Method and apparatus for generating assessments using physical activity and biometric parameters

• US 10,206,627 B2
• Filed: 08/30/2017
• Issued: 02/19/2019
• Est. Priority Date: 02/28/2014
• Status: Active Grant

• Current Assignee: Valencell, Inc.
• Original Assignee: Valencell, Inc.
• Inventors: LeBoeuf, Steven F., Aumer, Michael Edward, Romesburg, Eric Douglas
• Primary Examiner(s): Dowtin, Jewel V
• Application Number:
  US15/690,940
• Publication Number:
  US 20170367658A1
• Time in Patent Office: 538 Days
• CPC Class Codes: A61B 2505/09 Rehabilitation or training
• CPC Class Codes: A61B 2562/0219 Inertial sensors, e.g. accelerometers, gyroscopes, tilt switches
• CPC Class Codes: A61B 5/02055 Simultaneously evaluating both cardiovascular condition and temperature
• CPC Class Codes: A61B 5/021 Measuring pressure in heart or blood vessels A61B5/0205 takes precedence
• CPC Class Codes: A61B 5/02108 from analysis of pulse wave characteristics
• 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 5/026 Measuring blood flow A61B3/1233, A61B3/1241 take precedence
• CPC Class Codes: A61B 5/0816 Measuring devices for examining respiratory frequency measuring frequency of electric signals G01R23/00
• CPC Class Codes: A61B 5/091 Measuring volume of inspired or expired gases, e.g. to determine lung capacity
• CPC Class Codes: A61B 5/1118 Determining activity level
• CPC Class Codes: A61B 5/112 Gait analysis
• CPC Class Codes: A61B 5/1123 Discriminating type of movement, e.g. walking or running A61B5/1116, A61B5/112 take precedence
• CPC Class Codes: A61B 5/352 Detecting R peaks, e.g. for synchronising diagnostic apparatus; Estimating R-R interval
• CPC Class Codes: A61B 5/4205 Evaluating swallowing
• CPC Class Codes: A61B 5/6815 Ear
• CPC Class Codes: A61B 5/7203 for noise prevention, reduction or removal
• 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 5/7235 Details of waveform analysis A61B5/349 takes precedence
• CPC Class Codes: A61B 5/7239 : using differentiation including higher order derivatives
• CPC Class Codes: A61B 5/7242 : using integration
• CPC Class Codes: A61B 5/7275 : Determining trends in physiological measurement data; Predicting development of a medical condition based on physiological measurements, e.g. determining a risk factor
• CPC Class Codes: A61B 5/7278 : Artificial waveform generation or derivation, e.g. synthesising signals from measured signals A61B5/327 takes precedence
• CPC Class Codes: G16H 20/17 : delivered via infusion or injection
• CPC Class Codes: G16H 20/30 : relating to physical therapies or activities, e.g. physiotherapy, acupressure or exercising
• CPC Class Codes: G16H 20/40 : relating to mechanical, radiation or invasive therapies, e.g. surgery, laser therapy, dialysis or acupuncture
• CPC Class Codes: G16H 40/63 : for local operation
• CPC Class Codes: G16H 40/67 : for remote operation

Abstract

The methods and apparatuses presented herein determine and/or improve the quality of one or more physiological assessment parameters, e.g., response-recovery rate, based on biometric signal(s) and/or motion signal(s) respectively output by one or more biometric and/or motion sensors. The disclosed methods and apparatuses also estimate a user'"'"'s stride length based on a motion signal and a determined type of user motion, e.g., walking or running. The speed of the user may then be estimated based on the estimated stride length.

Claims

1. A method for determining a physiological assessment parameter associated with a user using an activity monitoring device comprising at least one biometric sensor and at least one motion sensor, wherein the biometric sensor is at least partially proximal to at least some skin of the user, the method executed in one or more processing circuits operatively connected to the at least one motion sensor and the at least one biometric sensor, the method comprising:

processing a motion signal output by the motion sensor over a first period of time to determine a targeted time period comprising at least one active portion and at least one recovery portion;

processing a biometric signal output by the biometric sensor over the first period of time to determine a biometric parameter for the user over the first period of time;

determining a response biometric parameter for the user using the biometric signal output by the biometric sensor during the at least one active portion of the targeted time period;

determining a recovery biometric parameter for the user using the biometric signal output by the biometric sensor during the at least one recovery portion of the targeted time period; and

computing a slope of the recovery biometric parameter versus the response biometric parameter associated with the targeted time period.

2. The method of claim 1 wherein the biometric parameter comprises at least one of a heart rate, breathing rate, breathing volume, pulse pressure, R-R interval, and heart rate variability.

3. The method of claim 1 wherein the biometric parameter comprises a blood pressure.

4. The method of claim 1 further comprising processing the slope to estimate at least one of VO₂, energy expenditure, and VO_2max.

5. A method of assessing a fitness level of a subject comprising:

measuring an average heart rate of the subject with a heart rate sensor worn by the subject over a period of time;

measuring an average cadence of the subject with a cadence sensor worn by the subject over the period of time; and

calculating a ratio of the average heart rate to the average cadence with a processor operatively coupled to the heart rate sensor and the cadence sensor.

6. The method of claim 5 wherein the fitness level is inversely proportional to the ratio of the average heart rate to the average cadence.

7. The method of claim 5 further comprising determining a relative body temperature using the calculated ratio of the average heart rate to the average cadence, wherein the higher the calculated ratio the higher the relative body temperature.

8. A method of determining a physiological assessment parameter associated with a user using a wearable activity monitoring device comprising at least one biometric sensor and at least one motion sensor, wherein the biometric sensor is at least partially proximal to at least some skin of the user and is configured to measure blood flow information from the user, the method executed in one or more processing circuits operatively connected to the at least one motion sensor and the at least one biometric sensor, the method comprising:

processing a motion signal output by the motion sensor over a first period of time to determine a physical activity parameter for the user over the first period of time;

processing a biometric signal output by the biometric sensor over the first period of time to determine a biometric parameter for the user over the first period of time;

processing the physical activity parameter to determine one or more time periods wherein the physical activity parameter is within a specific range of values;

processing the biometric parameter during the time periods wherein the physical activity parameter is within the specific range of values to determine the physiological assessment parameter for the user.

9. The method of claim 8 wherein the physical activity parameter comprises a user cadence or a user speed.

10. The method of claim 8 wherein the biometric parameter comprises a breathing rate.

11. The method of claim 10 wherein processing the biometric parameter during the time periods where the physical activity parameter is within the specific range of values comprises calculating an average breathing rate using the breathing rate during the time periods where the physical activity parameter is within the specific range of values.

12. The method of claim 11 wherein the physiological assessment parameter generated for the user comprises an estimation of VO₂max.

13. The method of claim 12 wherein the specific range of values comprises a speed less than or equal to 2.3 miles per hour.

14. The method of claim 8 wherein the biometric parameter comprises a heart rate.

15. The method of claim 14 wherein the processing the biometric parameter during the time periods where the physical activity parameter is within the specific range of values comprises determining whether the heart rate has changed by 15 beats per minute or less over the course of 15 to 40 seconds during the time periods where the physical activity parameter is within the specific range of values.

16. The method of claim 14 wherein the specific range of values is associated with a lower activity state, and wherein the determining that the physiological assessment parameter comprises determining that the physiological assessment parameter comprises a swallowing event when the heart rate has changed by 15 beats per minute or less over the course of 15 to 40 seconds during the time periods where the physical activity parameter is within the specific range of values associated with the lower activity state.

17. A method of evaluating an exercise activity comprising one or more sets of exercise repetitions performed by a user via at least one biometric sensor and at least one motion sensor comprised in a wearable monitoring device, the method executed in one or more processing circuits operatively connected to the at least one motion sensor and the at least one biometric sensor, the method comprising:

processing a motion signal output by the at least one motion sensor and a biometric signal output by the at least one biometric sensor to identify a type of the exercise activity; and

processing the motion signal using the identified exercise activity to determine an exercise cadence;

processing the biometric signal to determine at least one biometric parameter;

estimating a number of repetitions of the identified exercise activity using an integral of the exercise cadence; and

estimating a number of sets of the identified exercise activity using a time-dependent change of the at least one biometric parameter.

18. The method of claim 17 wherein further comprising estimating an intensity of the identified exercise activity using the integral of the exercise cadence and an integral of the at least one biometric parameter.

19. A method of determining a blood pressure characteristic of a user using a device comprising a photoplethysmography sensor and a motion sensor, wherein the photoplethysmography sensor is proximal to at least some skin of the user, the method executed in one or more processing circuits operatively connected to the motion sensor and the photoplethysmography sensor, the method comprising:

screening data from the motion sensor to determine an integrity of data from the photoplethysmography sensor;

buffering at least one of a plurality of pulses, at least one of the buffered pulses having integrity;

identifying a beginning point and an end point of at least one of the buffered pulses;

generating a pulse shape using the at least one of the buffered plurality of pulses having the identified beginning point and the identified end point;

determining a first derivative of the pulse shape; and

determining the blood pressure characteristic using a waveform representation of the first derivative of the pulse shape.

20. The method of claim 19 wherein the screening the data from the motion sensor comprises determining whether a user cadence is below a threshold to determine the integrity of the data from the photoplethysmography sensor.

21. The method of claim 19 wherein the generating the pulse shape comprises generating a spline representation of each of the buffered plurality of pulses.

22. A method of determining a blood pressure characteristic of a user using a device comprising a photoplethysmography sensor and a motion sensor, wherein the photoplethysmography sensor is proximal to at least some skin of the user, the method executed in one or more processing circuits operatively connected to the motion sensor and the photoplethysmography sensor, the method comprising:

screening data from the motion sensor to determine an integrity of data from the photoplethysmography sensor;

processing the data from the photoplethysmography sensor, at least some of the processed data having integrity such that user motion is determined to be below a threshold, to generate a normalized waveform representation of a first derivative of at least one pulse, the normalized waveform representation of the first derivative of the at least one pulse having substantially no pulse-rate dependence; and

determining the blood pressure characteristic using the normalized waveform representation of the first derivative of the at least one pulse.