described herein can be embodied in one or more processors, hardware, firmware, software, or any combination thereof. Describing different features as modules is to highlight different functional aspects and does not necessarily mean that these modules must be implemented by separate hardware / software components. Rather, the functionality associated with one or more modules can be performed by separate hardware / software components or integrated within common hardware / software components.

[0091] The processing module 230-a of ring 104 may include one or more processors (e.g., processing units), microcontrollers, digital signal processors, system-on-a-chip (SoC), and / or other processing devices. The processing module 230-a communicates with modules included in ring 104. For example, the processing module 230-a may send / receive data to / from modules and other components (e.g., sensors) of ring 104. As described herein, these modules can be implemented by various circuit components. Therefore, a module may also be referred to as a circuit (e.g., communication circuitry and power supply circuitry).

[0092] Processing module 230-a can communicate with memory 215. Memory 215 may include computer-readable instructions that, when executed by processing module 230-a, cause processing module 230-a to perform various functions belonging to processing module 230-a herein. In some embodiments, processing module 230-a (e.g., a microcontroller) may include additional features associated with other modules, such as communication functionality provided by communication module 220-a (e.g., an integrated Bluetooth Low Energy transceiver) and / or additional onboard memory 215.

[0093] Communication module 220-a may include circuitry providing wireless and / or wired communication with user equipment 106 (e.g., communication module 220-b of user equipment 106). In some embodiments, communication modules 220-a and 220-b may include wireless communication circuitry, such as Bluetooth and / or Wi-Fi circuitry. In some embodiments, communication modules 220-a and 220-b may include wired communication circuitry, such as Universal Serial Bus (USB) communication circuitry. Using communication module 220-a, ring 104 and user equipment 106 can be configured to communicate with each other. The ring's processing module 230-a may be configured to send / receive data to / from user equipment 106 via communication module 220-a. Exemplary data may include, but is not limited to, motion data, temperature data, pulse waveform, heart rate data, HRV data, PPG data, and status updates (e.g., charging status, battery level, and / or configuration settings of ring 104). The ring's processing module 230-a can also be configured to receive updates (e.g., software / firmware updates) and data from the user equipment 106.

[0094] Ring 104 may include a battery 210 (e.g., a rechargeable battery 210). Exemplary battery 210 may include a lithium-ion or lithium-polymer type battery 210, although various battery 210 options are possible. Battery 210 may be wirelessly charged. In some embodiments, ring 104 may include a power source other than battery 210, such as a capacitor. The power source (e.g., battery 210 or capacitor) may have a curved geometry that matches the curve of ring 104. In some aspects, the charger or other power source may include additional sensors that can be used to acquire data in addition to or supplement the data acquired by ring 104 itself. Furthermore, the charger or other power source for ring 104 may serve as user equipment 106, in which case the charger or other power source for ring 104 may be configured to receive data from ring 104, store and / or process data received from ring 104, and communicate data between ring 104 and server 110.

[0095] In some aspects, ring 104 includes a power module 225 that controls the charging of battery 210. For example, power module 225 may interface with an external wireless charger that charges battery 210 when interfaced with ring 104. The charger may include a reference structure that matches a reference structure of ring 104 to form a specific orientation with ring 104 during charging. Power module 225 may also regulate the voltage of device electronics, regulate the power output to device electronics, and monitor the state of charge of battery 210. In some embodiments, battery 210 may include a protection circuit module (PCM) that protects battery 210 from high-current discharge, overvoltage during charging, and undervoltage during discharging. Power module 225 may also include electrostatic discharge (ESD) protection.

[0096] One or more temperature sensors 240 may be electrically coupled to processing module 230-a. Temperature sensors 240 may be configured to generate temperature signals (e.g., temperature data) indicating the temperature read or sensed by the temperature sensor 240. Processing module 230-a may determine the user's temperature at the location of the temperature sensor 240. For example, in ring 104, the temperature data generated by the temperature sensor 240 may indicate the user's temperature at the finger (e.g., skin temperature). In some embodiments, the temperature sensor 240 may contact the user's skin. In other embodiments, a portion of housing 205 (e.g., inner housing 205-a) may form a barrier (e.g., a thin thermally conductive barrier) between the temperature sensor 240 and the user's skin. In some embodiments, the portion of ring 104 configured to contact the user's finger may have a thermally conductive portion and a thermally insulating portion. The thermally conductive portion may conduct heat from the user's finger to the temperature sensor 240. The thermally insulating portion may isolate multiple portions of ring 104 (e.g., temperature sensor 240) from the ambient temperature.

[0097] In some implementations, temperature sensor 240 may generate a digital signal (e.g., temperature data), which processing module 230-a can use to determine the temperature. As another example, if temperature sensor 240 includes a passive sensor, processing module 230-a (or temperature sensor 240 module) may measure the current / voltage generated by temperature sensor 240 and determine the temperature based on the measured current / voltage. Exemplary temperature sensor 240 may include a thermistor, such as a negative temperature coefficient (NTC) thermistor, or other types of sensors including resistors, transistors, diodes, and / or other electrical / electronic components.

[0098] Processing module 230-a can sample the user's temperature over time. For example, processing module 230-a can sample the user's temperature according to a sampling rate. Exemplary sampling rates may include one sample per second, although processing module 230-a may be configured to sample the temperature signal at other sampling rates higher or lower than one sample per second. In some embodiments, processing module 230-a can sample the user's temperature continuously day and night. Sampling at a sufficient rate throughout the day (e.g., one sample per second) can provide sufficient temperature data for the analysis described herein.

[0099] Processing module 230-a can store the sampled temperature data in memory 215. In some embodiments, processing module 230-a can process the sampled temperature data. For example, processing module 230-a can determine the average temperature value over a period of time. In one example, processing module 230-a can determine the average temperature value per minute by summing all temperature values ​​collected within one minute and dividing by the number of samples within one minute. In a specific example where the temperature is sampled at one sample per second, the average temperature can be the sum of all sampled temperatures within one minute divided by sixty seconds. Memory 215 can store the average temperature value over a period of time. In some embodiments, memory 215 can store the average temperature (e.g., one per minute) instead of the sampled temperatures to save memory 215.

[0100] The sampling rate, which can be stored in memory 215, is configurable. In some embodiments, the sampling rate can be the same during the day and night. In other embodiments, the sampling rate can vary throughout the day / night. In some embodiments, ring 104 can filter / reject temperature readings, such as large temperature spikes that do not indicate physiological changes (e.g., temperature spikes from a hot shower). In some embodiments, ring 104 can filter / reject temperature readings that are unreliable due to other factors, such as excessive exercise during exercise (e.g., indicated by motion sensor 245).

[0101] Ring 104 (e.g., a communication module) can transmit sampled and / or averaged temperature data to user equipment 106 for storage and / or further processing. User equipment 106 can transmit sampled and / or averaged temperature data to server 110 for storage and / or further processing.

[0102] Although ring 104 is illustrated as including a single temperature sensor 240, ring 104 may include multiple temperature sensors 240 located at one or more locations, such as along the inner casing 205-a close to the user's finger. In some embodiments, the temperature sensor 240 may be a stand-alone temperature sensor 240. Additionally or alternatively, one or more temperature sensors 240 may be included with other components (e.g., packaged with other components), such as with an accelerometer and / or a processor.

[0103] Processing module 230-a can acquire and process data from multiple temperature sensors 240 in a manner similar to that described with respect to a single temperature sensor 240. For example, processing module 230 can individually sample, average, and store temperature data from each of the multiple temperature sensors 240. In other examples, processing module 230-a can sample the sensors at different rates and average / store different values ​​from different sensors. In some embodiments, processing module 230-a can be configured to determine a single temperature based on the average of two or more temperatures determined by two or more temperature sensors 240 at different locations on the finger.

[0104] Temperature sensors 240 on ring 104 can acquire the distal temperature of a user's finger (e.g., any finger). For example, one or more temperature sensors 240 on ring 104 can acquire the user's temperature from different locations on the underside of the finger or on the finger. In some embodiments, ring 104 can continuously acquire distal temperatures (e.g., at a sampling rate). While this document describes distal temperatures measured by ring 104 at a finger, other devices can measure temperatures at the same / different locations. In some cases, the distal temperature measured at a user's finger may differ from the temperature measured at the user's wrist or other external body locations. Furthermore, the distal temperature measured at a user's finger (e.g., "surface" temperature) may differ from the user's core temperature. Thus, ring 104 can provide useful temperature signals that cannot be acquired at other internal / external locations of the body. In some cases, continuous temperature measurements at the finger can capture temperature fluctuations (e.g., small or large fluctuations) that may not be apparent in the core temperature. For example, continuous temperature measurements at the finger can capture temperature fluctuations per minute or hour that provide additional insights that may not be provided by other temperature measurements elsewhere on the body.

[0105] Ring 104 may include a PPG system 235. The PPG system 235 may include one or more light emitters that emit light. The PPG system 235 may also include one or more light receivers that receive the light emitted by the one or more light emitters. The light receivers may generate a signal (hereinafter referred to as a "PPG" signal) indicating the amount of light received by the light receivers. The light emitters may illuminate an area of ​​the user's finger. The PPG signal generated by the PPG system 235 may indicate blood perfusion in the illuminated area. For example, the PPG signal may indicate changes in blood volume in the illuminated area caused by the user's pulse pressure. Processing module 230-a may sample the PPG signal and determine the user's pulse waveform based on the PPG signal. Processing module 230-a may determine various physiological parameters based on the user's pulse waveform, such as the user's respiratory rate, heart rate, HRV, oxygen saturation, and other circulatory parameters.

[0106] In some embodiments, the PPG system 235 may be configured as a reflective PPG system 235, wherein the optical receiver receives propagated light reflected through the area of ​​the user's finger. In some embodiments, the PPG system 235 may be configured as a transmissive PPG system 235, wherein the light emitter and the light receiver are arranged opposite each other such that light is sent directly to the light receiver through a portion of the user's finger.

[0107] The number and ratio of transmitters and receivers included in the PPG system 235 may vary. An exemplary light transmitter may include a light-emitting diode (LED). The light transmitter may emit light of the infrared spectrum and / or other spectra. An exemplary optical receiver may include, but is not limited to, a photoelectric sensor, a phototransistor, and a photodiode. The optical receiver may be configured to generate a PPG signal in response to a wavelength received from the light transmitter. The locations of the transmitters and receivers may vary. Additionally, a single device may include a reflective and / or transmissive PPG system 235.

[0108] In some implementations... Figure 2 The illustrated PPG system 235 may include a reflective PPG system 235. In these embodiments, the PPG system 235 may include a centrally located light receiver (e.g., at the bottom of ring 104) and two light emitters located on either side of the light receiver. In this embodiment, the PPG system 235 (e.g., the light receiver) may generate a PPG signal based on light received from one or both light emitters. In other embodiments, other placements, combinations, and / or configurations of one or more light emitters and / or light receivers are contemplated.

[0109] Processing module 230-a can control one or two optical emitters to emit light while simultaneously sampling the PPG signal generated by the optical receiver. In some embodiments, processing module 230-a can cause an optical emitter with a stronger received signal to emit light while simultaneously sampling the PPG signal generated by the optical receiver. For example, when sampling the PPG signal at a sampling rate (e.g., 250 Hz), the selected optical emitter can emit light continuously.

[0110] Sampling the PPG signal generated by the PPG system 235 may generate a pulse waveform referred to as "PPG". The pulse waveform can indicate the relationship between blood pressure and time over multiple cardiac cycles. The pulse waveform may include peak values ​​indicating cardiac cycles. Furthermore, the pulse waveform may include respiratory-induced changes that can be used to determine respiratory rate. In some embodiments, the processing module 230-a may store the pulse waveform in memory 215. The processing module 230-a may process the pulse waveform during and / or from memory 215 to determine the user's physiological parameters described herein.

[0111] Processing module 230-a can determine a user's heart rate based on a pulse waveform. For example, processing module 230-a can determine the heart rate (e.g., in heartbeats per minute) based on the time between peaks in the pulse waveform. The time between peaks can be referred to as the interbeat interval (IBI). Processing module 230-a can store the determined heart rate value and IBI value in memory 215.

[0112] Processing module 230-a can determine HRV over time. For example, processing module 230-a can determine HRV based on changes in IBI. Processing module 230-a can store the time-varying HRV value in memory 215. Furthermore, processing module 230-a can determine the user's respiratory rate over time. For example, processing module 230-a can determine the respiratory rate based on frequency modulation, amplitude modulation, or baseline modulation of the user's IBI value over a period of time. The respiratory rate can be calculated as breaths per minute or another respiratory rate (e.g., breaths per 30 seconds). Processing module 230-a can store the time-varying user respiratory rate value in memory 215.

[0113] Ring 104 may include one or more motion sensors 245, such as one or more accelerometers (e.g., 6-D accelerometers) and / or one or more gyroscopes. Motion sensors 245 may generate motion signals indicating sensor motion. For example, ring 104 may include one or more accelerometers that generate acceleration signals indicating the acceleration of the accelerometers. As another example, ring 104 may include one or more gyroscope sensors that generate gyroscope signals indicating angular motion (e.g., angular velocity) and / or orientation changes. Motion sensors 245 may be included in one or more sensor packages. An example of an accelerometer / gyroscope sensor is the Bosch BM1160 inertial microelectromechanical system (MEMS) sensor, which can measure angular rate and acceleration on three vertical axes.

[0114] Processing module 230-a can sample the motion signal at a sampling rate (e.g., 50 Hz) and determine the motion of ring 104 based on the sampled motion signal. For example, processing module 230-a can sample an acceleration signal to determine the acceleration of ring 104. As another example, processing module 230-a can sample a gyroscope signal to determine angular motion. In some embodiments, processing module 230-a can store motion data in memory 215. The motion data may include sampled motion data and motion data calculated based on the sampled motion signal (e.g., acceleration and angle values).

[0115] Ring 104 can store various types of data described herein. For example, ring 104 can store temperature data, such as raw sampled temperature data and calculated temperature data (e.g., average temperature). As another example, ring 104 can store PPG signal data, such as pulse waveforms and data calculated based on pulse waveforms (e.g., heart rate values, IBI values, HRV values, and respiratory rate values). Ring 104 can also store motion data, such as sampled motion data indicating linear and angular motion.

[0116] The ring 104 or other computing device can calculate and store additional values ​​based on the sampled / calculated physiological data. For example, the processing module 230 can calculate and store various metrics, such as sleep metrics (e.g., sleep score), activity metrics, and readiness metrics. In some embodiments, the additional values / metrics may be referred to as “derived values.” The ring 104 or other computing / wearable device can calculate various values / metrics related to movement. Exemplary derived values ​​of movement data may include, but are not limited to, movement count values, regularity values, intensity values, task metabolic equivalent (MET) values, and orientation values. Movement counts, regularity values, intensity values, and MET values ​​can indicate the amount of user movement (e.g., speed / acceleration) over a period of time. Orientation values ​​can indicate the orientation of the ring 104 on the user's finger and whether the ring 104 is worn on the left or right hand.

[0117] In some implementations, motion counts and regularity values ​​can be determined by counting the number of acceleration peaks within one or more time periods (e.g., one or more time periods of 30 seconds to 1 minute). Intensity values ​​can indicate the number of motions and the associated intensity of the motion (e.g., acceleration value). Intensity values ​​can be categorized as low, medium, and high based on the associated threshold acceleration value. MET can be determined based on the motion intensity over a period of time (e.g., 30 seconds), the regularity / irregularity of the motion, and the number of motions associated with different intensities.

[0118] In some implementations, processing module 230-a may compress data stored in memory 215. For example, processing module 230-a may delete sampled data after performing calculations based on the sampled data. As another example, processing module 230-a may average the data over a longer period to reduce the number of stored values. In a particular example, if the user's average temperature over one minute is stored in memory 215, processing module 230-a may calculate and store the average temperature over a five-minute period, and then erase the one-minute average temperature data. Processing module 230-a may compress data based on various factors, such as the total amount of used / available memory 215 and / or the time elapsed since ring 104 last sent data to user equipment 106.

[0119] While a user's physiological parameters can be measured by sensors included on ring 104, other devices can also measure these parameters. For example, although a user's temperature can be measured by temperature sensor 240 included in ring 104, other devices can also measure it. In some examples, other wearable devices (e.g., wrist-worn devices) may include sensors for measuring a user's physiological parameters. Furthermore, medical devices, such as external medical devices (e.g., wearable medical devices) and / or implantable medical devices, can measure a user's physiological parameters. One or more sensors on any type of computing device can be used to implement the techniques described herein.

[0120] Physiological measurements can be performed continuously throughout the day and / or night. In some embodiments, physiological measurements can be performed during a portion of the day and / or a portion of the night. In some embodiments, physiological measurements can be performed in response to determining that the user is in a specific state (e.g., an active state, a resting state, and / or a sleeping state). For example, ring 104 can perform physiological measurements in a resting / sleeping state to obtain purer physiological signals. In one example, ring 104 or other devices / systems can detect when the user is resting and / or sleeping and obtain physiological parameters (e.g., temperature) of that detected state. When the user is in other states, the device / system can use the resting / sleeping physiological data and / or other data to implement the techniques of this disclosure.

[0121] In some implementations, as previously described, ring 104 may be configured to acquire, store, and / or process data, and may transmit any data described herein to user device 106 for storage and / or processing. In some aspects, user device 106 includes wearable application 250, operating system (OS), web browser application (e.g., web browser 280), one or more additional applications, and GUI 275. User device 106 may also include other modules and components, including sensors, audio devices, haptic feedback devices, etc. Wearable application 250 may include examples of applications (e.g., “apps”) that can be installed on user device 106. Wearable application 250 may be configured to acquire data from ring 104, store the acquired data, and process the acquired data as described herein. For example, wearable application 250 may include user interface (UI) module 255, acquisition module 260, processing module 230-b, communication module 220-b, and storage module (e.g., database 265) configured to store application data.

[0122] The various data processing operations described herein can be performed by ring 104, user device 106, server 110, or any combination thereof. For example, in some cases, data collected by ring 104 can be preprocessed and sent to user device 106. In this example, user device 106 can perform some data processing operations on the received data, send the data to server 110 for data processing, or both. For example, in some cases, user device 106 can perform processing operations requiring relatively low processing power and / or operations requiring relatively low latency, while user device 106 can send data to server 110 for processing operations requiring relatively high processing power and / or operations that allow relatively high latency.

[0123] In some aspects, the ring 104, user device 106, and server 110 of system 200 can be configured to assess a user's sleep patterns. Specifically, corresponding components of system 200 can be used to collect data from the user via ring 104 and generate one or more scores (e.g., sleep score, readiness score) for the user based on the collected data. For example, as previously described, the ring 104 of system 200 can be worn by the user to collect data from the user, including temperature, heart rate, HRV, etc. The data collected by ring 104 can be used to determine when the user sleeps in order to assess the user's sleep on a given "sleep day". In some aspects, a score can be calculated for each corresponding sleep day, such that a first sleep day is associated with a first set of scores, and a second sleep day is associated with a second set of scores. The score can be calculated for each corresponding sleep day based on data collected by ring 104 during each sleep day. The scores can include, but are not limited to, sleep scores, readiness scores, etc.

[0124] In some cases, a "sleep day" may coincide with a traditional calendar day, meaning a given sleep day extends from midnight to midnight of the corresponding calendar day. In other cases, the sleep day may be offset relative to the calendar day. For example, a sleep day can extend from 6:00 PM (6:00 PM) of one calendar day to 6:00 PM (6:00 PM) of the next calendar day. In this example, 6:00 PM can serve as the "cutoff time," where data collected from the user before 6:00 PM is counted as the current sleep day, and data collected from the user after 6:00 PM is counted as the next sleep day. Since most people sleep the most at night, offsetting the sleep day relative to the calendar day allows System 200 to assess the user's sleep patterns in a manner consistent with the user's sleep schedule. In some cases, the user can selectively adjust (e.g., via the GUI) the timing of the sleep day relative to the calendar day so that the sleep day aligns with the duration of the user's typical sleep.

[0125] In some implementations, a user's overall score for each day (e.g., sleep score, readiness score) can be determined / calculated based on one or more "influencing factors," "factors," or "impact factors." For example, a user's overall sleep score can be calculated based on a set of influencing factors, including: total sleep time, efficiency, stability, REM sleep, deep sleep, sleep latency, timing, or any combination thereof. A sleep score can include any number of influencing factors. The "total sleep time" influencing factor can refer to the sum of all sleep periods on a sleep day. The "efficiency" influencing factor can reflect the percentage of time spent sleeping compared to time spent awake in bed, and can be calculated using the average efficiency of the long sleep periods (e.g., primary sleep periods) on a sleep day, weighted by the duration of each sleep period. The "stability" influencing factor can indicate the stability of a user's sleep and can be calculated using the average of all sleep periods on a sleep day (weighted by the duration of each period). Stability factors can be based on “wake-up counts” (e.g., the sum of all wake-ups detected during different sleep periods when the user wakes up), excessive movement, and “get-out counts” (e.g., the sum of all get-outs detected during different sleep periods when the user gets out of bed).

[0126] The "REM sleep" influencing factor can refer to the sum of REM sleep durations across all sleep periods on a sleep day, including REM sleep. Similarly, the "deep sleep" influencing factor can refer to the sum of deep sleep durations across all sleep periods on a sleep day, including deep sleep. The "sleep latency" influencing factor can represent how long it takes for a user to fall asleep (e.g., average, average, longest), and can be calculated using the average of long sleep periods throughout the sleep day, weighted by the duration of each period and the number of such periods (e.g., a given sleep stage or a combination of multiple sleep stages can be its own influencing factor or a weighted factor for other influencing factors). Finally, the "timing" influencing factor can refer to the relative timing of sleep periods within a sleep day and / or calendar day, and can be calculated using the average of all sleep periods on a sleep day (weighted by the duration of each period).

[0127] As another example, a user's overall readiness score can be calculated based on a set of influencing factors, including: sleep, sleep balance, heart rate, HRV balance, recovery index, temperature, activity, activity balance, or any combination thereof. The readiness score can include any number of influencing factors. The "sleep" influencing factor can refer to the combined sleep score of all sleep periods within a sleep day. The "sleep balance" influencing factor can refer to the cumulative duration of all sleep periods within a sleep day. Specifically, sleep balance can indicate to a user whether the sleep a user has received over a period of time (e.g., the past two weeks) is in line with the user's needs. Generally, adults need 7–9 hours of sleep per night to maintain health, alertness, and optimal mental and physical well-being. However, occasional poor sleep is normal, so the sleep balance influencing factor takes into account long-term sleep patterns to determine whether each user's sleep needs are being met. The "resting heart rate" influencing factor can indicate the lowest heart rate from the longest sleep period (e.g., the main sleep period) and / or the lowest heart rate from a nap following the main sleep period.

[0128] Continuing with reference to the "Factors" (e.g., factors, influence factors) of the readiness score, the "HRV Balance" factor can indicate the average highest HRV from the primary sleep period and naps occurring after the primary sleep period. The HRV Balance factor can help users track their recovery status by comparing their HRV trend over a first period (e.g., two weeks) with the average HRV over a longer second period (e.g., three months). The "Recovery Index" factor can be calculated based on the longest sleep period. The Recovery Index measures the time required for a user's resting heart rate to stabilize during the night. A sign of excellent recovery is that the user's resting heart rate stabilizes in the first half of the night (at least six hours before the user wakes up), allowing time for the body to recover the next day. If the user's highest temperature during a nap is at least 0.5°C higher than the highest temperature during the longest sleep period, the "Body Temperature" factor can be calculated based on the longest sleep period (e.g., the primary sleep period) or naps occurring after the longest sleep period. In some respects, the ring can measure the user's body temperature while they sleep, and the system 200 can display the user's average temperature relative to their baseline temperature. If a user's body temperature is outside their normal range (e.g., significantly higher or lower than 0.0), factors affecting body temperature may be highlighted (e.g., entering an "attention" state) or an alert may be generated for the user in other ways.

[0129] In some implementations, wearable device 104 and / or user device 106 can measure certain characteristics, from which attributes (“derived attributes”) can be derived, and further attributes (“further derived attributes”) can be derived from the measurement results and / or the derived attributes. Measurement results may include at least one of the following: intercardiac interval (IBI), physical activity (intensity, duration, time), skin temperature, current time and time zone, ambient light exposure, mental stress, and food intake. Derived attributes may include at least one of the following: resting heart rate, respiratory rate, sleep stage, sleep duration, bedtime, and activity preference. Further derived attributes may include at least one of the following: sleep midpoint, sleep latency, spontaneous awakening time, circadian rhythm type (morning / evening), circadian rhythm, circadian rhythm alertness curve, sleep drive curve, synchronicity index, drowsiness index, and readiness level.

[0130] refer to Figure 3 Further details and descriptions of the incidental advantages of the invention will be provided.

[0131] Figure 3 An example of a system 300 supporting techniques for providing insights related to a user's physiological state, according to various aspects of this disclosure, is shown. Aspects of system 300 may be implemented by system 100, system 200, or both systems 100 and 200, or may be implemented by system 100, system 200, or both systems 100 and 200. For example, as described herein, system 300 may support techniques for providing insights related to a user's physiological state.

[0132] System 300 includes user 102, wearable device 104 (e.g., wearable ring device 104), and user device 106, which can be... Figure 1 and Figure 2 Examples of the corresponding devices described herein. In some embodiments, system 300 may also include a vehicle 302 that can be connected to user device 106 via a wired or wireless connection. Vehicle 302 may be any means of transportation that can be driven by user 102 or used by user 102 for travel, such as a car, bicycle, train, airplane, bus, boat or other watercraft, electric scooter, etc. User device 106 may execute wearable application 250. In some embodiments, user 102 may use several separate vehicles during a single travel event.

[0133] System 300 can provide physiological state-related insights associated with user 102. As used herein, the term "physiological state-related insights associated with user" can refer to, for example, messages, instructions, directives, user guidance information, user alertness information, or user state information representing the user's current alertness data or physiological state, or any combination thereof, that can be output by user device 106 or sent to vehicle 302.

[0134] Wearable application 250 can receive baseline physiological data associated with user 102 from wearable device 104. The baseline physiological data, including measured physiological parameters, can include any physiological data known in the art, including but not limited to temperature data, accelerometer data (e.g., movement / exercise data), sleep data, heart rate data, HRV data, blood oxygen level data, respiratory rate data, or any combination thereof. Although Figure 3 Only one wearable device 104 is shown, but in other embodiments, there may be multiple wearable devices associated with user 102.

[0135] Wearable application 250 can obtain a user-associated physiological baseline based at least in part on baseline physiological data associated with the user, which provides reference user alertness data. The user-associated physiological baseline can be determined by wearable device 104, user wearable application 250, or external processing device, or any combination thereof. Reference user alertness data can be derived from the baseline physiological data, i.e., from actual measurements taken by the wearable device, such as daytime heart rate data (e.g., heart rate when the user is awake), nighttime heart rate data (e.g., heart rate when the user is asleep), exercise heart rate data (e.g., heart rate during exercise), recovery time (e.g., time the user is in a relaxed state), temperature, respiratory rate, blood oxygen saturation, activity / movement, or any combination thereof.

[0136] Wearable application 250 may receive additional physiological data associated with the user from at least one wearable device. For example, the additional physiological data associated with the user may relate to time periods such as the past 24 hours, 48 ​​hours, or 72 hours, or any other applicable time period.

[0137] Wearable application 250 may obtain current user alertness data based at least in part on additional physiological data associated with the user. Current user alertness data can be derived from additional physiological data (i.e., from actual measurements taken by the wearable device), such as heart rate, skin temperature, blood oxygen saturation, activity / movement, etc. In other words, current user alertness data represents the user's current state, derived from the latest measurements obtained by wearable device 104 during a specific time period, such as the past 24 hours, 48 ​​hours, or 72 hours, or any other applicable time period. This current user alertness data can then be taken into account when the user initiates a travel event or is about to initiate a travel event in the (near) future.

[0138] The term "alertness data" as used herein includes not only a user's alertness or readiness, or lack thereof, but also their physical and mental state in response to various stresses. Alertness can be an estimate of a user's physiological and / or mental state at a given moment. For example, it can summarize the physical and mental prerequisites a user needs to be in good condition throughout the day. Essentially, it may encompass the effects of measured prior physical activity, the previous night's sleep, and various bodily responses. Bodily responses may mean, for example, temperature, resting heart rate relative to the user's own standard values, or the magnitude of their changes as a response to the previous day's physical activity. The terms "alertness data," "alertness score," "alertness level," "recovery data," "readiness data," "readiness level," and "readiness score" are used interchangeably in this specification.

[0139] In one embodiment, the user device is configured to calculate a baseline and / or alertness level / readiness score for assessing the user's readiness. Specifically, the readiness score can be calculated based on cross-correlation analysis of long-term data, trends, and in-depth data analysis (i.e., heart rate variability, sleep patterns, stress levels, etc.). Furthermore, the long-term data, trends, and cross-correlation analysis can be correlated with the time period (e.g., a day, a week, or a month) for which the in-depth data analysis was performed. Therefore, user movement and biosignals (e.g., heart rate, sleep patterns, heart rate variability, and stress levels) measured over that time period are cross-correlated to calculate the readiness score, thereby assessing the user's readiness.

[0140] A readiness score indicates a user's level of readiness and recovery from mental and physical stress. The terms "readiness" or "alertness" used herein can also describe the return of mental and physical strength (or energy levels) to normal after a mental and physical stress event. In one example, if physical stress is associated with a period of activity (e.g., physical exercise), the readiness score could be based on the user's heart rate, heart rate variability, and stress level. For example, if the user's heart rate, heart rate variability, and stress level have returned to normal after exercise, the readiness score could be good or high (e.g., approximately 90%). Similarly, if mental stress is associated with a period of rest (e.g., sleep), the readiness score could be based on the user's movement, heart rate, and sleep graph. For example, if the user moves less, has a heart rate within the expected range (40-70 beats per minute), and the sleep graph shows sufficient deep sleep, the readiness score could be good or high (e.g., approximately 90%).

[0141] In one embodiment, a user's historical data is also used to calculate the readiness score. For example, historical data may include information related to the user's medical history, but also includes historical data collected by the system itself. For instance, historical data may include data showing how the user typically recovers from workload. Furthermore, historical data may include information related to past professional life, dietary habits, etc. Therefore, it will be apparent to those skilled in the art that historical data can have a significant impact on the measurement of a user's readiness score.

[0142] The solutions described in this paper can use different computational parameters and can be designed to learn from previous measurements. For example, data from the past week, two weeks, one month, or two months (or any other time interval) can be used to set user-specific personalized calibration values, averages, and / or limits. Furthermore, the aggregated physiological data can be used to change the weights assigned to different aspects measured or obtained from the user.

[0143] Measuring or acquiring a user's movement provides movement data, while measuring at least one biosignal provides biosignal or biosignal data (these two terms are used interchangeably). User movement data acquired during rest periods can be used for a variety of purposes. For example, it is commonly used to determine whether a given moment belongs to an active or rest period, or, if one or more other types of periods have been defined, to determine whether it belongs to that other type of period. Furthermore, it can be used as part of the starting data for determining a rest summary. One or more biosignals are identified during rest periods, but can also be identified during active periods. For example, if a user's temperature rises during a rest period, that temperature can be monitored during subsequent active periods to ensure that the rise is caused by fever or other reasons. Additionally, elevated temperature readings (e.g., fever) can be programmed to adjust readiness / alertness over an extended period (i.e., not just the next day). In practice, it is beneficial to appropriately increase rest time proportional to the length of illness after one or several days.

[0144] User movement can be measured or retrieved from wearable devices and / or separate devices. User movement can include, for example, actual movement (such as raising an arm or hand, walking, running, etc.) or the user's cumulative steps, activity time, or distance traveled.

[0145] In one embodiment, the wearable device may include at least one motion sensor, such as an accelerometer, gyroscope, magnetic field sensor, or a combination thereof, to measure the user's movement. The motion sensor is configured to generate motion data indicative of the user's movement. For example, the motion sensor may be configured to determine linear motion information, rotational motion information, etc. Furthermore, this information (linear motion or rotational motion) may be combined or correlated to generate motion data indicative of the user's movement. As described above, the motion data may also be generated by a separate device and retrieved or obtained by a ring or server.

[0146] Wearable application 250 can identify trigger conditions at least in part based on a comparison between current user alertness data and reference user alertness data, which provides insights into the user's associated physiological state related to the travel event. For example, the comparison could reveal that the user's current alertness data is lower than the reference user alertness data. Lowered user alertness data implies that some factors are influencing the user, and this influence is reflected in the physiological data measured by wearable device 104. For example, a trigger condition can be identified when the current user alertness data differs from the reference user alertness data by a predetermined threshold amount or level. In some embodiments, user alertness data and reference user alertness data can be expressed as percentage values. Therefore, in some embodiments, the predetermined threshold amount can also be expressed as a percentage value. For example, the user's current alertness data could be 40%, and the reference user alertness data could be 75%. If the predetermined threshold amount is, for example, 30%, then a trigger condition can be identified as the difference between the reference user alertness data and the reference user alertness data being greater than 30%.

[0147] For example, current user alertness data might indicate that the user has had poor sleep quality over the past three nights. This could result in the current user alertness data being lower than the reference user alertness data, triggering user-related physiological state insights associated with the travel event. In some embodiments, different threshold levels may be present to identify triggering conditions. For example, different user-related physiological state insights associated with the travel event can be triggered based on the comparison results. When the comparison displays a first comparison result, a first physiological state insight associated with the user related to the travel event involving transportation can be provided. When the comparison displays a second comparison result, a second physiological state insight associated with the user related to the travel event involving transportation can be provided. For example, the first comparison result might indicate that the user should take a short rest during the driving event. The second comparison result might indicate that the user should have a longer rest period during the driving event.

[0148] Wearable application 250 can use user device 106 to provide physiological state-related insights associated with the user. For example, user device 106 itself can output physiological state-related insights associated with the user. In some embodiments, the graphical user interface (GUI) of user device 106 can be configured to display physiological state-related insights. For example, the GUI can display messages or notifications to the user, such as “Take a break,” “Drive slower,” “Keep a safer distance from the car in front,” “Have a coffee,” etc. In some embodiments, user device 106 can be configured to provide at least one of auditory, tactile, and visual alerts associated with physiological state-related insights. For example, user device 106 can provide auditory messages to the user via a speaker, such as “Take a break,” “Drive slower,” “Keep a safer distance from the car in front,” “Have a coffee.” In another example, the auditory alert can be a predetermined audio signal provided via a speaker, such as a buzzer signal to remind the user. The audio signal can also indicate that there is a message on the GUI that provides more details. In another example, user device 106 can provide predetermined tactile patterns to remind the user. In another example, wearable application 250 can use user device 106 to instruct wearable device 104 to provide haptic alerts.

[0149] In some embodiments, a travel event can be a future travel event. For example, a future travel event can be determined based on schedule records in a calendar associated with user 102. Schedule records can, for example, indicate information about the travel event, such as user 106 starting a long-distance bus drive tomorrow or user 106 having a long-haul intercontinental flight tomorrow. In another example, schedule records can indicate a client meeting at a location requiring a long-distance bus or flight. In yet another example, the calendar can indicate a busy day where the user needs to undertake a long-distance trip at the end of the day. In yet another example, the travel time may be challenging (very early or very late). In yet another example, after a long drive, the user needs to resume driving after only a short rest. Wearable application 250 can provide instructions to user device 106 to user 102, such as regarding the required amount of sleep (e.g., "You have a long trip tomorrow, go to bed no later than 10:00 pm and have a good breakfast in the morning" or "You have a flight tomorrow, go to bed no later than 10:00 pm and have a hearty breakfast in the morning") or regarding the number of times to eat and / or rest during driving (e.g., "After a busy day, you have a long drive today, please take several breaks during the drive" or "You will have another long drive soon, please eat and rest before driving"). Furthermore, the sleep stage, sleep score, and sleep state associated with user 102 have already been referenced previously. Figure 1The discussion took place. This sleep information can be used when identifying and providing users with insights related to their physiological state.

[0150] For example, when determining what instructions or insights to provide to a user, the wearable application 250 can take into account the comparison between current user alertness data and reference user alertness data. For instance, if the comparison between the current user alertness data and the reference user alertness data indicates a larger first difference rather than a smaller second difference, then the first difference could lead to providing a longer sleep instruction and the second difference. In other words, the required amount of sleep can be determined by the comparison results.

[0151] In some embodiments, a travel event can be a current travel event. For example, physiological data received from wearable device 104 may include accelerometer data. Wearable application 250 may detect a current travel event based at least in part on accelerometer data. For example, accelerometer data can provide an indication that user 102 is driving a car and that one or more of user 102's hands are making turning movements when user 106 turns the steering wheel. When wearable device 104 (e.g., a ring) is worn by user 102, the ring also moves when the user moves their hand containing the ring. Meanwhile, since the actual movement of the user's hand when turning the steering wheel is limited, this movement results in specific and repetitive signal components in the accelerometer data. When the accelerometer data is analyzed, these signal components can be identified, and it can be determined that user 102 is currently driving a car. In some embodiments, this determination can be made using reference accelerometer data to identify that the user is driving a car. Reference accelerometer data may refer to data stored in user device 106 and accessible by wearable application 250. Reference accelerometer data can identify signal waveforms associated with hand movements, for example, when the steering wheel is turned. These waveforms can then be compared with acceleration data obtained from wearable device 102.

[0152] In some embodiments, user equipment 106 may establish a valid local communication link (e.g., a wireless Bluetooth link) between user equipment 106 and vehicle 302, and may detect a travel event based at least in part on the presence of the valid local communication link. When wearable application 250 recognizes that a valid local communication link has been established between user equipment 106 and vehicle 302, for example, because user equipment 106 has been detected by vehicle 302 (or vehicle 302 has been detected by user equipment 106), the presence of the valid local communication link between user equipment 106 and vehicle 302 provides an indication that the user has initiated a travel event. Detection of a travel event may also mean that a process for identifying triggering conditions can be initiated. In other words, since there was no prior indication of a travel event and future travel events are unknown, in one example, the process for identifying triggering conditions may begin when a travel event has been detected.

[0153] In some embodiments, user device 106 may receive satellite positioning data and may detect travel events based at least in part on the satellite positioning data received from user device 106. For example, if the speed of user 102 determined based on satellite positioning data exceeds a predetermined threshold, or if the location of user 106 is constantly changing and acceleration sensor data received from wearable device 104 indicates that user 102 is driving a car, it can be determined that user 106 is indeed driving a car and a current travel event exists. Acceleration data may indicate, for example, repetitive movements of user 106's hands, indicating that user 106 is touching and turning the steering wheel while driving. In some embodiments, user device 106 may store reference acceleration data accessible to wearable application 250. The reference acceleration data may identify signal waveforms associated with hand movements, for example, when the steering wheel is turned. These waveforms can then be compared with the acceleration data obtained from wearable device 102. When a match or a sufficiently close match exists, it can be determined that user 102 is driving a car.

[0154] In some embodiments, in response to the detection of a travel event, an instruction to send physiological data at a preset rate can be sent to wearable device 104. When a travel event has been detected, wearable application 250 can instruct wearable device 104 to send physiological data more frequently. This ensures that physiological data is frequently sent from at least one wearable device 104 to monitor user 102 during the travel event. With more frequent receipt of physiological data, possible changes in user 102 or user 102's behavior reflected in the physiological data can be quickly identified, and necessary actions can be executed quickly. Since the user's current alertness data is determined based on more recent physiological data, triggering conditions can be identified once a change in the current user alertness data is detected. When the travel event is detected to be over, wearable application 250 can instruct wearable device 104 to send physiological data again at a normal rate, for example, to conserve the battery of wearable device 104.

[0155] In some embodiments, enabling user device 106 to provide physiological state-related insights associated with user 102 may include sending these insights to vehicle 302 via an effective local communication link between user device 106 and vehicle 302. This achieves a solution whereby the vehicle can at least partially utilize the physiological state-related insights received from user device 106 when deciding whether to alert user 102. For example, the physiological state-related insights associated with user 102 may include one or more predefined messages associated with identified triggering conditions to provide physiological state-related insights associated with the user in relation to a travel event involving the vehicle. For example, there may be an agreed-upon message structure between wearable application 250 and vehicle 302 or the vehicle system. The message structure may define the messages and information that can be sent between wearable application 250 and vehicle 302. For example, simple numerical or binary values ​​may be sent from wearable application 250 to vehicle 302, and each numerical or binary value may have a predetermined meaning. For example, bit value '0001' could indicate that the physiological state-related insight associated with user 102 means "take a coffee break," bit value '0010' could indicate that the physiological state-related insight associated with user 102 means "stop immediately and rest for a longer period," and bit value '0011' could indicate that the physiological state-related insight associated with user 102 means "reduce speed," and so on. As another example, a specific bit value could indicate to vehicle 302 that the user is too fatigued to operate vehicle 302 safely. In response to this indication, vehicle 302 could be configured not to start because the user is not able to drive safely. Obviously, these are just examples of possible physiological state-related insights, and any other insights related to user alertness data can be applied. Since wearable device 104 provides physiological data about user 102, based on which current user alertness data can be determined, it is possible to estimate or identify the user's physical and / or mental load before or during a travel event. For example, in response to receiving physiological state-related insights from user device 106, the driver monitoring system may lower the temperature in the vehicle to keep user 102 more alert, remind user 102 to rest, and / or automatically reduce the speed of vehicle 102, since the physiological state-related insights indicate a reduced level of alertness associated with user 106. In yet another example, vehicle 302 may apply, for example, a minimum distance limit for vehicle differences to vehicles in front of vehicle 302 based on physiological state-related insights received from wearable application 250.

[0156] In some embodiments, the wearable application 250 may provide a secure application programming interface (API) to the vehicle 302 via the user equipment 106. This allows the driver monitoring system of the vehicle 302 to securely receive additional information for its decision-making from the user equipment 106 via a secure communication connection.

[0157] In some embodiments, the wearable application 250 can display physiological state-related insights associated with the user through the graphical user interface of the user device 106. For example, the GUI can display messages or notifications to the user, such as “Take a break,” “Slow down,” “Keep a greater distance from the car in front,” “Have a cup of coffee,” etc. As another example, if the travel event is a future travel event (e.g., it happens tomorrow), the GUI can be configured to display notifications to the user 102, such as instructing the user 102 to get enough sleep the following night and / or eat properly at the right time. For example, if the travel event begins at 07:00 AM the next morning, the notification could instruct the user to “go to bed no later than 09:00 PM.” As another example, if the travel event begins at 09:00 AM the next morning, the notification could instruct the user to “have a hearty breakfast in the morning.” As another example, physiological data obtained from the wearable device 104 can include glucose level measurements, and the wearable application 250 can monitor the user's glucose levels based on these measurements. Based on the monitored glucose levels, the GUI can be configured to inform the user that their blood sugar levels are low / high and instruct the user to eat before the trip begins.

[0158] In some embodiments, user device 106 may be configured to provide at least one of auditory, tactile, and visual alerts associated with insights related to physiological state. For example, user device 106 may provide auditory messages to user 102 via a speaker, such as “Take a break,” “Slow down,” “Keep a greater distance from the vehicle in front,” or “Have a cup of coffee.” In another example, the auditory alert may be a predetermined audio signal provided via a speaker, such as a buzzer signal to remind user 102. The audio signal may also indicate that a more detailed message has been provided on the GUI. In another example, user device 106 may provide a predetermined tactile pattern to remind user 102. In yet another example, wearable application 250 may use user device 106 to instruct wearable device 104 to provide a tactile alert to indicate that a more detailed message has been provided on the GUI.

[0159] In some embodiments, when user device 106 provides physiological state-related insights associated with user 102, wearable application 250 may send these physiological state-related insights to a network entity, such as a call service. For example, in response to the sent physiological state-related insights, the call service may establish a call with user device 106 to notify the user of the state of user 102. For example, the call may notify the user, "You are too fatigued to continue driving, please stop immediately." For example, the call service may be used when the user's attention cannot be obtained through GUI, auditory alarms, tactile alarms, and / or visual alarms. In other words, the call service may be used as a "last resort" to obtain the user 102's attention.

[0160] In some embodiments, wearable application 250 may receive vehicle data associated with user 102 from vehicle 302. The vehicle data associated with the user includes travel user behavior data collected during a travel event. Triggering conditions may be identified at least in part based on the vehicle data. For example, there may be an agreed-upon message structure between wearable application 250 and vehicle 302 or the vehicle system. The message structure may define messages or information that can be sent between wearable application 250 and vehicle 302. For example, simple numerical or binary values ​​may be sent from vehicle 302 to wearable application 250. The driver monitoring system of vehicle 302 may use various sensors and driving data (e.g., speed, driving duration, lane assist data, steering wheel manipulation data, braking data, etc.) provided by vehicle 302 to monitor the user and the user's actions and behaviors. Each piece of information may then be sent to wearable application 250, for example, as an encoded message in the message structure. For example, specific binary fields can identify steering wheel manipulation data in an encoded form, such as the number of times the user made sharp steering wheel movements or the number of times the user braked suddenly in the past X minutes. Vehicle 302 can send vehicle data to wearable application 250, for example, via a safety API. Since wearable application 250 knows the current user alertness data based on physiological data received from wearable device 104, the vehicle data received from vehicle 302 can be used to supplement the current user alertness data. For example, the vehicle data received from vehicle 302 can provide indications that the user is exhibiting symptoms of fatigue based on data collected from the vehicle. For example, when lane assist data indicates that the user is having difficulty staying in the lane, the user may have made too many sharp (corrective) steering wheel movements within a specified time. When the vehicle data received from vehicle 302 is combined with the current user alertness data determined by wearable application 250, this combination can trigger conditions to provide insights related to the user's associated physiological state in relation to a travel event involving vehicle 302. Therefore, data received from vehicle 302 can also be used to identify triggering conditions. For example, although current user alertness data alone cannot lead to the identification of a triggering condition, current user alertness data together with vehicle data can trigger identification. Based on this identification, wearable application 250 can prompt the user, for example, to stop vehicle 302 and take a break.

[0161] In some embodiments, the wearable application 250 may receive weather data associated with a travel event. It can be determined, based on the weather data associated with the travel event, that the weather data affects the travel event. For example, a user may have just started their journey. For example, the weather data may indicate that a storm is approaching and will soon overlap with the user's driving route. Identification of triggering conditions may then include identifying triggering conditions based at least in part on the weather data. For example, if current user alertness data indicates that the user is fatigued, the wearable application 250 may also use the weather data in determining physiological state-related insights associated with the user. The physiological state-related insights provided may, for example, instruct the user to change their route due to the storm, or to take longer breaks so that the storm passes through the user during the break, or instruct the user 102 to take more breaks than usual during the travel event. Optionally, if the user has not yet started their travel event and a storm is approaching, the wearable application 250 may instruct the user 102 to, for example, delay the start of the travel event or start the travel event earlier.

[0162] In some embodiments, the wearable application 250 may receive satellite positioning data related to a travel event from the user device 106. For example, the travel event may be identified as being related to a route the user has not previously driven (i.e., a route they have never experienced). The wearable application 250 may access route data, including routes the user has previously driven. This information can be used to determine when the user was driving on a route they have never driven before or rarely drive. Therefore, it can be determined that the travel event is related to a route the user has never experienced, and this can be taken into account when identifying triggering conditions. The wearable application 250 may, for example, instruct the user to drive slower than usual and / or take a break during the travel event.

[0163] In some embodiments, the wearable application 250 may receive route planning data related to a travel event. The route planning data may, for example, identify the duration and start time of the travel event. For instance, the wearable application 250 may detect that user 102 is starting or intending to start a long and / or prolonged travel event (e.g., using a car) based on information obtained from a map or navigation application. This information may be taken into consideration when triggering conditions are identified. For example, current user alertness data may indicate that the user is fatigued. When user 102 now starts or intends to start a long and / or prolonged travel event, insights into what physiological state to provide to the user may be taken into consideration. For example, a longer and / or prolonged car driving event may result in providing the user with rest and food instructions during the car driving event, while a shorter car driving event may result in only providing the user with rest instructions during the car driving event.

[0164] In some embodiments, a single travel event may involve multiple modes of transportation. For example, user 102 may initiate or have already begun a travel event that first involves flying and then driving to the final destination. In cases where a single travel event involves multiple modes of transportation, the physiological state-related insights associated with the user can take into account the fact that multiple modes of transportation are associated with a single travel event. For example, the physiological state-related insights provided for a user who first takes a six-hour flight and then drives for five hours will differ from those provided for a user who drives for five hours without first taking a flight. For example, a user's behavior before and / or during the flight (e.g., whether the user sleeps during the flight) will influence the physiological state-related insights provided.

[0165] Figure 4 A block diagram of a device 400 supporting technologies for providing insights into a user's physiological state, according to various aspects of this disclosure, is shown. Device 400 may include an input module 405, an output module 410, and a wearable application 250. Device 400 may also include a processor. These components can communicate with each other, for example, via one or more buses.

[0166] Input module 405 provides a means for receiving information (e.g., data packets, user data, control information, or any combination thereof, associated with various information channels, such as control channels, data channels, information channels related to disease detection technologies). The information can be transmitted to other components of device 400. Input module 405 can utilize a single antenna or a group of multiple antennas.

[0167] Output module 410 provides a means for transmitting signals generated by other components of device 400. For example, output module 410 can transmit information associated with various information channels (e.g., control channels, data channels, information channels related to disease detection technologies), such as data packets, user data, control information, or any combination thereof. In some examples, output module 410 may be located in a transceiver module shared with input module 405. Output module 410 may utilize a single antenna or a group of multiple antennas.

[0168] For example, wearable application program 250 may include data acquisition component 420, physiological baseline acquisition component 425, current user alertness data acquisition component 430, trigger condition recognition component 435, and physiological state-related insight provision component 440, or any combination thereof. In some examples, wearable application 250 or its various components may be configured to use input module 405, output module 410, or both input module 405 and output module 410, or otherwise cooperate with input module 405, output module 410, or both input module 405 and output module 410 to perform various operations (e.g., receiving, monitoring, transmitting). For example, wearable application 250 may receive information from input module 405, send information to output module 410, or integrate with input module 405, output module 410, or both input module 405 and output module 410 to receive information, send information, or perform various other operations as described herein.

[0169] Data acquisition component 420 may be configured or otherwise support means for receiving user-related baseline physiological data from at least one wearable device. Physiological baseline acquisition component 425 may be configured or otherwise support means for obtaining a user-related physiological baseline based at least in part on user-related baseline physiological data, which provides reference user alertness data. Data acquisition component 420 may be configured or otherwise support means for receiving user-related additional physiological data from at least one wearable device. Current user alertness data acquisition component 430 may be configured or otherwise support means for obtaining current user alertness data based at least in part on additional user-related physiological data. Trigger condition identification component 435 may be configured or otherwise support means for identifying trigger conditions used to provide user-related physiological state insights related to travel events involving transportation, based at least in part on a comparison between current user alertness data and reference user alertness data. The physiological state-related insights providing component 440 can be configured or otherwise supported to enable user devices to provide physiological state-related insights associated with the user.

[0170] Figure 5A block diagram of a wearable application 500 supporting techniques for providing user-related physiological state insights according to various aspects of this disclosure is shown. As described herein, wearable application 500 may be an example of a wearable application or wearable application 250, or aspects of both. Wearable application 500 or its various components may be examples of means for performing various aspects of the techniques described herein for providing user-related physiological state insights. For example, wearable application 500 may include a data acquisition component 505, a physiological baseline acquisition component 510, a current user alertness data acquisition component 515, a trigger condition identification component 520, a physiological state insight provision component 525, a communication link establishment component 530, a data transmission component 535, or any combination thereof. These components may communicate with each other directly or indirectly (e.g., via one or more buses).

[0171] Data acquisition component 505 may be configured or otherwise support means for receiving user-related baseline physiological data from at least one wearable device. Physiological baseline acquisition component 510 may be configured or otherwise support means for obtaining a user-related physiological baseline based at least in part on user-related baseline physiological data, which provides reference user alertness data. Data acquisition component 505 may be configured or otherwise support means for receiving user-related additional physiological data from at least one wearable device. Current user alertness data acquisition component 515 may be configured or otherwise support means for obtaining current user alertness data based at least in part on additional user-related physiological data. Trigger condition identification component 520 may be configured or otherwise support means for identifying trigger conditions used to provide user-related physiological state insights related to travel events involving transportation, based at least in part on a comparison between current user alertness data and reference user alertness data. The physiological state-related insight providing component 525 can be configured or otherwise supported to enable the user equipment to provide physiological state-related insights associated with the user. The communication link establishment component 530 can be configured or otherwise supported to establish a local communication link between the user equipment and the vehicle. The data sending / receiving component 535 can be configured or otherwise supported to send physiological state-related insights to the vehicle and / or receive vehicle data associated with the user from the vehicle via the local communication link between the user equipment and the vehicle.

[0172] In some examples, the trigger condition recognition component 520 may be configured or otherwise supported to recognize trigger conditions when the current user alertness data differs from the reference user alertness data by a predetermined threshold amount.

[0173] In some examples, the travel event is a future travel event.

[0174] In some examples, the travel event is the current travel event.

[0175] In some examples, the physiological data received from the wearable device 104 includes accelerometer data, and the trigger condition recognition component 520 may be configured or otherwise supported for means of identifying that a user is driving a vehicle based at least in part on a comparison between the accelerometer data and reference accelerometer data, and for detecting travel events based at least in part on the comparison.

[0176] In some examples, the physiological state-related insight providing component 525 may be configured or otherwise support means for establishing a valid local communication link between the user equipment and the vehicle, and the trigger condition identification component 520 may be configured or otherwise support means for detecting travel events based at least in part on the presence of a valid local communication link between the user equipment and the vehicle.

[0177] In some examples, the data acquisition component 505 may be configured or otherwise supported to support means for receiving satellite positioning data from the user equipment. In some examples, the trigger condition identification component 520 may be configured or otherwise supported to support means for detecting travel events based at least in part on satellite positioning data from the user equipment.

[0178] In some examples, the data sending / receiving component 525 may be configured or otherwise supported for sending instructions to at least one wearable device in response to the detection of a travel event to send physiological data at a preset rate.

[0179] In some examples, the physiological state-related insights providing component 525 may be configured or otherwise support means for displaying physiological state-related insights in the graphical user interface of a user device.

[0180] In some examples, the physiological state-related insight providing component 525 may be configured or otherwise support means for enabling a user device to provide at least one of auditory, tactile, and visual alarms associated with physiological state-related insights.

[0181] In some examples, the data sending / receiving component 535 may be configured or otherwise supported to support means for receiving user-related vehicle data from the vehicle, wherein the user-related vehicle data includes user behavior data collected during a travel event. In some examples, the trigger condition identification component 520 may be configured or otherwise supported to support means for identifying trigger conditions, including identifying trigger conditions based at least in part on user-related vehicle data.

[0182] In some examples, the data sending / receiving component 535 may be configured or otherwise supported to support means for receiving meteorological data related to a travel event. In some examples, the trigger condition identification component 520 may be configured or otherwise supported to support means for determining, based on the meteorological data associated with the travel event, that the meteorological data associated with the travel event affects the travel event and to identify trigger conditions based at least in part on the meteorological data.

[0183] In some examples, the data sending / receiving component 535 may be configured or otherwise supported to support means for receiving calendar data associated with a travel event. In some examples, the trigger condition identification component 520 may be configured or otherwise supported to determine, based on the calendar data associated with the travel event, that the travel event is a future travel event, and to identify trigger conditions, include means for identifying trigger conditions at least in part based on that determination result.

[0184] In some examples, the data sending / receiving component 535 may be configured or otherwise supported to support means for receiving satellite positioning data associated with a travel event from a user equipment. In some examples, the trigger condition identification component 520 may be configured or otherwise supported to support means for determining routes not traveled by the user involved in the travel event based on the satellite positioning data associated with the travel event and to identify trigger conditions at least in part based on that determination.

[0185] In some examples, the data sending / receiving component 535 may be configured or otherwise supported to support means for receiving route planning data associated with travel events. In some examples, the trigger condition identification component 520 may be configured or otherwise supported to support means for identifying trigger conditions based at least in part on route planning data.

[0186] Figure 6A schematic diagram of system 600 is shown, which includes device 605 that supports techniques for providing insights related to a user's physiological state according to various aspects of this disclosure. Device 605 may be an example of a component of device 400 as described herein or may include components of device 400 as described herein. As previously mentioned, device 605 may include an example of user device 106. Device 605 may include components for bidirectional communication, including components for sending and receiving communications with wearable device 104 and server 110, such as wearable application 620, communication module 610, antenna 615, user interface component 625, database (application data) 630, memory 635, and processor 640. These components may communicate electronically or be otherwise coupled (e.g., operational coupling, communication coupling, functional coupling, electronic coupling, electrical coupling) via one or more buses (e.g., bus 645).

[0187] The communication module 610 can manage the input and output signals of the device 605 via the antenna 615. The communication module 610 may include... Figure 2 An example of the communication module 220-b of the user equipment 106 shown and described herein. In this regard, the communication module 610 can manage communication with the ring 104 and the server 110, such as... Figure 2 As shown. Communication module 610 can also manage peripheral devices not integrated into device 605. In some cases, communication module 610 may represent a physical connection or port to an external peripheral device. In some cases, communication module 610 may utilize an operating system (such as iOS®, ANDROID®, MS-DOS®, MS-WINDOWS®, OS / 2®, UNIX®, LINUX®) or other known operating systems. In other cases, communication module 610 may represent or interact with a wearable device (e.g., ring 104), modem, keyboard, mouse, touchscreen, or similar device. In some cases, communication module 610 may be implemented as part of processor 640. In some examples, a user can interact with device 605 via communication module 610, user interface component 625, or via hardware components controlled by communication module 610.

[0188] In some cases, device 605 may include a single antenna 615. However, in other cases, device 605 may have more than one antenna 615, capable of simultaneously transmitting or receiving multiple wireless transmissions. As described herein, communication module 610 can communicate bidirectionally via one or more antennas 615, wired or wireless links. For example, communication module 610 may represent a wireless transceiver and can communicate bidirectionally with another wireless transceiver. Communication module 610 may also include a modem to modulate data packets, provide modulated data packets to one or more antennas 615 for transmission, and demodulate data packets received from one or more antennas 615.

[0189] User interface component 625 manages data storage and processing within database 630. In some cases, users can interact with user interface component 625. In other cases, user interface component 625 can operate automatically without user interaction. Database 630 can be an example of a single database, a distributed database, multiple distributed databases, a data storage, a data lake, or an emergency backup database.

[0190] Memory 635 may include random access memory (RAM) and read-only memory (ROM). Memory 635 may store computer-readable, computer-executable software, including instructions that, when executed, cause processor 640 to perform the various functions described herein. In some cases, memory 635 may contain a BIOS, which controls basic hardware or software operations, such as interaction with peripheral components or devices.

[0191] Processor 640 may include intelligent hardware devices (e.g., general-purpose processors, DSPs, CPUs, microcontrollers, ASICs, FPGAs, programmable logic devices, discrete gate or transistor logic units, discrete hardware components, or any combination thereof). In some cases, processor 640 may be configured to use a memory controller to operate a memory array. In other cases, the memory controller may be integrated into processor 640. Processor 640 may be configured to execute computer-readable instructions stored in memory 635 to perform various functions (e.g., functions or tasks supporting methods and systems for sleep staging algorithms).

[0192] For example, wearable application 620 may be configured or otherwise support means for receiving user-related baseline physiological data from at least one wearable device. Wearable application 620 may be configured or otherwise support means for obtaining a user-related physiological baseline based at least in part on the user-related baseline physiological data, which provides reference user alertness data. Wearable application 620 may be configured or otherwise support means for receiving user-related additional physiological data from at least one wearable device. Wearable application 620 may be configured or otherwise support means for obtaining current user alertness data based at least in part on the user-related additional physiological data. Wearable application 620 may be configured or otherwise support means for identifying trigger conditions for providing user-related physiological state insights related to travel events involving transportation, based at least in part on a comparison between current user alertness data and reference user alertness data. Wearable application 620 may be configured or otherwise support means for enabling user devices to provide user-related physiological state insights.

[0193] Wearable application 620 may include applications (e.g., "app"), programs, software, or other components configured to facilitate communication with ring 104, server 110, other user devices 106, etc. For example, wearable application 620 may include an application executable on user device 106 configured to receive data (e.g., physiological data) from ring 104, perform processing operations on the received data, send and receive data with server 110, and facilitate the presentation of data to user 102.

[0194] Figure 7 A flowchart illustrating a method for providing insights into a user's associated physiological state, supported by descriptions of various aspects of this disclosure, is shown. Operation of method 700 can be implemented by a user device or its components described herein. For example, operation of this method can be performed by reference to… Figures 1 to 6 The user equipment described is used to perform this function. In some examples, the user equipment may execute a set of instructions to control the functional elements of the user equipment to perform the described function. Additionally or alternatively, the user equipment may use dedicated hardware to perform aspects of the described function.

[0195] At 700, this method may include receiving baseline physiological data associated with a user from at least one wearable device. The operation of 700 can be performed according to the examples disclosed herein. In some examples, aspects of the operation of 700 may be derived from references... Figure 4 The data acquisition component 420 described is used for execution.

[0196] At 705, this method may include obtaining a user-associated physiological baseline based at least in part on baseline physiological data associated with the user, which provides reference user arousal data. Operation of 705 can be performed according to the examples disclosed herein. In some examples, aspects of operation of 705 may be derived from reference... Figure 4 The physiological baseline described is obtained by component 425 for execution.

[0197] At 710, the method may include receiving additional physiological data associated with a user from at least one wearable device. The operation of 710 can be performed according to the examples disclosed herein. In some examples, aspects of the operation of 710 may be derived from references... Figure 4 The data acquisition component 420 described is used for execution.

[0198] In 715, this method may include obtaining current user alertness data based at least in part on additional physiological data associated with the user. The operation of 715 can be performed according to the examples disclosed herein. In some examples, aspects of the operation of 715 can be derived from references... Figure 4 The current user alertness data acquisition component 430 is used for execution.

[0199] At 720, this method may include identifying triggering conditions, at least in part, based on a comparison between current user alertness data and reference user alertness data, for providing physiological state-related insights associated with a user involved in a travel event involving at least one mode of transportation. The operation of 720 can be performed according to the examples disclosed herein. In some examples, aspects of the operation of 720 may be derived from reference... Figure 4 The described trigger condition identification component 435 is used for execution.

[0200] At 725, this method may include enabling the user device to provide physiological state-related insights associated with the user. The operation of 725 can be performed based on the examples disclosed herein. In some examples, aspects of the operation of 725 may be derived from references... Figure 4 The described physiological state-related insights provide component 440 for execution.

[0201] It should be noted that the above method describes feasible implementations, and the operations and steps can be rearranged or otherwise modified, and other implementations are also feasible. Furthermore, aspects of two or more methods can be combined.

[0202] Figure 8 A block diagram illustrating the relationship between data attributes measured and derived according to various aspects of this disclosure is shown.

[0203] Measurements may include, for example, inter-heart interval (IBI), physical activity level (intensity, duration, time), skin temperature, current time and time zone, ambient light exposure, mental load, and food intake. Derived attributes may include, for example, heart rate, resting heart rate, respiratory rate, sleep stage, sleep duration, bedtime, and activity preference. Even further derived attributes may include sleep midpoint, sleep latency, spontaneous awakening time, circadian rhythm type (morning / evening), sleep drive curve, synchronicity index, readiness, circadian rhythm, circadian rhythm alertness curve, and drowsiness index. In some embodiments, alertness data may be obtained in part based on one or more of these measurements and attributes.

[0204] A method is described. This method may include: receiving baseline physiological data associated with a user from at least one wearable device; obtaining a user-associated physiological baseline based at least in part on the user-associated baseline physiological data, the physiological baseline providing reference user alertness data; receiving additional physiological data associated with the user from said at least one wearable device; obtaining current user alertness data based at least in part on the user-associated additional physiological data; identifying triggering conditions for providing user-associated physiological state-related insights related to a travel event involving at least one mode of transportation, based at least in part on a comparison between said current user alertness data and said reference user alertness data; and causing the user device to provide user-associated physiological state-related insights.

[0205] An apparatus is described. The apparatus 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 receive baseline physiological data associated with a user from at least one wearable device; to obtain a user-associated physiological baseline based at least in part on the user-associated baseline physiological data, the physiological baseline providing reference user alertness data; to receive additional physiological data associated with the user from the at least one wearable device; to obtain current user alertness data based at least in part on the user-associated additional physiological data; to identify triggering conditions for providing user-associated physiological state-related insights related to travel events involving at least one mode of transportation, based at least in part on a comparison between the current user alertness data and the reference user alertness data; and to cause the user device to provide user-associated physiological state-related insights.

[0206] A non-transitory computer-readable medium storing code is described. The code may include processor-executable instructions to: receive baseline physiological data associated with a user from at least one wearable device; obtain a physiological baseline associated with the user, at least in part based on the baseline physiological data associated with the user, the physiological baseline providing reference user alertness data; receive additional physiological data associated with the user from said at least one wearable device; obtain current user alertness data, at least in part based on the additional physiological data associated with the user; identify triggering conditions for providing physiological state-related insights associated with the user in relation to a travel event involving at least one mode of transportation, at least in part based on a comparison between said current user alertness data and said reference user alertness data; and cause the user device to provide physiological state-related insights associated with the user.

[0207] In some examples of the methods, apparatuses and non-transitory computer-readable media described herein, identifying trigger conditions also includes identifying trigger conditions when the current user alertness data differs from the reference user alertness data by a predetermined threshold amount.

[0208] In some examples of the methods, apparatuses, and non-transitory computer-readable media described herein, the travel event is a future travel event.

[0209] In some examples of the methods, apparatuses, and non-transitory computer-readable media described herein, the travel event is the current travel event.

[0210] In some examples of the methods, apparatuses and non-transitory computer-readable media described herein, additional physiological data includes acceleration sensor data, and the identification of a user driving at least one vehicle is based at least in part on a comparison between the acceleration sensor data and reference acceleration sensor data; and the detection of a travel event is based at least in part on the comparison.

[0211] Some examples of the methods, apparatuses, and non-transitory computer-readable media described herein may also include operations, features, means, or instructions for establishing a valid local communication link between a user equipment and at least one vehicle; and for detecting travel events based at least in part on the existence of a valid local communication link between the user equipment and at least one vehicle.

[0212] Some examples of the methods, apparatuses, and non-transitory computer-readable media described herein may also include operations, features, means, or instructions for receiving satellite positioning data from a user equipment; and for detecting travel events based at least in part on satellite positioning data from the user equipment.

[0213] Some examples of the methods, apparatuses, and non-transitory computer-readable media described herein may also include operations, features, means, or instructions for sending instructions to at least one wearable device in response to the detection of a travel event to transmit physiological data at a preset rate.

[0214] Examples of the methods, apparatuses, and non-transitory computer-readable media described herein may also include sending physiological state-related insights to the operation, characteristics, means, or instructions of at least one vehicle via an effective local communication link between a user device and at least one vehicle.

[0215] Examples of the methods, apparatuses, and non-transitory computer-readable media described herein may also include operations, features, means, or instructions for enabling a user device's graphical user interface to display insights related to physiological states.

[0216] Some examples of the methods, apparatuses, and non-transitory computer-readable media described herein may also include operations, features, means, or instructions for enabling a user device to provide at least one of auditory, tactile, and visual alarms related to insights into physiological states.

[0217] Some examples of the methods, apparatuses, and non-transitory computer-readable media described herein may also include operations, features, means, or instructions for receiving user-related vehicle data from at least one vehicle, wherein the user-related vehicle data includes user behavior data collected during a travel event and identifies triggering conditions based at least in part on the user-related vehicle data.

[0218] Examples of the methods, apparatus, and non-transitory computer-readable media described herein may also include operations, features, means, or instructions for receiving meteorological data associated with a travel event; determining, based on the meteorological data associated with the travel event, that the meteorological data associated with the travel event affects the travel event; and identifying triggering conditions based at least in part on the meteorological data.

[0219] Some examples of the methods, apparatuses, and non-transitory computer-readable media described herein may also include operations, features, means, or instructions for receiving calendar data associated with a travel event; determining, based on the calendar data associated with the travel event, that the travel event is a future travel event; and identifying triggering conditions based at least in part on the determination result.

[0220] Some examples of the methods, apparatuses, and non-transitory computer-readable media described herein may also include operations, features, means, or instructions for receiving satellite positioning data associated with a travel event from a user equipment; determining, based on the satellite positioning data associated with the travel event, that the travel event is related to a route that the user has not traveled; and identifying triggering conditions based at least in part on the determination result.

[0221] Examples of the methods, apparatus, and non-transitory computer-readable media described herein may also include operations, features, means, or instructions for receiving route planning data associated with a travel event; and for identifying triggering conditions based at least in part on the route planning data.

[0222] The description herein, taken in conjunction with the accompanying drawings, illustrates exemplary configurations but does not represent all implementable or within the scope of the claims. The term "exemplary" as used herein means "serving as an example, instance, or illustration," not "preferred" or "superior to other examples." The detailed description includes specific details intended to provide an understanding of the techniques described. However, these techniques can be implemented without these specific details. In some cases, well-known structures and devices are shown in block diagram form to avoid obscuring the concept of the described examples.

[0223] In the accompanying drawings, similar parts or features may have the same reference numerals. Furthermore, various parts of the same type can be distinguished by adding a dash and a second reference numeral after the reference numeral, which is used to differentiate similar parts. If only the first reference numeral is used in the description, the description applies to any similar part having the same first reference numeral, regardless of the second reference numeral.

[0224] The information and signals described herein can be represented using a variety of different techniques and methods. For example, the data, instructions, commands, information, signals, bits, symbols, and chips mentioned throughout the foregoing description can all be represented by voltage, current, electromagnetic waves, magnetic fields or particles, light fields or particles, or any combination thereof.

[0225] The various illustrative blocks and modules described herein can be implemented or performed using general-purpose processors, DSPs, ASICs, FPGAs or other programmable logic devices, discrete gate or transistor logic, discrete hardware components, or any combination designed to perform the functions described herein. A general-purpose processor may be a microprocessor, but alternatively, it may be any conventional processor, controller, microcontroller, or state machine. The processor may also be implemented as a combination of computing devices (e.g., a combination of a DSP and a microprocessor, multiple microprocessors, one or more microprocessors combined with a DSP core, or any other such configuration).

[0226] The functions described herein may be implemented in hardware, processor-executed software, firmware, or any combination thereof. If implemented in processor-executed software, these functions may be stored or transmitted as one or more instructions or code on a computer-readable medium. Other examples and implementations are within the scope of this disclosure and the appended claims. For example, due to the nature of software, the above-described functions may be implemented using processor-executed software, hardware, firmware, hardwired, or any combination thereof. Features implementing the functions may also be physically located in various locations, including being distributed such that some functions are implemented in different physical locations. Furthermore, as used herein (including in the claims), the word “or” used in a list of items (e.g., a list of items beginning with phrases such as “at least one” or “one or more”) indicates a list of inclusions, such that 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). Furthermore, as used herein, the phrase “based on” should not be construed as referring to a closed set of conditions. For example, an exemplary step described as “based on condition A” may be based on conditions A and B without departing from the scope of this disclosure. In other words, as used in this article, the phrase “based on” should be interpreted in the same way as the phrase “at least partially based on”.

[0227] Computer-readable media includes both non-transitory computer storage media and communication media, encompassing any medium that facilitates the transfer of computer programs from one place to another. Non-transitory storage media can be any available medium accessible to a general-purpose or special-purpose computer. By way of example, and not limitation, non-transitory computer-readable media can include RAM, ROM, electrically erasable programmable ROM (EEPROM), optical disc (CD) ROM or other optical disc storage, disk storage or other magnetic storage devices, or any other non-transitory medium that can be used to carry or store desired program code 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. Similarly, any connection is appropriately referred to as computer-readable media. For example, if software is transmitted from a website, server, or other remote source using coaxial cable, fiber optic cable, twisted pair, digital subscriber line (DSL), or wireless technologies such as infrared, radio, and microwave, then coaxial cable, fiber optic cable, twisted pair, DSL, or wireless technologies such as infrared, radio, and microwave are included in the definition of media. The disks and optical discs used in this article include CDs, laser discs, optical discs, digital versatile discs (DVDs), floppy disks, and Blu-ray discs, where disks typically reproduce data magnetically, while optical discs reproduce data optically using lasers. Combinations of the above are also included within the scope of computer-readable media.

[0228] The description herein is intended to enable those skilled in the art to make or use this disclosure. Various modifications to this disclosure will be apparent to those skilled in the art, and the general principles defined herein may be applied to other variations without departing from the scope of this disclosure. Therefore, this disclosure is not limited to the examples and designs described herein, but should be given the broadest protection scope consistent with the principles and novel features disclosed herein.

Claims

1. A method for providing insights related to a user's physiological state, comprising: Receive baseline physiological data associated with the user from at least one wearable device; A physiological baseline associated with the user is obtained, at least in part, based on the baseline physiological data associated with the user, which provides reference user alertness data; Receive additional physiological data associated with the user from the at least one wearable device; The current user alertness data is obtained at least in part based on the additional physiological data associated with the user; Based at least in part on a comparison between the current user alertness data and the reference user alertness data, triggering conditions for providing physiological state-related insights associated with the user are identified, the physiological state-related insights being related to travel events involving at least one mode of transportation; and Use user devices to provide insights related to the physiological state associated with the user.

2. The method according to claim 1, wherein identifying the triggering condition further comprises: The trigger condition is identified when the current user alertness data differs from the reference user alertness data by a predetermined threshold amount.

3. The method according to claim 1, wherein the travel event is a future travel event.

4. The method according to claim 1, wherein the travel event is the current travel event.

5. The method of claim 4, wherein the additional physiological data includes accelerometer data, and the method further comprises: The user is identified as driving the at least one vehicle based at least in part on a comparison between the acceleration sensor data and reference acceleration sensor data. and The travel event is detected at least in part based on the comparison.

6. The method according to claim 4, further comprising: Establish an effective local communication link between the user equipment and the at least one vehicle; and The travel event is detected at least in part based on the existence of a valid local communication link between the user equipment and the at least one vehicle.

7. The method according to claim 4, further comprising: Receive satellite positioning data from the user equipment; and The travel event is detected based at least in part on the satellite positioning data from the user device.

8. The method according to claim 5, further comprising: In response to the detection of the travel event, an instruction is sent to the at least one wearable device to transmit the physiological data at a preset rate.

9. The method of claim 6, wherein enabling the user equipment to provide the physiological state-related insights associated with the user comprises sending the physiological state-related insights to the at least one vehicle via the effective local communication link between the user equipment and the at least one vehicle.

10. The method of claim 1, wherein enabling the user device to provide the physiological state-related insights associated with the user comprises enabling the graphical user interface of the user device to display the physiological state-related insights.

11. The method of claim 1, wherein enabling the user device to provide the physiological state-related insight associated with the user includes enabling the user device to provide at least one of an auditory alarm, a tactile alarm, and a visual alarm associated with the physiological state-related insight.

12. The method according to claim 3, further comprising: Receive vehicle data associated with the user from the at least one means of transportation, wherein the vehicle data associated with the user includes user behavior data collected during the travel event. Identifying the triggering condition includes identifying the triggering condition based at least in part on the vehicle data associated with the user.

13. The method according to claim 1, further comprising: Receive meteorological data associated with the travel event; The impact of the meteorological data associated with the travel event on the travel event is determined based on the meteorological data associated with the travel event. and Identifying the triggering conditions includes identifying the triggering conditions based at least in part on the meteorological data.

14. The method according to claim 1, further comprising: Receive calendar data associated with the travel event; Based on calendar data associated with the travel event, it is determined that the travel event is a future travel event; and Identifying the triggering condition includes identifying the triggering condition based at least in part on the determination.

15. The method according to claim 1, further comprising: Receive satellite positioning data associated with the travel event from the user equipment; Based on the satellite positioning data associated with the travel event, it is determined that the travel event is related to a route that the user has not traveled. and Identifying the triggering condition includes identifying the triggering condition based at least in part on the determination.

16. The method according to claim 1, further comprising: Receive route planning data associated with the travel event; Identifying the triggering conditions includes identifying the triggering conditions based at least in part on the route planning data.

17. An apparatus for providing insights related to a user's physiological state, the apparatus comprising: processor; as well as Memory coupled to the processor; as well as Instructions stored in memory and executable by the processor, the instructions causing the device to perform the following operations: Receive baseline physiological data associated with the user from at least one wearable device; A physiological baseline associated with the user is obtained, at least in part, based on the baseline physiological data associated with the user, which provides reference user alertness data; Receive additional physiological data associated with the user from the at least one wearable device; The current user alertness data is obtained at least in part based on the additional physiological data associated with the user; Based at least in part on a comparison between the current user alertness data and the reference user alertness data, triggering conditions for providing physiological state-related insights associated with the user are identified, the physiological state-related insights being related to travel events involving at least one mode of transportation; and Use user devices to provide insights related to the physiological state associated with the user.

18. A non-transitory computer-readable medium storing code, said code comprising instructions executable by a processor to: Receive baseline physiological data associated with the user from at least one wearable device; A physiological baseline associated with the user is obtained, at least in part, based on the baseline physiological data associated with the user, which provides reference user alertness data; Receive additional physiological data associated with the user from the at least one wearable device; The current user alertness data is obtained at least in part based on the additional physiological data associated with the user; Based at least in part on a comparison between the current user alertness data and the reference user alertness data, triggering conditions for providing physiological state-related insights associated with the user are identified, the physiological state-related insights being related to travel events involving at least one mode of transportation; and Use user devices to provide insights related to the physiological state associated with the user.

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