# US 10,945,618 B2 · Physiological monitoring devices and methods for noise reduction in physiological signals based on subject activity type > Agents: this data is available as JSON from the patentgrep API and MCP server — see https://patentgrep.com/llms.txt - Number: US 10,945,618 B2 - Document ID: US10945618B2 - Status: Granted - Kind: B2 - Application number: 15/922,610 - Filed: 2018-03-15 - Published: 2018-07-19 - Granted: 2021-03-16 - Earliest claimed: 2015-10-23 - Assignees: Valencell, Inc. - Applicants: Valencell, Inc. - Inventors: Michael Edward Aumer; Steven Francis LeBoeuf - Web page: https://patentgrep.com/patent/US10945618B2 ## CPC - A61B 5/02427: {Details of sensor} - A61B 5/1118: {Determining activity level} - A61B 5/721: {using a separate sensor to detect motion or using motion information derived from signals other than the physiological signal to be measured} - A61B 5/0022: {Monitoring a patient using a global network, e.g. telephone networks, internet} - A61B 5/0205: Simultaneously evaluating both cardiovascular conditions and different types of body conditions, e.g. heart and respiratory condition - A61B 5/02055: {Simultaneously evaluating both cardiovascular condition and temperature} - A61B 5/021: Measuring pressure in heart or blood vessels - A61B 5/02405: {Determining heart rate variability} - A61B 5/02438: {with portable devices, e.g. worn by the patient} - A61B 5/0816: {Measuring devices for examining respiratory frequency (measuring frequency of electric signals G01R23/00)} - A61B 5/1455: using optical sensors, e.g. spectral photometrical oximeters - A61B 5/352: Detecting R peaks, e.g. for synchronising diagnostic apparatus; Estimating R-R interval - A61B 5/6815: {Ear} - A61B 5/6831: {Straps, bands or harnesses} - A61B 5/7253: {characterised by using transforms} - A61B 2560/0242: adapted to measure environmental factors, e.g. temperature, pollution - A61B 2562/0219: Inertial sensors, e.g. accelerometers, gyroscopes, tilt switches - A61B: DIAGNOSIS; SURGERY; IDENTIFICATION (usefulness limited to only animals A61D) ## Abstract Methods and apparatus for monitoring a subject are described. A monitoring device configured to be attached to a body of a subject includes a sensor that is configured to detect and/or measure physiological information from the subject and at least one motion sensor configured to detect and/or measure subject motion information. The physiological sensor and motion sensor are in communication with a processor that is configured to receive and analyze signals produced by the physiological sensor and motion sensor. The processor is configured to process motion sensor signals to identify an activity characteristic of the subject. Once an activity characteristic is identified, the processor is configured to select a noise reference in response to identification of the activity characteristic of the subject, and then process physiological sensor signals using the noise reference to generate an output signal having reduced noise relative to the physiological sensor signal, to produce physiological information about the subject. ## Claims ### Claim 1 A method of monitoring a subject via a monitoring device, wherein the monitoring device includes a physiological sensor and a plurality of motion sensors, and wherein the physiological sensor and the plurality of motion sensors are in communication with at least one processor, the method comprising: processing, via the at least one processor, a motion sensor signal to identify an activity characteristic of the subject; selecting one of the plurality of motion sensors as a noise reference via the at least one processor in response to based on identification of the activity characteristic; and processing, via the at least one processor, a physiological sensor signal received from the physiological sensor using the noise reference to generate an output signal having reduced noise relative to the physiological sensor signal. ### Claim 2 (depends on 1) The method of claim 1, wherein the plurality of motion sensors comprises first and second motion sensors, wherein the first and second motion sensors are different types of sensors, and wherein selecting the one of the plurality of motion sensors as the noise reference comprises: selecting, from among the first and second motion sensors, the first motion sensor as the noise reference based on identification of the activity characteristic as periodic motion; or selecting, from among the first and second motion sensors, the second motion sensor as the noise reference based on identification of the activity characteristic as non-periodic motion. ### Claim 3 (depends on 2) The method of claim 2, wherein the physiological sensor comprises an optical sensor, and wherein the second motion sensor is configured to provide a signal response that more closely corresponds to motion-related optical noise present in the physiological sensor signal than the first motion sensor. ### Claim 4 (depends on 2) The method of claim 2, wherein processing the physiological sensor signal using the noise reference comprises: processing the physiological sensor signal using a frequency-domain-based algorithm or circuit responsive to identification of the activity characteristic as periodic motion; or processing the physiological sensor signal using a time-domain-based algorithm or circuit responsive to identification of the activity characteristic as non-periodic motion. ### Claim 5 (depends on 2) The method of claim 2, wherein the physiological sensor is a photoplethysmography (PPG) sensor, wherein the first motion sensor comprises an inertial sensor, and wherein the second motion sensor comprises an optomechanical sensor. ### Claim 6 (depends on 5) The method of claim 5, wherein the optomechanical sensor is configured to modulate light generated by an optical emitter in response to body motion, and to direct the light upon a pathway which is substantially unaffected by blood flow. ### Claim 7 (depends on 1) The method of claim 1, wherein processing the physiological sensor signal using the noise reference further comprises: in response to identification of the activity characteristic as periodic motion, processing the physiological sensor signal using a first algorithm or circuit; or in response to identification of the activity characteristic as non-periodic motion, processing the physiological sensor signal using a second algorithm or circuit that is different from the first algorithm or circuit. ### Claim 8 (depends on 7) The method of claim 7, wherein the first algorithm or circuit comprises frequency-domain processing and/or filtering, and wherein the second algorithm or circuit comprises time-domain processing and/or filtering. ### Claim 9 (depends on 8) The method of claim 8, wherein the first and second algorithms or circuits utilize a same sensor or sensors of the plurality of motion sensors. ### Claim 10 (depends on 8) The method of claim 8, wherein the first algorithm or circuit is configured to perform spectral subtraction, and wherein the second algorithm or circuit is configured to perform adaptive filtering. ### Claim 11 (depends on 1) The method of claim 1, wherein body motion information contained in the noise reference is greater than blood flow information contained therein. ### Claim 12 (depends on 1) The method of claim 1, wherein the noise reference comprises information associated with motion of the subject and is substantially free of information associated with blood flow of the subject. ### Claim 13 (depends on 1) The method of claim 1, wherein the physiological information includes one or more of the following: subject heart rate, subject respiration rate, subject RR-interval (RRi), subject heart rate variability (HRV), subject blood pressure, subject blood analyte levels, subject cardiovascular properties. ### Claim 14 (depends on 1) The method of claim 1, wherein the activity characteristic comprises a first activity characteristic or a second activity characteristic that is different than the first activity characteristic, wherein the plurality of motion sensors comprises first and second motion sensors, wherein the first and second motion sensors are different types of sensors, and wherein selecting the one of the plurality of motion sensors as the noise reference comprises: selecting, from among the first and second motion sensors, the first motion sensor as the noise reference based on identification of the first activity characteristic; or selecting, from among the first and second motion sensors, the second motion sensor as the noise reference based on identification of the second activity characteristic. ### Claim 15 (depends on 14) The method of claim 14, wherein the first motion sensor comprises an inertial sensor, and wherein the second motion sensor comprises an optomechanical sensor. ### Claim 16 A monitoring device configured to be attached to a bodily location of a subject, the monitoring device comprising: a physiological sensor configured to detect and/or measure physiological data from the subject and generate a physiological sensor signal representative thereof; a plurality of motion sensors, each configured to detect and/or measure subject motion data and generate a respective motion sensor signal representative thereof; and at least one processor coupled to the physiological sensor and the plurality of motion sensors, wherein the at least one processor is configured to perform operations comprising: processing the respective motion sensor signal received from one of the plurality of motion sensors to identify an activity characteristic of the subject; selecting one of the plurality of motion sensors as a noise reference based on identification of the activity characteristic; and processing the physiological sensor signal received from the physiological sensor using the noise reference to generate an output signal having reduced noise relative to the physiological sensor signal. ### Claim 17 (depends on 16) The monitoring device of claim 16, wherein the plurality of motion sensors comprises first and second motion sensors, wherein the first and second motion sensors are different types of sensors, and wherein selecting the one of the plurality of motion sensors as the noise reference comprises: selecting, from among the first and second motion sensors, the first motion sensor as the noise reference based on identification of the activity characteristic as periodic motion; or selecting, from among the first and second motion sensors, the second motion sensor as the noise reference based on identification of the activity characteristic as non-periodic motion. ### Claim 18 (depends on 17) The monitoring device of claim 17, wherein the physiological sensor comprises an optical sensor, and wherein a signal response of the second motion sensor more closely corresponds to motion-related optical noise present in the physiological sensor signal than a signal response of the first motion sensor. ### Claim 19 (depends on 18) The monitoring device of claim 18, wherein processing the physiological sensor signal using the noise reference comprises: processing the physiological sensor signal using a frequency-domain-based algorithm or circuit responsive to identification of the activity characteristic as periodic motion; or processing the physiological sensor signal using a time-domain-based algorithm or circuit responsive to identification of the activity characteristic as non-periodic motion. ### Claim 20 (depends on 19) The monitoring device of claim 19, wherein the physiological sensor is a photoplethysmography (PPG) sensor, wherein the first motion sensor comprises an inertial sensor, and wherein the second motion sensor comprises an optomechanical sensor. ### Claim 21 (depends on 20) The monitoring device of claim 20, wherein the optomechanical sensor is configured to modulate light generated by an optical emitter in response to body motion, and to direct the light upon a pathway which is substantially unaffected by blood flow. ### Claim 22 A computer program product comprising a non-transitory computer readable storage medium having computer readable program code embodied therein, which, when executed by at least one processor, causes the at least one processor to perform operations comprising: processing a motion sensor signal to identify an activity characteristic of the subject; selecting one of a plurality of motion sensors as a noise reference based on identification of the activity characteristic; and processing a physiological sensor signal received from the physiological sensor using the noise reference to generate an output signal having reduced noise relative to the physiological sensor signal.