Detection of biking, walking, and running

• US 10,456,622 B2
• Filed: 11/04/2014
• Issued: 10/29/2019
• Est. Priority Date: 11/04/2013
• Status: Active Grant

• Current Assignee: Intel Corporation
• Original Assignee: Intel Corporation
• Inventors: Szabados, Steven P., Stirn, Andrew A., Melano, Timothy, Kowahl, Nathan R., Verplaetse, Christopher, Stander, Colt
• Primary Examiner(s): Cerioni, Daniel L
• Application Number:
  US15/022,013
• Publication Number:
  US 20160206921A1
• Time in Patent Office: 1,820 Days
• Field of Search: 600595
• CPC Class Codes: A61B 5/0024 for multiple sensor units attached to the patient, e.g. using a body or personal area network
• CPC Class Codes: A61B 5/02055 Simultaneously evaluating both cardiovascular condition and temperature
• CPC Class Codes: A61B 5/02438 with portable devices, e.g. worn by the patient
• CPC Class Codes: A61B 5/0245 by using sensing means generating electric signals, i.e. ECG signals
• 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 5/4266 sweat secretion
• CPC Class Codes: A61B 5/681 Wristwatch-type devices
• CPC Class Codes: A63B 24/0062 Monitoring athletic performances, e.g. for determining the work of a user on an exercise apparatus, the completed jogging or cycling distance
• CPC Class Codes: A63B 71/0619 Displays, user interfaces and indicating devices, specially adapted for sport equipment, e.g. display mounted on treadmills
• CPC Class Codes: G01P 15/00 Measuring acceleration; Measuring deceleration; Measuring shock, i.e. sudden change of acceleration
• CPC Class Codes: G16H 20/30 relating to physical therapies or activities, e.g. physiotherapy, acupressure or exercising
• CPC Class Codes: G16H 40/63 for local operation
• CPC Class Codes: G16H 40/67 for remote operation

Abstract

A wearable device automatically identifies an activity in which a user of the device is engaged while wearing the device. The wearable device receives motion data of the user collected during the activity and determines a magnitude and a frequency of the motion data. Based on the magnitude and frequency of the motion data, the wearable device identifies the activity in which the user is engaged.

Claims

1. A wearable device to be worn by a user during an activity, the wearable device comprising:

a motion sensor to collect motion data of the user during the activity; and

processing logic stored in a memory element of the wearable device and comprising instructions executable by a processor to;

receive motion data collected by the motion sensor;

determine a magnitude of the motion data by taking the magnitude of an acceleration signal, applying a high-pass filter to the acceleration signal, and integrating the standard deviation of the high-passed acceleration signal over a period of time;

determine a frequency of the motion data; and

identify the activity in which the user is engaged based on the magnitude and the frequency of the motion data.

2. The wearable device of claim 1, wherein the processing logic further comprises instructions executable by the processor to:

determine the frequency of the motion data by determining a cadence of steps taken by the user;

responsive to the cadence exceeding a cadence threshold and the magnitude of the motion data exceeding a magnitude threshold, identify the activity as running; and

responsive to at least one of the cadence and magnitude being less than a corresponding threshold, identify the activity as walking.

3. The wearable device of claim 2, wherein the processing logic further comprises instructions executable by the processor to:

after identifying the activity as running, detect at least one of the cadence falling below the cadence threshold and the magnitude of the motion data falling below the magnitude threshold; and

responsive to the detection, identify the activity as walking.

4. The wearable device of claim 1, wherein the processing logic further comprises instructions executable by the processor to:

determine an orientation of the wearable device; and

identify the activity as bicycling based on the magnitude and the frequency of the motion data and the orientation of the wearable device.

5. The wearable device of claim 4, wherein the processing logic further comprises instructions executable by the processor to:

determine a dominant frequency of a low frequency range of the motion data and a dominant frequency of a high frequency range of the motion data.

6. The wearable device of claim 5, wherein the processing logic further comprises instructions executable by the processor to:

apply a trained classifier to the magnitude of the motion data, the orientation of the wearable device, the dominant frequency of the low frequency range, and the dominant frequency of the high frequency range, the classifier generating a score indicating a likelihood that the user is bicycling; and

responsive to the score exceeding a threshold, identify the activity as bicycling.