Physiological monitoring devices and methods that identify subject activity type

• US 10,610,158 B2
• Filed: 10/21/2016
• Issued: 04/07/2020
• Est. Priority Date: 10/23/2015
• Status: Active Grant

• Current Assignee: Yukka Magic LLC
• Original Assignee: Valencell, Inc.
• Inventors: Aumer, Michael Edward, LeBoeuf, Steven Francis
• Primary Examiner(s): Jackson, Gary
• Assistant Examiner(s): Kabir, Zahed
• Application Number:
  US15/299,684
• Publication Number:
  US 20170112447A1
• Time in Patent Office: 1,264 Days
• Field of Search: 600301, 600479, 600519, 600513, 600515, 600518
• CPC Class Codes: A61B 2562/0219 Inertial sensors, e.g. accelerometers, gyroscopes, tilt switches
• CPC Class Codes: A61B 5/0205 Simultaneously evaluating both cardiovascular conditions and different types of body conditions, e.g. heart and respiratory condition
• CPC Class Codes: A61B 5/021 Measuring pressure in heart or blood vessels A61B5/0205 takes precedence
• CPC Class Codes: A61B 5/02405 Determining heart rate variability
• CPC Class Codes: A61B 5/02416 using photoplethysmograph signals, e.g. generated by infrared radiation A61B5/14552 takes precedence
• CPC Class Codes: A61B 5/02438 with portable devices, e.g. worn by the patient
• CPC Class Codes: A61B 5/0816 Measuring devices for examining respiratory frequency measuring frequency of electric signals G01R23/00
• CPC Class Codes: A61B 5/1118 Determining activity level
• CPC Class Codes: A61B 5/145 Measuring characteristics of blood in vivo, e.g. gas concentration, pH value; Measuring characteristics of body fluids or tissues, e.g. interstitial fluid, cerebral tissuemeasuring of blood pressure or blood flow A61B5/02; non-radiation detecting or locating of foreign bodies in blood A61B5/06
• CPC Class Codes: A61B 5/6815 Ear
• CPC Class Codes: A61B 5/6817 Ear canal
• CPC Class Codes: A61B 5/6831 Straps, bands or harnesses
• CPC Class Codes: 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
• CPC Class Codes: A61B 5/7257 using Fourier transforms
• CPC Class Codes: A61B 5/7278 Artificial waveform generation or derivation, e.g. synthesising signals from measured signals A61B5/327 takes precedence

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 a 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 determined, the processor is configured to select a biometric signal extraction algorithm or circuit in response to the activity characteristic of the subject, and then process physiological sensor signals via the biometric signal extraction algorithm or circuit to produce physiological information about the subject.

Claims

1. A method of monitoring a subject via a monitoring device, wherein the monitoring device includes a photoplethysmography (PPG) sensor that is in communication with at least one processor, the method comprising:

processing PPG sensor signals received from the PPG sensor by the at least one processor to obtain RR-intervals and identify a statistical relationship between first and second RR-intervals of the RR-intervals obtained from the PPG sensor signals;

selecting a biometric signal extraction algorithm or circuit by the at least one processor in response to identification of the statistical relationship between the first and second RR-intervals; and

then

processing PPG sensor signals received from the PPG sensor by the at least one processor using the selected biometric signal extraction algorithm or circuit to produce physiological information about the subject.

2. The method of claim 1, wherein the physiological information that is produced 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.

3. The method of claim 1, wherein the monitoring device is configured to be positioned at or within an ear of the subject, secured to an appendage of the subject, or worn on a bodily location of the subject.

4. The method of claim 1, wherein the at least one processor is configured to process the PPG sensor signals using the selected biometric signal extraction algorithm or circuit to obtain 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.

5. The method of claim 1, wherein, prior to selecting a biometric signal extraction algorithm or circuit, the method comprises processing the statistical relationship between the first and second RR-intervals to determine a type of motion of the subject or a physiological status of the subject.

6. The method of claim 5, wherein the processing to determine the type of motion of the subject comprises determining that the type of motion of the subject is periodic motion or non-periodic motion.

7. The method of claim 6, wherein the processing the PPG sensor signals using the selected biometric tracking algorithm or circuit comprises:

processing the PPG sensor signals using a first biometric signal extraction algorithm or circuit in response to determining that the type of motion is periodic motion, wherein the first biometric signal extraction algorithm or circuit comprises frequency domain processing and/or filtering; and

processing the PPG sensor signals using a second biometric signal extraction algorithm or circuit, which is different from the first biometric signal extraction algorithm or circuit, in response to determining that the type of motion is non-periodic motion, wherein the second biometric signal extraction algorithm or circuit comprises time domain processing and/or filtering.

8. The method of claim 7, wherein the second biometric signal extraction algorithm or circuit comprises a modification of the first biometric signal extraction algorithm or circuit, wherein the modification is based on the type of motion of the subject.

9. The method of claim 5, wherein processing the PPG sensor signals to identify the statistical relationship between the first and second RR-intervals therein is performed using a first biometric signal extraction algorithm or circuit that is different than the selected biometric signal extraction algorithm or circuit, and wherein the selected biometric signal extraction algorithm or circuit is configured based on noise associated with the type of motion or physiological status.

10. A method of monitoring a subject via a monitoring device, wherein the monitoring device includes a photoplethysmography (PPG) sensor that is in communication with at least one processor, the method comprising:

processing PPG sensor signals received from the PPG sensor by the at least one processor to obtain RR-intervals and identify a statistical relationship between the RR-intervals obtained from the PPG sensor signals;

processing the statistical relationship between the RR-intervals to determine a stress status for the subject;

selecting a biometric signal extraction algorithm or circuit by the at least one processor in response to identification of the statistical relationship between the RR-intervals and based on the stress status determined therefrom; and

then

processing PPG sensor signals received from the PPG sensor by the at least one processor using the selected biometric signal extraction algorithm or circuit to produce physiological information about the subject.

11. The method of claim 10, wherein:

the processing the statistical relationship between the RR-intervals to determine the stress status comprises determining a likelihood of a first health condition;

the selecting the biometric signal extraction algorithm or circuit is based on the likelihood of the first health condition; and

the processing the PPG sensor signals using the selected biometric signal extraction algorithm to produce the physiological information indicates a diagnosis of the first health condition or a second health condition that is associated with the first health condition.

12. The method of claim 11, wherein the first health condition comprises atrial fibrillation.

13. The method of claim 10, wherein:

processing the PPG sensor signals to identify the statistical relationship between the RR-intervals therein is performed using a first biometric signal extraction algorithm or circuit that is different than the selected biometric signal extraction algorithm or circuit; and

responsive processing the PPG sensor signals using the selected biometric signal extraction algorithm or circuit, an accuracy of the physiological information is increased relative to processing the PPG sensor signals using the first biometric signal extraction algorithm or circuit.

14. The method of claim 13, wherein the first biometric signal extraction algorithm or circuit comprises frequency domain processing and/or filtering, and wherein the selected biometric signal extraction algorithm or circuit comprises time domain processing and/or filtering.