Event feedback using a small form factor wearable electronic device

Abstract

Wearable electronic device may include a processor, a photoplethysmography sensor and an accelerometer each coupled to the processor. At least one of the photoplethysmography sensor and the accelerometer extract biological signals. The processor, based on the extracted biological signals, is operable to determine one or more sleep conditions indicative of abnormal sleep. The processor is operable to generate an alert for the one or more sleep conditions indicative of abnormal sleep, and the alert is communicated to a medical professional.

Description

Attorney Docket No. 085150-862967EVENT FEEDBACK USING A SMALL FORM FACTOR WEARABLE ELECTRONIC DEVICECROSS-REFERENCE TO RELATED APPLICATIONS

[0001] This application claims the benefit of, and priority to, U.S. Provisional Patent Application Serial No.: 63 / 709,225 filed October 18, 2024, the entire contents of which are incorporated by reference in entirety for all purposes.TECHNICAL FIELD

[0002] The field of the disclosure relates generally to a wearable electronic device that is configured to provide event feedback for sleep disorders.BACKGROUND

[0003] Many sleep disorders are characterized by events that disrupt normal sleep. For example, in sleep apnea, airflow is disrupted either through obstruction or nervous-system related issues. In hypersomnia, sleep onset occurs extremely rapidly whether the individual is taking a nap or setting for the night. Other disorders, such as narcolepsy, are related to the duration and frequency of sleep stages (for example, time spent in Rapid Eye Movement (REM) sleep at various times during the sleep cycles). Individuals exhibiting or suffering from such sleep disorders previously were diagnosed with a single sleep test at a diagnostic facility.BRIEF DESCRIPTION OF DRAWINGS

[0004] The following drawings form part of the present specification and are included to further demonstrate certain aspects of the present disclosure. The disclosure may be better understood by reference to one or more of these drawings in combination with the detailed description of specific examples presented herein.

[0005] FIG. 1 illustrates an example wearable electronic device, in accordance with an example of this disclosure;

[0006] FIG. 2 illustrates a block diagram of a wearable electronic device, for example, as shown in FIG. 1, in accordance with an example of this disclosure;Attorney Docket No. 085150-862967

[0007] FIG. 3 illustrates a diagram of a system for monitoring and treating sleep disorders, in accordance with an example of this disclosure;

[0008] FIG. 4 illustrates a method of monitoring and treating sleep disorders using a wearable electronic device, in accordance with example of this disclosure; and

[0009] FIG. 5 illustrates another method for detecting abnormal sleep using a wearable electronic device in accordance with one example.

[0010] Corresponding reference characters indicate corresponding parts throughout the several views of the drawings. Although specific features of various examples may be shown in some drawings and not in others, this is for convenience only. Any feature of any drawing may be referenced or claimed in combination with any feature of any other drawing.

[0011] Some structural or method features may be shown in specific arrangements and / or orderings in the drawings. However, it should be appreciated that such specific arrangements and / or orderings may not be required. Rather, in some examples, such features may be arranged in a different manner and / or order than shown in the illustrative figures. Additionally, the inclusion of a structural or method feature in a particular figure is not meant to imply that such feature is required in all examples, and, in some examples, it may not be included or may be combined with other features.DETAILED DESCRIPTION

[0012] The following detailed description and examples set forth materials, components, and procedures used in accordance with the present disclosure. This description and these examples, however, are provided by way of illustration only, and nothing therein shall be deemed to be a limitation upon the overall scope of the present disclosure. Reference will now be made in detail to examples and aspects illustrated in the accompanying drawings.

[0013] As used herein, an element or step recited in the singular and proceeded with the word “a” or “an” should be understood as not excluding plural elements or steps unless such exclusion is explicitly recited. Furthermore, references to “one example” of the disclosure or an “example” are not intended to be interpreted as excluding the existence of additional examples that also incorporate the recited features. Likewise, limitations associated with “one example” or “an example” should not be interpreted as limiting to all examples unless explicitly recited.

[0014] Disjunctive language such as the phrase “at least one of X, Y, or Z,” unless specifically stated otherwise, is generally intended, within the context presented, to discloseAttorney Docket No. 085150-862967 that an item, term, etc. may be either X, Y, or Z, or any combination thereof (e.g., X, Y, and / or Z). Likewise, conjunctive language such as the phrase “at least one of X, Y, and Z,” unless specifically stated otherwise, is generally intended, within the context presented, to disclose at least one of X, at least one of Y, and at least one of Z. Real time as used herein can be less than one minute. In other examples, real time can be less than two seconds. In other examples, real time can be less than one second. A medical professional as used herein can refer to a doctor, a nurse, or other trained medical professional that has a license.

[0015] Although modern sleep medicine understands a wide variety of disorders that affect normal, healthy sleep, many of the diagnostic tools used by physicians in diagnosing sleep disorders rely on only a single measurement. For example, a single night in a sleep lab, or an at-home sleep test (HST) that is used for only one night. Unfortunately, single measurements are subject to many biases including modified sleep environments (minimally from wearing the equipment used to measure sleep, or as severe as sleeping in a lab in a completely different bed, room, etc.), differences in total sleep time, delayed sleep onset / sleep schedule, differences in the quantity of rapid eye movement (REM) sleep, varying periods of nighttime wakefulness, unstable REM latency, and variations in pre-sleep patient behaviors. While such measurements can still be useful, they don’t provide long term monitoring of treatment efficacy. It is also extremely difficult for physicians to correctly adjust dosages, titration, etc., since physicians have little data since single measurements are taken months or years apart. Currently known wearable devices and sensors merely track a subset of possible sleep disorder events described above. Moreover, current devices struggle to provide real time tracking and reporting of these sleep disorder events and do not support prediction of a sleep disorder or sleep event based on real time tracking.

[0016] The wearable electronic devices (e.g., wearable electronic device 100 or 200 described below) of this disclosure provide continuous monitoring of a user to provide measurements of sleep events over a plurality of sleep cycles or nights, which can be conducted from a user's home or any other location. Many sleep events such as transitions between sleep stages (slow wave, deep, REM, awake), respiratory effort events, oxygen desaturation events, involuntary leg movements due to neural issues, nocturnal scratch, and excessive tossing and turning can all be measured using a variety of wearable sensors discussed in more detail with reference to FIG. 2.Attorney Docket No. 085150-862967

[0017] This disclosure provides control, optionally in real time, of connected devices using a small form factor wearable electronic device, such as wearable electronic device 100 illustrated in FIG. 1. A wearable electronic device in accordance with examples of this disclosure is configured for continuous and multifaceted detection of sleep disorders using one or more sensors by providing measurements or additional measurements of one or more biological signals, as described below in further detail in FIGS. 1-5, enabling diagnosing, continuing diagnosing, monitoring, and / or treating of sleep disorders. In at least one example, the present disclosure can include real time, near real time, and / or diagnosing, continuing diagnosing, monitoring, and / or treating of sleep disorders. The wearable electronic device 100 provides continuous monitoring of a user to provide measurements of sleep events over a plurality of sleep cycles or nights, which can be conducted from a user's home or any other location.

[0018] As described herein, common sleep disorders with treatment interventions that were previously diagnosed using a single point of reference, can now be more accurately diagnosed and precisely treated using the wearable electronic devices of this disclosure. The wearable electronic devices described herein are able to measure efficacy over time, and enabling adjustment of the intensity or type of treatment in an optimal way. Since the wearable electronic device of this disclosure provides tracking and additional measurements, treatments of sleep disorders may be adjusted or provided in quicker, earlier increments compared to prior single measurement (e.g., a single night evaluation) sleep disorder diagnostic methods. Additionally, the wearable electronic device of this disclosure may provide real time tracking and additional measurements, whereby treatments of sleep disorders may be adjusted or provided in real time compared to prior single measurement (e.g., a single night evaluation) sleep disorder diagnostic methods.

[0019] Moreover, a wearable electronic device, such as a wearable ring device, disclosed herein may be capable of providing, optionally real time, event feedback for sleep disorders to communicate with connected devices that either support better sleep quality, or are prescribed interventions, such as CPAP machines or oral appliances and control or adjust the prescribed interventions automatically. The wearable electronic device detects sleep events, and may provide alerts able to control connected devices for adjusting treatments or configurations and provide diagnosis of recognized sleep disorders. Connected devices may also, in turn, modify the data acquisition mode of the ring (e.g., more frequent or less frequent sampling). TheAttorney Docket No. 085150-862967 described operation of providing real time sleep events is an important benefit of the present disclosure.

[0020] Treatments for sleep disorders vary from continuous positive airway pressure (CPAP) machines that reduce the physical obstruction to breathing in apnea patients; oral appliances that change the geometry of the mouth and throat to reduce physical breathing obstructions; mattresses that are temperature controlled for better sleep and that may provide haptic, audible or temperature feedback to modify sleep timing, quality, and / or stages; surgical devices that electrically stimulate muscles in the throat or mouth to reduce breathing obstructions; environmental devices (such as thermostat, lights, noise machines, etc); and pharmaceutical drugs that directly interact with the nervous system functions. Each of these devices and pharmaceutical drugs requires dosage, titration, and / or configuration based on the severity and type of sleeping disorder. The wearable electronic device of this disclosure provides a plurality of data points (over a plurality of nights) using one or more measurements from one or more sensors of the wearable electronic device, alerting a medical professional to treat or modify treatment of an identified sleep disorder or sleep disorder event, or send an alert or instruction to a processor configured to adjust a sleep disorder treatment device (e.g., a CPAP, oral appliance, an adjustable mattress, etc.). Thus, the dosage, titration, or configuration is continuously monitored for effectiveness and / or adjusted to provide the best possible outcome for the patient.

[0021] For interventions, such as pharmacological interventions that rely on dosages, remote monitoring of the patient’s sleep events provides the necessary diagnostic support for physicians or other medical professionals to adjust dosage. For interventions, such as devicebased interventions or monitoring, the sleep events are forwarded to other devices connected to the disclosed wearable electronic device in so that interventions can be adjusted for optimal patient outcomes. In some examples, these can be done in real time. As a result, technical benefits of the disclosed wearable electronic device include, but are not limited to, long term monitoring of the patient’s sleep events that provides important information as to the efficacy of the prescribed interventions. Further, the long term, regular, and / or real time monitoring of the patient’s sleep events is extremely valuable because sleep disorders are generally comorbid with other diseases, and many of which are fatal or extremely costly to treat, causing reduced quality of life. Thus, treatment of the sleep disorders may increase the quality of life when comorbid diseases are present.Attorney Docket No. 085150-862967

[0022] FIG. 1 illustrates an example wearable electronic device 100 configured to detect a sleep disorder and / or monitor biological signals (e.g., heart rate, oxygen saturation levels, blood pressure, sweat gland activity, etc.) or movement of a user. The wearable electronic device 100 includes a device body 110 including a housing that carries, encloses, and supports both externally and internally various components (including, for example, integrated circuit chips, sensors, wireless communication devices, etc.) to provide computing and functional operations for the wearable electronic device 100. Examples of internal components are described in more detail with respect to FIG. 2 below. The components may be disposed on the outside of the housing, partially within the housing, through the housing, completely inside the housing, and the like. The housing may, for example, include a cavity for retaining components internally, holes or windows for providing access to internal components, and various features for attaching other components. The housing may also be configured to form a water-resistant or water-proof enclosure for the device body 110. For example, the housing may be formed as a single unitary body and the openings in the unitary body may be configured to cooperate with other components to form a water-resistant or water-proof barrier.

[0023] By way of a non-limiting example, the device body 110 may include components such as, but not limited to, processing units, memory, display, sensors, biosensors, speakers, microphones, haptic actuators, batteries, and so on. The wearable electronic device 100 may also include a band 112 or strap or other means for attaching to a user. In examples, as shown by example in FIG. 1, the band 112 has an annular shape with an aperture to receive a finger of a subject user, wherein the band 112 defines the device body 110 as a ring.

[0024] In an example, the wearable electronic device 100 is configured to measure events such as transitions between sleep stages (slow wave, deep, REM, awake), respiratory effort events, oxygen desaturation events, involuntary leg movements due to neural issues, nocturnal scratch, and excessive tossing and turning, etc., which can be in real time. Due to its design, functionality, and small form factor, a ring shaped wearable electronic device 100 can be worn repeatedly to provide a consistent view of treatment efficacy and long-term monitoring for dosage or titration (e.g., of a CPAP machine), and diagnostic support. Other examples of a wearable device may include a watch, a brace, or any small, portable electronic device designed to be worn on the body, often on the wrist, neck, head, or other limb or on clothing.

[0025] Additionally, the device body 110 may have one or more contact areas 114 for cognitive stress measurement for the user. By way of an example, the one or more contact areasAttorney Docket No. 085150-862967114 may be provided as one or more buttons on the sides of the device body 110. Additionally, or alternatively, one or more electrodermal activity (EDA) sensors, one or more temperature sensors, and / or one or more PPG sensors may be positioned on the bottom of the device body 110 such that these sensors come into contact with skin of the subject user or face the skin on the body for measuring various physiological and / or biological events. The electrodermal activity (EDA) sensor is configured to measure variations in skin conductance resulting from changes in sweat gland activity regulated by the autonomic nervous system of a user. By capturing fine variations in electrodermal responses, the sensor enables accurate detection and analysis of physiological arousal, stress, emotional states, and / or sleep states. This provides continuous, noninvasive monitoring beneficial for identifying patterns associated with sleep quality, disturbances, and / or potential sleep disorders.

[0026] The wearable electronic device 100 may be worn by a user or secured to the user. By way of an example, the wearable electronic device may include, but is not limited to, a ring computer, a wearable computer, a wearable watch, a wearable communication device, a wearable media player, a wearable health monitoring device, and the like. Thus, in some examples, the device body 110 may have a housing defining a disc or other shape coupled to a band or strap.

[0027] The wearable electronic device 100 may be configured for time keeping, health monitoring, sports monitoring, medical monitoring, stress monitoring, sleep monitoring, communications, navigation, computing operations, monitoring a user's physiological and / or biological signals and providing health-related information based on those signals, and / or communicating with other electronic devices or services in a wired or wireless manner. The wearable electronic device 100 may also provide alerts to the user, which may include one or more of audio, haptic, visual and / or other sensory output. The wearable electronic device 100 may be configured for detection of a sleep event or abnormal sleep condition. In at least some examples, the wearable electronic device 100 may be configured for real time detection of a sleep event or abnormal sleep condition. Real time event detection includes real time buffering, real time monitoring of stress, and / or real time detection of hypersomnia or insomnia. The wearable electronic device 100 may also display data on a display device of the wearable electronic device 100 and acquire sensor data form one or more sensors positioned at or within the wearable electronic device 100, all in real time, near real time, or at specified intervals if desired.Attorney Docket No. 085150-862967

[0028] FIG. 2 illustrates a diagram of example components of a wearable electronic device 200 according to examples of this disclosure. The components of the wearable electronic device 200 may be implemented in, for example, the wearable electronic device 100 shown in FIG. 1. The wearable electronic device 200 may include a processor 202, and an emitter 204, a detector 206, a non-transitory storage medium 208, an alert module 210, a global positioning system (GPS) module 212, an electrodermal activity (EDA) sensor 214, a photoplethysmography (PPG) sensor 216, an inertial measurement unit (IMU) 218, and / or a skin temperature sensor 220 (e.g., a thermistor 220, a resistance temperature detector, or a thermocouple, etc.) which are coupled to the processor 202. In additional examples, the wearable electronic device 200 includes an ambient temperature sensor 224 and / or an ambient light sensors 226. The processor 202 is coupled to a non-transitory storage medium 208. The wearable electronic device 200 may be coupled to an output device 222. The output device 222 may be a mobile phone, a laptop computer, a desktop computer, a cloud network computer system, a display, or any other similar device or device configured to display or present an output. In some examples, the output device 222 is a display on the device body 110 In examples, the inertial measurement unit 218 is instead an accelerometer 218. In other examples, the inertial measurement unit 218 includes an accelerometer, a gyroscope, and / or a magnetometer.

[0029] The EDA sensor 214, the PPG sensor 216, and / or the IMU inertial measurement unit 218, including an accelerometer, are configured to extract biological signals. The processor 202, based on the extracted biological signals, is operable to determine one or more sleep conditions of abnormal sleep. The processor 202 is further operable to generate an alert for the one or more sleep conditions indicative of abnormal sleep, and the alert may be communicated to a medical professional, for example, via the output device 222. In at least one example, the alert may be communicated in real time to a medical professional.

[0030] In examples, at least one of the PPG sensor 216, the accelerometer 220, the EDA sensor 214, the skin temperature sensor 220, the ambient temperature sensor 224, and / or the ambient light sensor 226 are configured to extract biological signals from a user of the wearable electronic device 200. In aspects, each of the photoplethysmography sensor, the accelerometer, the electrodermal activity sensor, the skin temperature sensor, the ambient temperature sensor, and / or the ambient light sensor ambient light sensor extract respective biological signals.Attorney Docket No. 085150-862967

[0031] The emitter 204 emits light to a tissue and the detector 206 collects an optically attenuated signal that is backscattered from the tissue as a result of the emitted light. In at least one example, the emitter 204 can be configured to emit at least three separate wavelengths of light. In another example, the emitter 204 may be configured to emit at least three separate bands or ranges of wavelengths. In at least one example, the emitter 204 may include one or more light emitting diodes (LEDs). The emitter 204 may also include a light filter. The emitter 204 may include a low-powered laser, LED, or a quasi-monochromatic light source, or any combination thereof. The emitter may emit light ranging from infrared to ultraviolet light. As described in further detail below, the present disclosure uses Near-Infrared Spectroscopy (NIRS) as a primary example and the other types of light can be implemented in other examples and the description as it relates to NIRS does not limit the present disclosure in any way to prevent the use of the other wavelengths of light.

[0032] The data generated by the detector 206 may be processed by the processor 202, such as a computer processor, according to instructions stored in the non-transitory storage medium 208 coupled to the processor. Similarly, the biological signals or data extracted by the EDA sensor 214, the PPG sensor 216, and / or the inertial measurement unit 218 may be processed by the processor 202 according to instructions stored in the non-transitory storage medium 208 coupled to the processor. The processed data can be communicated to the output device 222 for storage or display to a user. The displayed processed data may be manipulated by the user using control buttons or touch screen controls on the output device 222 or on the device body 110. The processor 202, based on the extracted biological signals, is configured to generate a diagnosis of one or more sleep disorders. The one or more sleep disorders includes, but is not limited to, sleep apnea, insomnia, narcolepsy, circadian phase disorder, and / or shift work disorder.

[0033] The wearable electronic device 200 may include an alert module 210 configured to generate an alert. The processor 202 may send the alert to the output device 222 or the alert module 210 may send the alert directly to the output device 222. The processor 202 is operable to generate an alert for the one or more sleep disorders, and the alert may be communicated to a medical professional (see FIG. 3). In at least one example, the wearable electronic device 200 may be configured so that the processor 202 is configured to generate an alert to the output device 222 without the device including an alert module 210. The alert may include one or more, and / or a plurality of each of: a text message, email, audible alert (e.g., a beep or siren),Attorney Docket No. 085150-862967 flashing light, haptic feedback, and / or vibration. For example, the alert may be a vibration of the wearable electronic device 200 or of the output device 222. In other examples, the alert may be a light flashing from the output device 222 or a light in a room where the user is located. Text messages, emails and other alerts may be communicated both to the user, a medical professional, or other pre-determined person (e.g., a user's family member or caretaker).

[0034] In examples, the processor 202 is operable to generate a real time alert for one or more sleep conditions indicative of abnormal sleep, and the real time alert may be communicated to a medical professional or a user. The PPG sensor 216, the EDA sensor 214, the IMU 218, the ambient light sensor 226, ambient temperature sensor 224, and / or the detector 206, may be configured for continuous or discontinuous (e.g., at any specified interval) monitoring of a user, whereby the processor may, in real time, detect an abnormal sleep condition and then generate the real time alert.

[0035] The alert may provide notice to a user or a medical professional, via a speaker or display on the output device 222, of a change in biological indicator conditions, sleep condition or sleep disorder, or other parameter being monitored by the wearable electronic device 200, or the alert may be used to provide an updated biological indicator level or sleep indicator level to a user. In at least one example, the alert may be manifested as an auditory signal, a visual signal, a vibratory signal, or combinations thereof. In at least one example, an alert may be sent by the processor 202 when a predetermined biological indicator event, which may be associated with a sleep disorder event or sleep condition indicative of abnormal sleep, occurs during a physical activity or rest.

[0036] In at least one example, the wearable electronic device 200 may include a GPS module 212 configured to determine geographic position and tagging the biological indicator data with location-specific information. The wearable electronic device 200 may also include an EDA sensor 214, a PPG sensor 216, an inertial measurement unit 218, and a thermistor 220. The inertial measurement unit 218 may be used to detect movement of a user during sleep. For example, the inertial measurement unit 218 may detect when a user changes from sleeping on the user's back to the user's stomach, or unintended or involuntary movement of a limb. In other aspects, the inertial measurement unit 218 may be used to measure, for example, gait performance of a runner or pedal kinematics of a cyclist, as well as physiological parameters of a user during a physical activity in addition to the user's activity while sleeping. The EDA sensor 214, the PPG sensor 216, inertial measurement unit 218, and skin temperature sensorAttorney Docket No. 085150-862967220 may also serve as independent sensors configured to independently measure parameters of a physiological threshold. The wearable electronic device 200 may also include other types of sensors not described herein.

[0037] Event detection is accomplished by using the aforementioned sensors to collect raw data in the form of biological signals. The event detection may be done in real time. As will be discussed in further detail below, sleep events including normal or abnormal sleep conditions, includes, but is not limited to cardiac stress events, respiratory effort events, blood oxygen desaturation events, ANS activation events, body positioning, transitioning and movement events, and / or snoring events.

[0038] By way of an example, the EDA sensor is used to measure autonomous nervous system (ANS) activation in real time (real time stress patent). Further, heart rate variability and pulse rate in real time (hypersomnia patent) are measured or monitored using a combination of raw data from the PPG and accelerometer sensors, while sleep onset (hypersomnia patent) is measured or monitored using a combination of raw data from PPG, accelerometer, EDA and / or skin temperature sensors.

[0039] In an example, sleep events of interest include one or more of: (i) detection of sleep stages (slow wave, deep, REM, awake) and transitions between them; (ii) detection of cardiac stress events; (iii) detection of blood deoxygenation events; (iv) detection of respiratory effort events; (v) detection of ANS activation; (vi) detection of body position and transitions between body positions; (vii) detection of involuntary movements; and / or (viii) detection of snoring events. Subsets of these sleep events satisfy the diagnostic criteria for a wide variety of sleep disorders that have known and effective treatments. Devices connected to the disclosed wearable electronic device is used to improve the sleep environment or directly prevent certain disordered sleep events (e.g. obstructive apnea) based upon adjusting the connected device based upon real time monitoring data of these sleep events.

[0040] By way of an example, an obstructive apnea patient using a CPAP machine can have the amount of positive airway pressure adjusted (called titration). If the pressure is too low, the obstruction to the airway will not be removed and apneic events will continue to occur. However, if this is known, the CPAP machine can gradually increase the pressure until an optimal number of events is obtained. In some cases, the patient’s sleep is also disrupted by the presence of the positive airway pressure. Especially at first use of a CPAP machine, sleep is generally disrupted. If the initial pressure setting is too high, then the patient may abandon theAttorney Docket No. 085150-862967CPAP machine altogether because it is too uncomfortable. Conversely, if the CPAP machine is started at a low pressure, it is less disruptive, and the patient can get used to it over time. Once the initial discomfort from wearing the CPAP mask is no longer sleep disruptive, positive airway pressure can be increased gradually in a way that does not disrupt regular sleep patterns. If only breathing disruptions are known, an optimal titration cannot be achieved because of lack of knowledge of whether the increased pressure is causing the patient to wake up more often. However, if knowledge of sleep stages and body positions and / or movements are also known, then the knowledge can be used to adjust pressure in to ensure an optimal night rest for the patient. In at least one example, the pressure can be adjusted in real time.

[0041] Accordingly, specific adjustments may be made to the connected devices based upon real time monitoring or measurements for each sleep disorder based on knowledge of the specific disorder and the various peripheral information required to make a holistic decision for the patient’s overall health and well-being. In an example, using the means disclosed means to measure the disordered sleep events, the measured or monitored sleeps events are relayed to the other connected devices to make appropriate adjustments. The adjustments may be made by an expert based upon the monitored real time sleep disorder related events, or automatically by the connected devices or based upon instructions by the disclosed wearable electronic device in accordance with the monitored real time data of sleep events.

[0042] Further, when configured for real time alerts and real time event detection, the present disclosure makes it crucial to appropriately merge the various streams of raw sensor data (e.g., from PPG sensor 216, thermistor 220, EDA sensor 214, etc.) in real time, also referenced herein as real time buffering. A real-time buffer provides an appropriate window of raw data for processing.

[0043] Sleep stage detection is required to determine whether the subject is asleep or awake. Once the sleep windows (portions in time where the subject is asleep) are known, the sleep stages (slow wave, deep, REM) can be obtained. The sleep window is readily obtained in real time based on whether the most recent detected event was a sleep onset, or a wake onset. Further, within those windows where the user is known to be asleep may be determined using a device and method for obtaining real time heart rate variability (HRV).

[0044] Sleep onset is identified by analyzing multiple sensor signals, including detecting “shark-fin” shaped rises in skin temperature, using the skin temperature sensor (e.g., thermistor 220), long-term decay regions in galvanic skin conductance using the EDA sensor 214,Attorney Docket No. 085150-862967 elevated heart-rate variance (HRV) from the PPG sensor 216, and periods of low acceleration from the inertial measurement unit 218. A sleep onset candidate is determined when at least two of these features overlap in time. The precise moment of sleep onset may be marked at the inflection point at the base of the shark-fin temperature feature, and candidates not followed by sustained low motion may be discarded. When multiple candidates are found within a set window, their mean time is used as the final sleep onset timestamp.

[0045] Cardiac Stress Events

[0046] When oxygen availability changes, there are subtle changes in the blood pressure wave morphology due to the increased stress placed on the heart due to oxygen availability. The effects of this stress become more pronounced as the oxygen saturation decreases. A method for measuring cardiac stress using the morphology of the blood pressure wave is disclosed.

[0047] The raw PPG data provides an averaged view of the blood pressure wave at the attachment point. It is composed of the arterial (larger) wave and the venous (smaller) reflection wave. The intersection of these two is separated in time due to the travel time of the blood pressure wave before the reflected wave returns to the same measurement point. The characteristic notch between these two waves holds important information about the blood pressure and cardiac stress. For example, the width of the arterial wave in time (at a fixed heart rate) changes as a function of cardiac stress. The amplitude of the arterial wave (at fixed heart rate, for neighboring waves) changes as a function of cardiac stress. The phase shift between arterial and venous waves changes as a function of cardiac stress.

[0048] While measuring such small changes in waveforms is difficult, especially when a continuous metric for cardiac stress is the target, a method is disclosed herein to obtain a continuous metric for cardiac stress. The method includes performing a convolution of the single heart beat of PPG using a continuous wavelet (e.g. Gabor), separating the convolution into the low frequency and high frequency (detail) components, by keeping the low frequency components as part of a final vector representing the heart beat, performing the convolution on the detail components and again separating out the low frequency components and combining them with the ones at the previous level, and continuing these operations until no detail coefficients are left.

[0049] The final vector representing the heart beat is the combination of all the low frequency components. Using a gold-standard dataset of extremely high quality, high sample rate PPG waveforms as a reference, a similarity score between the gold-standard and the current heartAttorney Docket No. 085150-862967 beat is computed. The similarity score, in some examples, can just be the autocorrelation between the two final vectors from the convolutional cascade. The heart beats must be personalized for each subject (or a patient or a user). The first stream of PPG heartbeat waveforms is used to create a pool of heart beats for the user. If a higher quality heart beat is found (e.g., a heart beat having a higher similarity to the gold standard), then the higher quality heart beat replaces one of lower quality heart beats until a pool of high quality heart beats for that user is obtained. Cardiac stress is then defined by, or computed using, the similarity of heart beats to the unstressed, reference heart beats for that subject.

[0050] Blood Oxygen Desaturation Events

[0051] Oxygen desaturation events occur when there is a decrease in blood oxygen that exceeds 3%, as defined by the American Academy of Sleep Medicine (AASM). Techniques to obtain peripheral blood oxygen levels are known in which the ratios of PPG counts on the red (R) and infrared (IR) channels are used. Oxygenated versus deoxygenated hemoglobin have different extinction rates at different wavelengths, accordingly, a swap for red versus infrared is used so that the ratio of the two corresponds to blood oxygen level.

[0052] In some examples, to obtain a real time peripheral blood oxygen value, a single window of raw PPG data is obtained. The single window of raw PPG data is obtained using real time buffering. After detecting heart beats within the red and infrared (R / IR) channels independently, the collection of heart beats in each channel is filtered to include only those high-quality heart beats in the absence of motion or other signal degrading artifacts. When both channels have high-quality beats occurring at the same time, then the ratio of PPG counts provides peripheral blood oxygenation. As described herein, changes in the relative (ratios of) ratios in the multispectral tissue reflectance spectra are also indicative of changes in the blood pressure dynamics, which may be correlated to specific sleep disorders and other sleep disordered events. Further, using the signal processing techniques, places where the peripheral blood oxygen level changes that occur by more than 3% over time may be identified, which corresponds with a real time blood oxygen desaturation event.

[0053] Respiratory Effort Events

[0054] In an example, two different methods may be used to detect independent measures of respiratory effort events. The methods rely on the coupling between respiration and the subsequent dynamics of the heart (or heart beat). Heartbeat dynamics change in two ways based on respiratory effort, for example, (i) when a person stops breathing (or airflow is reduced),Attorney Docket No. 085150-862967 phase shifts are introduced in the regularity of the heart beats, and (ii) cardiac stress events as described herein. The phase shifts may be analyzed using cardiopulmonary coupling.

[0055] Once a continuous measure for cardiac stress is available, a fit of a nonlinear function to the cardiac stress in a real time, windowed fashion may be obtained. As described herein, locations within the real time cardiac stress window are found where a “tent” shape occurs. The tent shape happens due to the increased stress placed on the heart (exponential increase), followed by an exponential decrease when the stressor subsides. Two non-linear, exponential functions are fitted to the cardiac stress rise and fall, and the slope parameter of the exponential fits is recorded.

[0056] A probability vector is created by normalizing the slope parameters as a function of time. Larger slope parameters may indicate a more drastic exponential increase in cardiac stress. Plotting the normalized slope of the exponential fits to cardiac stress events creates a characteristic plot that has a noise floor with prominent peaks at the larger, more stressful events that correspond with respiratory effort events.

[0057] Since the body is a dynamic system and the heart is responding to many cues from the environment, nervous system, etc., continuously, minor stressors on the heart due the environment are handled dynamically and still show up in the typical mode of a cognitive stress event. However, a lack of oxygen is a severe stress event compared to the normal stresses placed on the heart, the cardiac stress response is much higher.

[0058] ANS Activation Events

[0059] Stress events related to autonomic nervous system (ANS) activation may be detected in real time. Real-time detection of stress events related to autonomic nervous system (ANS) activation is accomplished by analyzing electrodermal activity (EDA) sensor data for evaporation events. Macro scale evaporation events are the most important for identifying stress, occurring over periods of 5 to 20 minutes depending on severity. Regions of actual cognitive stress can be identified by combining rise and fall characterizations in the EDA signal and may be classified as low, medium, or high stress using decay constants and a number and slope of rise fits. Detection includes identifying regions of long-term ANS evaporation in the EDA sensor data. Although there are large sections of time during sleep where there is no ANS activation, sleep onsets after wake events during the night may have very clear ANS deactivation. Also, additional ANS activation may occur during sleep due to sleep disorders orAttorney Docket No. 085150-862967 other factors. In an example, the ANS events that are detected during sleep may be correlated to sleep disorders.

[0060] Body Positions and Transitions, Movements

[0061] The accelerometer provides information about acceleration of the disclosed wearable electronic device such as, a ring, over time. When the subject wearing the ring moves during his or her sleep, either due to involuntary nervous system activation, or “rolling over” in bed, the ring also moves and that movement creates acceleration. Although there is some ambiguity at times about the orientation of the ring relative to gravity (for example, if a person lies on their back or stomach, with their palm facing away from or toward the mattress), differences between lying on the side versus on chest or back may be determined or identified.Additionally, if there is a transition between chest and back, that transition is detectable even if it is unknown directly from the accelerometer whether the person was on their chest or back. When other events (such as breathing disruptions) occur, it often becomes possible to distinguish between back and chest based on the frequency of breathing disruption events since patients with an apnea diagnosis frequently have more events when sleeping on back versus chest.

[0062] Body position is easily computed from accelerometer by computing the pitch and roll of a three-dimensional (3D) acceleration vector and thresholding the values. For large pitch and roll, the subject is on their back or chest. Smaller values indicate that they are on their side. After body position is obtained, transitions between positions are easily determined as well. Small movements unrelated to changing body position can be extracted by looking at a threshold acceleration magnitude along a known axis. Body position changes cause large changes in the accelerometer data, whereas smaller movements (such as involuntary movement of the legs) are smaller changes in data by comparison. Periodicity of the smaller movements is an important factor to consider diagnostic events. If involuntary leg movements occur as part of a sleep pathology, there will be periodicity in the small movements picked up by the hand. This periodicity is absent on other hand movements that are unrelated. Finally, for detecting nocturnal scratch events, the periodicity of the scratching is characteristic for the particular user and happens at a much faster rate than involuntary leg movements or rolling over on the mattress.

[0063] SnoringAttorney Docket No. 085150-862967

[0064] Snoring from induced vibrations may be detected in real time, for real time controlling of the connected devices for the treatment of snoring in real time. The periodic, induced vibrations from snoring are extracted from the accelerometer data from the real time buffer, for example, using frequency analysis methods.

[0065] Controlling Devices Connected to the Wearable Electronic Device

[0066] In an example, the wearable electronic device streams frames of real time raw sensor data to other devices communicatively coupled to the wearable electronic device, for example, a smartphone device using Bluetooth to communicatively coupled to the wearable electronic device. Real time buffering and combination of the sensor data thus occurs or performed on the smartphone device along with the event detection algorithms.

[0067] When an event is detected, the event type and time (along with other relevant information) is sent to the device connected to the ring. By way of an example, the event type and time along with other relevant information is communicated or transmitted to the smartphone device using a communication protocol such as, Bluetooth, Wi-Fi, 4G, 5G, 6G, a local area network, a wide area network, etc. Additionally, or alternatively, a wired communication method may also be used for transmitting the data to the connected device.

[0068] The connected device is programmed, configured, or adapted, as discussed earlier, to determine the best course of action in accordance with the event notification. In a similar implementation of this disclosure, a history of events for the current sleep session as well as previous nights of sleep data or naps can be communicated or transmitted to the smartphone device for storing on the smartphone device. Additionally, or alternatively, new events may be sent along with additional historical information and probabilities to provide additional context to the connected device (e.g., the smartphone device).

[0069] Adjusting Data Acquisition on the Ring

[0070] In an example, during an operation mode, when a connected device (e.g., a treatment device such as a CPAP machine, a light, noise machine, etc., as described below), receives a real time sleep event from the wearable electronic device 100, the connected device may transmit to the wearable electronic device a message requesting a configuration change on the wearable electronic device. Since small wearable electronic devices like rings are extremely power constrained, data is usually acquired at the lowest possible sample rate for the application. However, if a connected device requires higher accuracy or sample rates, the data acquisition configuration can be accordingly adjusted in real time. Additionally, orAttorney Docket No. 085150-862967 alternatively, methods for compressed sensing and real time adjustment of data acquisition mode adjustment for conserving power may be used for adjusting data acquisition on the wearable electronic device 100. Thus, in some examples the present disclosure can be operable to work in real time and in other examples the device can be operable to have different types of delay or waiting for connections. In some examples, this can be in terms of minutes or days.

[0071] FIG. 3 illustrates an exemplary environment for use of a wearable electronic device 100 or wearable electronic device 200. The wearable electronic device 100 may be in communication with a network device 302 (e.g., a local or cloud computing network device having dedicated processors and memory), a mobile device 304, or an alert device 306, which each are examples of the output device 222. The wearable electronic devices 100 may be in communication with a medical professional 312 via the network device 302, the mobile device 304, or the alert generator 306, or via a personal computer or other computing device of the medical professional 312. The wearable electronic device 100 may be in communication with one or more connected devices that provide biofeedback, modifies a sleep environment, and / or configures a prescribed intervention. For example, a connected device may be a treatment device 310 such as a CPAP machine, oral appliance, surgical device, or neuromuscular stimulation device. In aspects the sleep environment may be an actuatable sleeping device 308 (e.g., a mattress such as a hospital bed), or a thermostat, light, noise machine, and / or speakers.

[0072] The alert generated by the processor 202 may control a connected device that provides biofeedback, modifies the sleep environment, and / or configures a prescribed intervention. In at at least one example, the alert can be generated in real time. The prescribed intervention includes controlling one or more CPAP machines (e.g., treatment device 310), titration of a CPAP machine, oral appliances, mattresses (e.g., 308), surgical devices, neuromuscular stimulation devices, environmental devices, thermostat (e g., thermostat 316), lights (e.g., light 318), noise machines (e.g., sound device 306), and / or speakers (e.g., sound device 306), or any other device configured or capable of causing a change in a sleep condition. The processor 202 may execute instructions for control of the connected device(s) to affect input and / or output settings of the connected device related to the extracted biological signals, monitoring, or adjusting the intervention. In some examples, the control can be real time control. In some examples, insufficient or incorrect prescribed interventions are sent by the processor 202 to the medical professional as a notification or alert. For example, the alert controls a connected device including a CPAP machine, instructing the CPAP machine to change a level ofAttorney Docket No. 085150-862967 treatment by increasing or decreasing pressure from the CPAP machine. In some examples, the alert can be in real time. In aspects, the prescribed intervention is measured for efficacy using a number and kind of sleep signals.

[0073] In further examples, the connected device (e.g., the treatment device 310 such as a CPAP machine, the thermostat 316, or light 318, etc.) provides real time feedback to the processor to adjust one or more of: sensor configurations and / or sampling rates, for example, of at least one of the PPG sensor 216, the EDA sensor 214, the skin temperature sensor 220, the detector 206, the emitter 204, the inertial measurement unit 218, the ambient light sensor 226, and / or the ambient temperature sensor 224.

[0074] The wearable electronic device 200 may include a wireless communication device 322 operable to be coupled to a computer (e.g., network device 302, mobile device 304, or other personal computing device), via wireless connection. The computer (e.g., network device 302 or mobile device 304) may in turn be coupled to a connected device wherein the computer includes an additional processor operable to execute instructions for control of the connected device to affect input and / or output settings of the connected devices related to extracted biological signals, monitoring, or adjusting the intervention. In some examples, the control can be in real time.

[0075] FIG. 4 illustrates a method 400 for detecting one or more sleep disorders using a wearable electronic device (e.g., wearable electronic device 200) comprising at least one sensor. The method includes, at step 410, extracting biological signals from a user of the wearable electronic device 200. The extraction is performed using at least one of the electrodermal activity (EDA) sensor 214, the photoplethysmography (PPG) sensor 216, the inertial measurement unit (IMU) 218 (including an accelerometer), the skin temperature sensor 220, the ambient temperature sensor 224, and / or the ambient light sensor 226, each operatively coupled to the processor 202.

[0076] In aspects, the method includes detecting, via the the PPG sensor 216, volumetric changes in blood circulation within the microvascular bed of tissue by emitting light into the user's skin and measuring the amount of light either transmitted or reflected to the sensor. At step 410, the PPG sensor 216 may generate electronic signals representative of pulse waveforms, which are sampled and digitized for subsequent analysis. In some aspects, at step 410, the PPG sensor 216 and the accelerometer or inertial measurement unit 218 each extract respective biological signals.Attorney Docket No. 085150-862967

[0077] In aspects, the EDA sensor 214 is configured to detect changes in the electrical conductance of the user's skin, which are indicative of autonomic nervous system activity associated with sleep stages and arousal events. Step 410 may include extract additional respective biological signals via the EDA sensor 214, the skin temperature sensor (e.g., thermistor 220), ambient temperature sensor 224, and ambient light sensor 226.

[0078] In some examples, the method includes emitting light from the emitter 204 toward a tissue of the user and collecting, via the detector 206, an optically attenuated signal backscattered from the tissue. In some aspects, the method includes emitting, via emitter 204, at least three separate wavelengths or bands of light and collecting, via the detector 206, the resulting optical signals for further analysis.

[0079] At step 420, the biological signals are processed by the processor 202, according to instructions stored in the non-transitory storage medium 208, to identify sympathetic nervous system activity, arousal events, and / or physiological parameters. Step 420 generates data representative of physiological parameters related to sleep. Step 420 may include processing biological signals extracted by the PPG sensor 216 to extract physiological parameters such as, but not limited to, heart rate, heart rate variability, blood oxygen saturation, and / or pulse amplitude. In some examples, the processor combines features derived from PPG signals with data from other sensors to enhance the accuracy of sleep stage classification and sleep disorder detection. For example, at step 420, the processor 202 electronically may additionally process digitized EDA signals to identify patterns pertinent to a sleep disorder or abnormal sleep condition including events such as micro-arousals, stress responses, or abnormal autonomic activity that may correlate with specific sleep disorders.

[0080] At step 430, method includes analyzing the processed data, such as the hear rate, heart rate variability, blood oxygen parameters, micro-arousals, stress responses, etc., to determine one or more sleep conditions indicative of one or more sleep disorders or an abnormal sleep condition. The sleep disorders or conditions may include, but are not limited to, sleep apnea, insomnia, narcolepsy, circadian phase disorder, and / or shift work disorder.

[0081] At step 440, upon detection of a sleep disorder or abnormal sleep condition, the method generates an alert. The alert may comprise at least one of a text message, email, audible alert, visual alert, haptic feedback, or vibration. The alert is communicated to at least one of a user, a medical professional, or a pre-determined person via the output device 222.Attorney Docket No. 085150-862967

[0082] At step 450, the method includes controlling a connected device, such as a treatment device 310, an actuatable sleeping device 308, a thermostat 316, or a light 318, to provide biofeedback, modify a sleep environment, or configure a prescribed intervention based on the detected sleep disorder. The processor 202 may further receive real-time feedback from the connected device to adjust sensor configurations or sampling rates. In at least one example, the method can include controlling the connected device in real time.

[0083] The method 400 may include communicating the alert and processed data from the wearable electronic device 200 to the output device 222, which may include a mobile device, network device, or display, optionally via a wireless communication device 322. The output device 222 may in turn relay information to a medical professional or initiate further actions.

[0084] In certain examples, the method 400 further comprises tagging extracted biological data with location-specific information using a GPS module 212. The method may be performed with either continuous or discontinuous monitoring, with real-time alerts generated upon detection of abnormal sleep conditions. The method may further comprise enabling user interaction with processed data via control buttons or a touchscreen on the output device 222 or the device body.

[0085] Thus, method 400 enables comprehensive, automated detection and management of sleep disorders utilizing the integrated components and functionalities of the wearable electronic device 200.

[0086] FIG. 5 illustrates another method for detecting sleep disorders or abnormal sleep conditions using a wearable electronic device in accordance with examples of this disclosure. In block 510, method 500 extracts biological signals from a user with at least one of a photoplethysmography sensor, an accelerometer, an electrodermal activity sensor, a skin temperature sensor, an ambient temperature sensor, and / or an ambient light sensor, each coupled to a processor. In block 520, method 500 determines, by the processor and based on the extracted biological signals, one or more sleep conditions indicative of abnormal sleep. In block 530, method 500 generates, by the processor, an alert for the one or more sleep conditions indicative of abnormal sleep and communicating the alert to a medical professional. In at least one example, the alert can be generated in real time based upon real time sensor measurements. In other examples, the alert can be generated in real time, but can be based upon processing the data using pre-recorded sensor measurements.Attorney Docket No. 085150-862967

[0087] It will be understood by those skilled in the art that the method steps of method 400 and 500 described herein are not all required to be performed in every example of the disclosed method, and that certain steps may be omitted, combined, or performed in a different order without departing from the scope of the invention. The methods encompass examples in which only a subset of the described steps may be performed, as well as examples including additional, fewer, or alternative steps. For example, in method 400, the processor may rely only on extracting biological signals using the EDA sensor 214, skin temperature sensor (e.g., thermistor 220), and / or the PPG sensor 216, while in method 500, additional steps may include controlling a treatment device such as a CPAP machine. The treatment device can include others that are described herein as well as ones available after this disclosure.

[0088] In one example, a wearable ring device is disclosed. The wearable ring device includes a processor, and one or more sensors. The one or more sensors includes a photoplethysmography sensor, an accelerometer, an electrodermal activity sensor, a skin temperature sensor, an ambient temperature sensor, and / or an ambient light sensor. Each of the one or more sensors is coupled to the processor and configured to extract biological signals. The extraction of biological signals can be done in real time. The processor is operable to determine one or more sleep conditions indicative of an abnormal sleep based on the extracted biological signals.

[0089] Each of the photoplethysmography sensor, the accelerometer, the electrodermal activity sensor, the skin temperature sensor, the ambient temperature sensor, and the ambient light sensor extract respective biological signals is configured to extract respective biological signals, and the processor is operable to determine one or more sleep conditions indicative of abnormal sleep based on the extracted respective biological signals, and generate a diagnosis of one or more sleep disorders based on the extracted biological signals. The one or more sleep disorders include sleep apnea, narcolepsy, insomnia, circadian phase disorder, and / or shift work disorder.

[0090] The processor is further operable to generate an alert for sleep events, and the real time alert is communicated to one or more of: a patient, caretaker, and / or medical professional. The real time alerts control a connected device that provides biofeedback, modifies the sleep environment, and / or configures a prescribed intervention. The prescribed intervention includes one or more of CPAP machines, oral appliances, mattresses, surgical devices, neuromuscular stimulation devices, environmental devices, thermostat, lights, noise machines, and / or speakers.Attorney Docket No. 085150-862967In other examples, the alerts can be non-real time and the control can be non-real time or any combination of real time and non-real time. For example, the alert can be generated in real time, but the control of the prescribed intervention can require approval from the medical professional prior to implementation. In other examples, the alert can be provided based on connectivity of the device and the prescribed intervention can be conducted in real time such that the titration or other settings are adjust in real time. In yet other examples, the adjustment can be made in real time even if the prescribed intervention is currently not being performed on the patient at the time of the adjustment.

[0091] The processor is further operable to execute instructions for real time control of the connected device to affect input and / or output settings of the connected devices related to extracted biological signals, monitoring, or adjusting the intervention. Insufficient or incorrect prescribed interventions are sent to the prescribing physician as a notification or alert. The real time alerts include text messages, emails, audible alerts, flashing lights, haptic feedback, and / or vibration. The prescribed intervention is measured for efficacy using a number and kind of sleep signals. The connected device provides real time feedback to the processor to adjust one or more of sensor configurations and / or sampling rates.

[0092] The prescribed intervention includes one or more of CPAP machines, titration of a CPAP, oral appliances, mattresses, surgical devices, neuromuscular stimulation devices, environmental devices, thermostat, lights, noise machines, and / or speakers.

[0093] Some examples involve the use of one or more electronic processing or computing devices. As used herein, the terms “processor” and “computer” and related terms, e.g., “processing device,” and “computing device” are not limited to just those integrated circuits referred to in the art as a computer, but broadly refers to a processor, a processing device or system, a general purpose central processing unit (CPU), a graphics processing unit (GPU), a microcontroller, a microcomputer, a programmable logic controller (PLC), a reduced instruction set computer (RISC) processor, a field programmable gate array (FPGA), a digital signal processor (DSP), an application specific integrated circuit (ASIC), and other programmable circuits or processing devices capable of executing the functions described herein, and these terms are used interchangeably herein. These processing devices are generally “configured” to execute functions by programming or being programmed, or by the provisioning of instructions for execution. The above examples are not intended to limit in any way the definition or meaning of the terms processor, processing device, and related terms.Attorney Docket No. 085150-862967

[0094] The various aspects illustrated by logical blocks, modules, circuits, processes, algorithms, and algorithm steps described above may be implemented as electronic hardware, software, or combinations of both. Certain disclosed components, blocks, modules, circuits, and steps are described in terms of their functionality, illustrating the interchangeability of their implementation in electronic hardware or software. The implementation of such functionality varies among different applications given varying system architectures and design constraints. Although such implementations may vary from application to application, they do not constitute a departure from the scope of this disclosure.

[0095] Aspects of examples implemented in software may be implemented in program code, application software, application programming interfaces (APIs), firmware, middleware, microcode, hardware description languages (HDLs), or any combination thereof. A code segment or machine-executable instruction may represent a procedure, a function, a subprogram, a program, a routine, a subroutine, a module, a software package, a class, or any combination of instructions, data structures, or program statements. A code segment may be coupled to, or integrated with, another code segment or an electronic hardware by passing or receiving information, data, arguments, parameters, memory contents, or memory locations. Information, arguments, parameters, data, etc. may be passed, forwarded, or transmitted via any suitable means including memory sharing, message passing, token passing, network transmission, etc.

[0096] The actual software code or specialized control hardware used to implement these systems and methods is not limiting of the claimed features or this disclosure. Thus, the operation and behavior of the systems and methods were described without reference to the specific software code being understood that software and control hardware can be designed to implement the systems and methods based on the description herein.

[0097] When implemented in software, the disclosed functions may be embodied, or stored, as one or more instructions or code on or in memory. In the examples described herein, memory includes non-transitory computer-readable media, which may include, but is not limited to, media such as flash memory, a random-access memory (RAM), read-only memory (ROM), erasable programmable read-only memory (EPROM), electrically erasable programmable readonly memory (EEPROM), and non-volatile RAM (NVRAM). As used herein, the term “non- transitory computer-readable media” is intended to be representative of any tangible, computer- readable media, including, without limitation, non-transitory computer storage devices,Attorney Docket No. 085150-862967 including, without limitation, volatile and non-volatile media, and removable and nonremovable media such as a firmware, physical and virtual storage, CD-ROM, DVD, and any other digital source such as a network, a server, cloud system, or the Internet, as well as yet to be developed digital means, with the sole exception being a transitory propagating signal. The methods described herein may be embodied as executable instructions, e.g., “software” and “firmware,” in a non-transitory computer-readable medium. As used herein, the terms “software” and “firmware” are interchangeable and include any computer program stored in memory for execution by personal computers, workstations, clients, and servers. Such instructions, when executed by a processor, configure the processor to perform at least a portion of the disclosed methods.

[0098] In aspects, a wearable ring device is disclosed, the wearable ring device includes: a processor; a photoplethysmography sensor coupled to the processor; and an accelerometer coupled to the processor. At least one of the photoplethysmography sensor and the accelerometer extract biological signals. The processor, based on the extracted biological signals, is operable to determine one or more sleep conditions indicative of abnormal sleep. The processor is operable to generate an alert for the one or more sleep conditions indicative of abnormal sleep, and the alert is communicated to a medical professional.

[0099] In some aspects, a wearable ring device, further includes: an electrodermal activity sensor coupled to the processor; a skin temperature sensor coupled to the processor; an ambient temperature sensor coupled to the processor; and an ambient light sensor coupled to the processor. At least one of the photoplethysmography sensor, the accelerometer, the electrodermal activity sensor, the skin temperature sensor, the ambient temperature sensor, and / or the ambient light sensor extract biological signals.

[0100] In some aspects, each of the photoplethysmography sensor, the accelerometer, the electrodermal activity sensor, the skin temperature sensor, the ambient temperature sensor, and the ambient light sensor extract respective biological signals. The processor, based on the extracted respective biological signals, is operable to determine one or more sleep conditions indicative of abnormal sleep.

[0101] In some aspects, the processor, based on the extracted biological signals, generates a diagnosis of one or more sleep disorders.

[0102] In some aspects, the one or more sleep disorders include: sleep apnea, insomnia, narcolepsy, circadian phase disorder, and / or shift work disorder.Attorney Docket No. 085150-862967

[0103] In some aspects, the processor is operable to generate an alert for the one or more sleep disorders, and the alert is communicated to the medical professional.

[0104] In some aspects, in the processor is operable to generate a real time alert for the one or more sleep conditions indicative of abnormal sleep, and the real time alert is communicated to the medical professional.

[0105] In some aspects, the real time alert controls a connected device that provides biofeedback, modifies the sleep environment, and / or configures a prescribed intervention.

[0106] In some aspects, the prescribed intervention includes controlling one or more of CPAP machines, titration of a CPAP, oral appliances, mattresses, surgical devices, neuromuscular stimulation devices, environmental devices, thermostat, lights, noise machines, and / or speakers.

[0107] In some aspects, the processor executes instructions for real time control of the connected device to affect input and / or output settings of the connected device related to extracted biological signals, monitoring, or adjusting the intervention.

[0108] In some aspects, the insufficient or incorrect prescribed interventions are sent to the medical professional as a notification or alert.

[0109] In some aspects, the connected device provides real time feedback to the processor to adjust one or more of: sensor configurations and / or sampling rates.

[0110] In some aspects, the prescribed intervention is measured for efficacy using a number and kind of sleep signals.

[0111] In some aspects, the real time alerts including text messages, emails, audible alerts, flashing lights, haptic feedback, and / or vibration.

[0112] In some aspects, the real time alert controls a connected device including a CPAP machine.

[0113] In some aspects, a wearable ring device further includes a wireless communication device operable to be coupled to a computer, which is in turn coupled to a connected device. The computer includes an additional processor operable to execute instructions for real time control of the connected device to affect input and / or output settings of the connected devices related to extracted biological signals, monitoring, or adjusting the intervention.

[0114] Although certain examples have been illustrated and described herein for purposes of description, a wide variety of alternate and / or equivalent examples or implementations calculated to achieve the same purposes may be substituted for the examples shown andAttorney Docket No. 085150-862967 described without departing from the scope of the present disclosure. This application is intended to cover any adaptations or variations of the examples discussed herein, including the implementation or utilization of components of the systems or steps independently and separately from other described components or steps. Therefore, it is manifestly intended that examples described herein be limited only by the claims.

Claims

Attorney Docket No. 085150-862967CLAIMSWe claim:

1. A wearable ring device comprising: a processor; a photoplethysmography sensor coupled to the processor; an accelerometer coupled to the processor; wherein at least one of the photoplethysmography sensor and the accelerometer extract biological signals; wherein the processor, based on the extracted biological signals, is operable to determine one or more sleep conditions indicative of abnormal sleep; wherein the processor is operable to generate an alert for the one or more sleep conditions indicative of abnormal sleep, and alert is communicated to a medical professional.

2. The wearable ring device of claim 1, further comprising: an electrodermal activity sensor coupled to the processor; a skin temperature sensor coupled to the processor; an ambient temperature sensor coupled to the processor; and an ambient light sensor coupled to the processor; wherein at least one of the photoplethysmography sensor, the accelerometer, the electrodermal activity sensor, the skin temperature sensor, the ambient temperature sensor, and / or the ambient light sensor extract biological signals.

3. The wearable ring device of claim 2, wherein each of the photoplethysmography sensor, the accelerometer, the electrodermal activity sensor, the skin temperature sensor, the ambient temperature sensor, and the ambient light sensor extract respective biological signals; and the processor, based on the extracted respective biological signals, is operable to determine one or more sleep conditions indicative of abnormal sleep.

4. The wearable ring device of claim 2, wherein the processor, based on the extracted biological signals, generates a diagnosis of one or more sleep disorders.

5. The wearable ring device of claim 4, wherein the one or more sleep disorders comprise: sleep apnea, insomnia, narcolepsy, circadian phase disorder, and / or shift work disorder.Attorney Docket No. 085150-8629676. The wearable ring device of claim 4, wherein the processor is operable to generate an alert for the one or more sleep disorders, and the alert is communicated to the medical professional.

7. The wearable ring device of claim 2, wherein the processor is operable to generate a real time alert for the one or more sleep conditions indicative of abnormal sleep, and the real time alert is communicated to the medical professional.

8. The wearable ring device of claim 7, wherein the real time alert controls a connected device that provides biofeedback, modifies a sleep environment, and / or configures a prescribed intervention.

9. The wearable ring device of claim 8, wherein the prescribed intervention includes controlling one or more of CPAP machines, titration of a CPAP, oral appliances, mattresses, surgical devices, neuromuscular stimulation devices, environmental devices, thermostat, lights, noise machines, and / or speakers.

10. The wearable ring device of claim 8, wherein the processor executes instructions for real time control of the connected device to affect input and / or output settings of the connected device related to extracted biological signals, monitoring, or adjusting the intervention.

11. The wearable ring device of claim 10, wherein insufficient or incorrect prescribed interventions are sent to the medical professional as a notification or alert.

12. The wearable ring device of claim 11, wherein the connected device provides real time feedback to the processor to adjust one or more of sensor configurations and / or sampling rates.

13. The wearable ring device of claim 11, wherein the prescribed intervention is measured for efficacy using a number and kind of sleep signals.

14. The wearable ring device of claim 13, wherein the prescribed intervention includes controlling one or more of CPAP machines, titration of a CPAP, oral appliances, mattresses, surgical devices, neuromuscular stimulation devices, environmental devices, thermostat, lights, noise machines, and / or speakers.

15. The wearable ring device of claim 7, the real time alerts including text messages, emails, audible alerts, flashing lights, haptic feedback, and / or vibration.Attorney Docket No. 085150-86296716. The wearable ring device of claim 1, wherein the processor is operable to generate a real time alert for the one or more sleep conditions indicative of abnormal sleep, and the real time alert is communicated to the medical professional.

17. The wearable ring device of claim 16, wherein the real time alert controls a connected device including a CPAP machine.

18. The wearable ring device of claim 1, further comprising a wireless communication device operable to be coupled to a computer, which is in turn coupled to a connected device.

19. The wearable ring device of claim 18, wherein the computer includes an additional processor operable to execute instructions for real time control of the connected device to affect input and / or output settings of the connected devices related to extracted biological signals, monitoring, or adjusting an intervention.

20. The wearable ring device of claim 19, wherein the additional processor operable to execute instructions for real time control of the connected device to affect input and / or output settings of the connected devices related to extracted biological signals, monitoring, or adjusting the intervention.

21. The wearable ring device of claim 20, wherein insufficient or incorrect prescribed interventions are sent to the medical professional as a notification or alert.

22. A method for detecting sleep disorders using a wearable electronic device, the method comprising: extracting biological signals from a user with at least one of an electrodermal activity (EDA) sensor, a photoplethysmography (PPG) sensor, an inertial measurement unit (IMU), a skin temperature sensor, an ambient temperature sensor, and / or an ambient light sensor, each operatively coupled to a processor; detecting and digitizing skin conductance data with the EDA sensor; emitting light from an emitter toward a tissue of the user and collecting, via a detector, an optically attenuated signal backscattered from the tissue; processing the biological signals and optically attenuated signals with the processor according to instructions stored in a non-transitory storage medium;Attorney Docket No. 085150-862967 analyzing the EDA data with the processor to identify an abnormal sleep condition associated with a sleep disorder; determining, based on the processed data, a presence of one or more sleep disorders; generating and sending an alert if abnormal sleep or a sleep disorder is detected, and optionally controlling a connected device based on the detected sleep disorder.

23. A method for detecting abnormal sleep using a wearable ring device, the method comprising: extracting biological signals from a user with at least one of a photoplethysmography sensor, an accelerometer, an electrodermal activity sensor, a skin temperature sensor, an ambient temperature sensor, and / or an ambient light sensor, each coupled to a processor; determining, by the processor and based on the extracted biological signals, one or more sleep conditions indicative of abnormal sleep; and generating, by the processor, an alert for the one or more sleep conditions indicative of abnormal sleep and communicating the alert to a medical professional.

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