METHOD TO ESTIMATE PHYSICAL ACTIVITY RATING FROM PEDOMETER DATA

• US 20160058333A1
• Filed: 09/30/2014
• Published: 03/03/2016
• Est. Priority Date: 09/02/2014
• Status: Abandoned Application

• Current Assignee: Apple Inc.
• Original Assignee: Apple Inc.
• Inventors: ARNOLD, Edith Merle, RAGHURAM, Karthik Jayaraman, TAN, Xing
• Application Number:
  US14/502,809
• Publication Number:
  US 20160058333A1
• Time in Patent Office: Days
• US Class Current: 1/1
• CPC Class Codes: A61B 2560/0204 of power management
• CPC Class Codes: A61B 2560/0242 adapted to measure environmental factors, e.g. temperature, pollution
• CPC Class Codes: A61B 2560/0475 Special features of memory means, e.g. removable memory cards
• CPC Class Codes: A61B 2562/0219 Inertial sensors, e.g. accelerometers, gyroscopes, tilt switches
• CPC Class Codes: A61B 5/0002 Remote monitoring of patients using telemetry, e.g. transmission of vital signals via a communication network A61B5/07 takes precedence; transmission systems for measured values G08C; transmission H04B; transmission of digital information H04L; wireless communication networks H04W
• CPC Class Codes: A61B 5/0004 characterised by the type of physiological signal transmitted
• 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 5/02416 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 5/1112 Global tracking of patients, e.g. by using GPS
• CPC Class Codes: A61B 5/1116 Determining posture transitions
• CPC Class Codes: A61B 5/1118 Determining activity level
• CPC Class Codes: A61B 5/112 Gait analysis
• CPC Class Codes: A61B 5/1121 Determining geometric values, e.g. centre of rotation or angular range of movement
• 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 5/222 combined with detection or measurement of physiological parameters, e.g. heart rate
• CPC Class Codes: A61B 5/4866 Evaluating metabolism A61B5/083 takes precedence
• CPC Class Codes: A61B 5/4884 inducing physiological or psychological stress, e.g. applications for stress testing
• CPC Class Codes: A61B 5/681 Wristwatch-type devices
• CPC Class Codes: A61B 5/6898 Portable consumer electronic devices, e.g. music players, telephones, tablet computers
• CPC Class Codes: A61B 5/7221 : Determining signal validity, reliability or quality A61B5/7207 and A61B5/7217 take precedence
• CPC Class Codes: A61B 5/7246 : using correlation, e.g. template matching or determination of similarity
• CPC Class Codes: A61B 5/725 : using specific filters therefor, e.g. Kalman or adaptive filters A61B5/316 take precedence
• CPC Class Codes: A61B 5/7264 : Classification of physiological signals or data, e.g. using neural networks, statistical classifiers, expert systems or fuzzy systems neural networks per se G06N3/00; expert systems per se G06N5/00
• 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: A63B 22/0605 : performing a circular movement, e.g. ergometers
• CPC Class Codes: G01C 22/006 : Pedometers

Abstract

In one aspect, the present disclosure relates to a method including obtaining, by a fitness tracking device, an average step count of a user of the fitness tracking device; mapping, by the fitness tracking device, the average step count to a first corresponding physical activity level of a plurality of physical activity levels; storing, in a memory of the fitness tracking device, the first corresponding physical activity level; estimating, by the fitness tracking device, an aerobic capacity of the user using the first corresponding physical activity level of the user; and estimating, by the fitness tracking device, an energy expenditure rate of the user using the aerobic capacity of the user.

Claims

1. A method comprising:

obtaining, by a fitness tracking device, an average step count of a user of the fitness tracking device;

mapping, by the fitness tracking device, the average step count to a first corresponding physical activity level of a plurality of physical activity levels;

storing, in a memory of the fitness tracking device, the first corresponding physical activity level;

estimating, by the fitness tracking device, an aerobic capacity of the user using the first corresponding physical activity level of the user; and

estimating, by the fitness tracking device, an energy expenditure rate of the user using the aerobic capacity of the user.

2. The method of claim 1, wherein obtaining the average step count comprises:

obtaining, by the fitness tracking device, a plurality of daily step counts over a period of time; and

comparing, by the fitness tracking device, each daily step count of the plurality of daily step counts to a threshold step count to identify a plurality of valid daily step counts,

wherein each valid daily step count of the plurality of valid daily step counts exceeds the threshold step count, and

wherein the average step count comprises a moving average of the plurality of valid daily step counts.

3. The method of claim 2, wherein each valid daily step count comprises an estimate, by the fitness tracking device, of a number of steps taken by the user on a corresponding valid day, and wherein an invalid daily step count comprises an indication that the fitness tracking device was not worn by the user during a corresponding invalid day.

4. The method of claim 1, comprising:

determining, by the fitness device, for each physical activity level of the plurality of physical activity levels, a corresponding step range of a plurality of step ranges,

wherein mapping the average step count to the first corresponding physical activity level comprises matching the average step count to a first corresponding step range that corresponds to the first corresponding physical activity level.

5. The method of claim 4, comprising:

obtaining, by a motion sensor of the fitness tracking device, motion data of the user;

analyzing, by the fitness tracking device, the motion data to determine at least one of a walking cadence, a walking step length, a running cadence, and a running step length of the user; and

modifying, by the fitness tracking device, each corresponding step range of the plurality of step ranges using at least one of the walking cadence, the walking step length, the running cadence, and the running step length of the user to generate a customized plurality of step ranges for the user.

6. The method of claim 4, comprising:

obtaining, by a motion sensor of the fitness tracking device, motion data of the user;

analyzing, by the fitness tracking device, the motion data to determine an average duration of exercise of the user; and

adjusting, by the fitness tracking device, the first corresponding physical activity level of the user if the average duration of exercise exceeds a corresponding threshold duration of exercise.

7. The method of claim 4, comprising:

obtaining, by a motion sensor of the fitness tracking device, motion data of the user; and

analyzing, by the fitness tracking device, the motion data to determine an average duration of exercise of the user,

wherein mapping the average step count to the first corresponding physical activity level comprises;

matching, by the fitness tracking device, the average step count to a first corresponding step range that corresponds to the first corresponding physical activity level;

matching, by the fitness tracking device, the average step count to a second corresponding step range that corresponds to a second corresponding physical activity level;

selecting, by the fitness tracking device, the first corresponding physical activity when the average duration of exercise exceeds a corresponding threshold duration of exercise.

8. A fitness tracking device comprising:

a memory;

a motion sensor for obtaining estimates of step counts of a user of the fitness tracking device;

a processor communicatively coupled to the memory and the motion sensor, wherein the processor is configured to;

obtain an average step count of a user of the fitness tracking device;

map the average step count to a first corresponding physical activity level of a plurality of physical activity levels;

store, in the memory, the first corresponding physical activity level;

estimate an aerobic capacity of the user using the first corresponding physical activity level of the user; and

estimate an energy expenditure rate of the user using the aerobic capacity of the user.

9. The fitness tracking device of claim 8, wherein the processor configured to obtain the average step count is configured to:

obtain a plurality of daily step counts over a period of time; and

compare each daily step count of the plurality of daily step counts to a threshold step count to identify a plurality of valid daily step counts,

wherein each valid daily step count of the plurality of valid daily step counts exceeds the threshold step count, and

wherein the average step count comprises a moving average of the plurality of valid daily step counts.

10. The fitness tracking device of claim 9, wherein each valid daily step count comprises an estimate, by the fitness tracking device, of a number of steps taken by the user on a corresponding valid day, and wherein an invalid daily step count comprises an indication that the fitness tracking device was not worn by the user during a corresponding invalid day.

11. The fitness tracking device of claim 8, wherein the processor is configured to:

determine, for each physical activity level of the plurality of physical activity levels, a corresponding step range of a plurality of step ranges, and

wherein the processor configured to map the average step count to the first corresponding physical activity level is configured to match the average step count to a first corresponding step range that corresponds to the first corresponding physical activity level.

12. The fitness tracking device of claim 11, wherein the processor is configured to:

analyze the motion data to determine at least one of a walking cadence, a walking step length, a running cadence, and a running step length of the user; and

modify each corresponding step range of the plurality of step ranges using at least one of the walking cadence, the walking step length, the running cadence, and the running step length of the user to generate a customized plurality of step ranges for the user.

13. The fitness tracking device of claim 11, wherein the processor is configured to:

analyze the motion data to determine an average duration of exercise of the user; and

adjust the first corresponding physical activity level of the user if the average duration of exercise exceeds a corresponding threshold duration of exercise.

14. The fitness tracking device of claim 11, wherein the processor is configured to:

analyze the motion data to determine an average duration of exercise of the user,

wherein the processor configured to map the average step count to the first corresponding physical activity level is configured to;

match the average step count to a first corresponding step range that corresponds to the first corresponding physical activity level;

match the average step count to a second corresponding step range that corresponds to a second corresponding physical activity level;

select the first corresponding physical activity when the average duration of exercise exceeds a corresponding threshold duration of exercise.

15. An article of manufacture comprising:

a non-transitory processor readable storage medium; and

instructions stored on the medium;

wherein the instructions are configured to be readable from the medium by a processor of a fitness tracking device comprising a memory and a motion sensor for obtaining estimates of step counts of a user of the fitness tracking device and thereby cause the processor to operate to;

obtain an average step count of a user of the fitness tracking device;

map the average step count to a first corresponding physical activity level of a plurality of physical activity levels;

store, in the memory, the first corresponding physical activity level;

estimate an aerobic capacity of the user using the first corresponding physical activity level of the user; and

estimate an energy expenditure rate of the user using the aerobic capacity of the user.

16. The article of manufacture of claim 15, wherein the processor caused to obtain the average step count is caused to:

obtain a plurality of daily step counts over a period of time; and

compare each daily step count of the plurality of daily step counts to a threshold step count to identify a plurality of valid daily step counts,

wherein each valid daily step count of the plurality of valid daily step counts exceeds the threshold step count, and

wherein the average step count comprises a moving average of the plurality of valid daily step counts.

17. The article of manufacture of claim 16, wherein each valid daily step count comprises an estimate, by the fitness tracking device, of a number of steps taken by the user on a corresponding valid day, and wherein an invalid daily step count comprises an indication that the fitness tracking device was not worn by the user during a corresponding invalid day.

18. The article of manufacture of claim 15, wherein the processor is caused to:

determine, for each physical activity level of the plurality of physical activity levels, a corresponding step range of a plurality of step ranges, and

wherein the processor caused to map the average step count to the first corresponding physical activity level is caused to match the average step count to a first corresponding step range that corresponds to the first corresponding physical activity level.

19. The article of manufacture of claim 18, wherein the processor is caused to:

analyze the motion data to determine at least one of a walking cadence, a walking step length, a running cadence, and a running step length of the user; and

modify each corresponding step range of the plurality of step ranges using at least one of the walking cadence, the walking step length, the running cadence, and the running step length of the user to generate a customized plurality of step ranges for the user.

20. The article of manufacture of claim 18, wherein the processor is caused to:

analyze the motion data to determine an average duration of exercise of the user; and

adjust the first corresponding physical activity level of the user if the average duration of exercise exceeds a corresponding threshold duration of exercise.