# US 11,992,340 B2 · Efficient wellness measurement in ear-wearable devices > Agents: this data is available as JSON from the patentgrep API and MCP server — see https://patentgrep.com/llms.txt - Number: US 11,992,340 B2 - Document ID: US11992340B2 - Status: Granted - Kind: B2 - Application number: 17/657,556 - Filed: 2022-03-31 - Published: 2022-10-06 - Granted: 2024-05-28 - Earliest claimed: 2019-02-01 - Assignees: Starkey Laboratories, Inc. - Applicants: Starkey Laboratories, Inc. - Inventors: Jingjing Xu; Justin Burwinkel; Kenneth Jensen; Jason Galster; Sahar Akram; Adriana Goyette - Web page: https://patentgrep.com/patent/US11992340B2 ## CPC - A61B 5/6815: {Ear} - H04R 25/55: {using an external connection, either wireless or wired} - A61B 5/0002: {Remote monitoring of patients using telemetry, e.g. transmission of vital signals via a communication network (endoradiosondes A61B5/07)} - A61B 5/0024: {for multiple sensor units attached to the patient, e.g. using a body or personal area network} - A61B 5/0205: Simultaneously evaluating both cardiovascular conditions and different types of body conditions, e.g. heart and respiratory condition - A61B 5/1117: {Fall detection} - A61B 5/1118: {Determining activity level} - A61B 5/165: {Evaluating the state of mind, e.g. depression, anxiety} - A61B 5/486: {Biofeedback (using electroencephalography [EEG] A61B5/375)} - A61B 5/7264: {Classification of physiological signals or data, e.g. using neural networks, statistical classifiers, expert systems or fuzzy systems} - A61B 5/7267: {involving training the classification device} - A61B 5/742: {using visual displays (displays for heart-related electrical signals, e.g. ECG, A61B5/339)} - A61B 5/746: {Alarms related to a physiological condition, e.g. details of setting alarm thresholds or avoiding false alarms} - G06N 3/08: Learning methods - G06N 3/09: Supervised learning - G06N 3/092: Reinforcement learning - G06N 20/00: Machine learning - G08B 21/0446: {worn on the body to detect changes of posture, e.g. a fall, inclination, acceleration, gait} - G16H 10/60: for patient-specific data, e.g. for electronic patient records - G16H 20/70: relating to mental therapies, e.g. psychological therapy or autogenous training - G16H 50/30: for calculating health indices; for individual health risk assessment - H04R 3/005: {for combining the signals of two or more microphones (specially adapted for hearing aids H04R25/407)} - H04R 25/554: {using a wireless connection, e.g. between microphone and amplifier or using Tcoils} - A61B 5/01: Measuring temperature of body parts {; Diagnostic temperature sensing, e.g. for malignant or inflamed tissue} (clinical contact thermometers G01K13/20) - A61B 5/024: Measuring pulse rate or heart rate - A61B 5/02438: {with portable devices, e.g. worn by the patient} - A61B 5/6817: {Ear canal} - A61B 5/7435: {Displaying user selection data, e.g. icons in a graphical user interface} - A61B 2562/0219: Inertial sensors, e.g. accelerometers, gyroscopes, tilt switches - A61B 2562/0223: Magnetic field sensors - A61N 1/36038: {Cochlear stimulation} - G06N 3/044: Recurrent networks, e.g. Hopfield networks - G06N 3/045: Combinations of networks - G06N 5/01: Dynamic search techniques; Heuristics; Dynamic trees; Branch-and-bound - G06N 7/01: Probabilistic graphical models, e.g. probabilistic networks - G06N 20/10: using kernel methods, e.g. support vector machines [SVM] - G08B 21/0492: {Sensor dual technology, i.e. two or more technologies collaborate to extract unsafe condition, e.g. video tracking and RFID tracking} - H04R 2225/55: Communication between hearing aids and external devices via a network for data exchange - H04R 2420/07: Applications of wireless loudspeakers or wireless microphones - H04R 2460/03: Aspects of the reduction of energy consumption in hearing devices - H04R 2460/07: Use of position data from wide-area or local-area positioning systems in hearing devices, e.g. program or information selection - H04R 2499/11: Transducers incorporated or for use in hand-held devices, e.g. mobile phones, PDA's, camera's - A61B: DIAGNOSIS; SURGERY; IDENTIFICATION (usefulness limited to only animals A61D) - H04R: LOUDSPEAKERS, MICROPHONES, GRAMOPHONE PICK-UPS OR LIKE ACOUSTIC ELECTROMECHANICAL TRANSDUCERS; ELECTRIC HEARING AIDS; PUBLIC ADDRESS SYSTEMS (producing sounds with frequency not determined by supply frequency G10K) - G06N: COMPUTING ARRANGEMENTS BASED ON SPECIFIC COMPUTATIONAL MODELS - G08B: SIGNALLING SYSTEMS, e.g. PERSONAL CALLING SYSTEMS; ORDER TELEGRAPHS; ALARM SYSTEMS - G16H: HEALTHCARE INFORMATICS, i.e. INFORMATION AND COMMUNICATION TECHNOLOGY [ICT] SPECIALLY ADAPTED FOR THE HANDLING OR PROCESSING OF MEDICAL OR HEALTHCARE DATA - A61N: ELECTROTHERAPY; MAGNETOTHERAPY; RADIATION THERAPY; ULTRASOUND THERAPY (measurement of bioelectric currents A61B; surgical instruments, devices or methods for transferring non-mechanical forms of energy to or from the body A61B18/00; anaesthetic apparatus in general A61M; incandescent lamps H01K; infrared radiators for heating H05B) ## Abstract A wellness evaluation system may determine, based on data generated by a first set of sensors powered by one or more batteries of one or more ear-wearable devices, that a user of the one or more ear-wearable devices is currently in an environment that includes human-directed communication signals. If so, a second set of sensors may be activated such that the one or more batteries provides an increased amount of power to the second set of sensors. Furthermore, the wellness evaluation system may determine based on data generated by the second set of sensors, whether the user has satisfied a target level of a wellness measure. If the user has not satisfied the target level of the wellness measure, the wellness evaluation system may perform an action to encourage the user to perform one or more activities to increase an achieved level of the wellness measure. ## Claims ### Claim 1 A method comprising: determining, by one or more processing circuits, based on data generated by a first set of sensors powered by one or more batteries of one or more ear-wearable devices, that a user of the one or more ear-wearable device is currently in an environment that includes human-directed communication signals, wherein a second set of sensors includes at least one sensor that is not included in the first set of sensors; in response to determining that the user is currently in the environment that includes human-directed communication signals, activating, by the one or more processing circuits, the second set of sensors and/or activating, by the one or more processing circuits, wireless streaming of data associated with the second set of sensors; determining, by the one or more processing circuits, based on the data associated with the second set of sensors, a measure of complexity of social engagement of the user; and generating, by the one or more processing circuits, a visual representation of the measure of complexity of social engagement of the user. ### Claim 2 (depends on 1) The method of claim 1, wherein the method further comprises generating, by the one or more processing circuits, a notification message that provides a tip on how to improve the complexity of social engagement of the user. ### Claim 3 (depends on 1) The method of claim 1, wherein the visual representation of the measure of complexity of social engagement of the user comprises a visual representation of a comparison of the measure of complexity of social engagement to a typical level of the measure of complexity of social engagement achieved by a population of individuals. ### Claim 4 (depends on 1) The method of claim 1, further comprising providing, by the one or more processing circuits, information regarding the measure of complexity of social engagement of the user to one or more persons other than the user. ### Claim 5 (depends on 1) The method of claim 1, further comprising: determining, by the one or more processing circuits, that the user has not satisfied a target level of the measure of complexity of social engagement of the user; and providing, by the one or more processing circuits, based on the determination that the user has not satisfied a target level of the measure of complexity of social engagement of the user, an alert that prompts a third party or an artificial intelligence companion to initiate a social interaction with the user. ### Claim 6 (depends on 1) The method of claim 1, wherein the one or more ear-wearable devices include the second set of sensors. ### Claim 7 (depends on 1) The method of claim 1, further comprising: identifying, by the one or more processing circuits, terms and phrases in speech of the user that are associated with depression or risk of self-harm. ### Claim 8 (depends on 1) The method of claim 1, wherein the batteries provide a first amount of power to a second set of one or more sensors when the second set of sensors are not activated and provide a second amount of power greater than the first amount of power to the second set of sensors when the second set of sensors are activated. ### Claim 9 A system comprising: a data storage system configured to store data generated by a first set of sensors powered by one or more batteries of one or more ear-wearable devices; and one or more processing circuits configured to: determine, based on the data generated by the first set of sensors, that a user of the one or more ear-wearable devices is currently in an environment that includes human- directed communication signals, wherein a second set of sensors includes at least one sensor that is not included in the first set of sensors; in response to determining that the user is currently in the environment that includes human-directed communication signals, activate the second set of sensors and/or activate wireless streaming of data associated with the second set of sensors, wherein the second set of sensors includes at least one sensor that is not included in the first set of sensors; determine, based on the data associated with by the second set of sensors, a measure of complexity of social engagement of the user; and generate a visual representation of the measure of complexity of social engagement of the user. ### Claim 10 (depends on 9) The system of claim 9, wherein the one or more processing circuits are further configured to generate a notification message that provides a tip on how to improve the complexity of social engagement of the user. ### Claim 11 (depends on 9) The system of claim 9, wherein the visual representation of the measure of complexity of social engagement of the user comprises a visual representation of a comparison of the measure of complexity of social engagement to a typical level of the measure of complexity of social engagement achieved by a population of individuals. ### Claim 12 (depends on 9) The system of claim 9, wherein the one or more processing circuits are configured to provide information regarding the measure of complexity of social engagement of the user to one or more persons other than the user. ### Claim 13 (depends on 9) The system of claim 9, wherein the one or more processing circuits are further configured to: determine that the user has not satisfied a target level of the measure of complexity of social engagement of the user; and provide, based on the determination that the user has not satisfied the target level of the measure of complexity of social engagement of the user, an alert that prompts a third party or an artificial intelligence companion to initiate a social interaction with the user. ### Claim 14 (depends on 9) The system of claim 9, wherein the one or more ear-wearable devices include the second set of sensors. ### Claim 15 (depends on 9) The system of claim 9, wherein the batteries provide a first amount of power to a second set of one or more sensors when the second set of sensors are not activated and provide a second amount of power greater than the first amount of power to the second set of sensors when the second set of sensors are activated. ### Claim 16 A system comprising: means for determining, based on data generated by a first set of sensors, that a user of one or more ear-wearable devices is currently in an environment that includes human-directed communication signals, wherein a second set of sensors includes at least one sensor that is not included in the first set of sensors; means for activating, in response to determining that the user is currently in the environment that includes human-directed communication signals, the second set of sensors and/or activating wireless streaming of data associated with the second set of sensors; means for determining, based on the data associated with the second set of sensors, a measure of complexity of social engagement of the user; and means for generating a visual representation of the measure of complexity of social engagement of the user. ### Claim 17 A non-transitory computer-readable storage medium having instructions stored thereon that, when executed, cause one or more processing circuits to: determine, based on data generated by a first set of sensors, that a user of one or more ear-wearable devices is currently in an environment that includes human-directed communication signals, wherein a second set of sensors includes at least one sensor that is not included in the first set of sensors; in response to determining that the user is currently in the environment that includes human-directed communication signals, activate the second set of sensors and/or activate wireless streaming of data associated with the second set of sensors; determine, based on the data associated with the second set of sensors, a measure of complexity of social engagement of the user; and generate a visual representation of the measure of complexity of social engagement of the user.