Human activity monitoring device

DC CAFC

US 7,881,902 B1
Filed: 01/26/2010
Issued: 02/01/2011
Est. Priority Date: 12/22/2006
Status: Active Grant

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First Claim

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1. A method comprising:

detecting motion by an inertial sensor included in a mobile device;

determining, by the mobile device, whether the motion has a motion signature indicative of a user activity that the mobile device is configured to monitor;

when the motion does not have a motion signature of a user activity that the mobile device is configured to monitor, entering a sleep mode.

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Abstract

A method for monitoring human activity using an inertial sensor includes continuously determining an orientation of the inertial sensor, assigning a dominant axis, updating the dominant axis as the orientation of the inertial sensor changes, and counting periodic human motions by monitoring accelerations relative to the dominant axis.

257 Citations

11 Claims

1. A method comprising:
- detecting motion by an inertial sensor included in a mobile device;
  
  determining, by the mobile device, whether the motion has a motion signature indicative of a user activity that the mobile device is configured to monitor;
  
  when the motion does not have a motion signature of a user activity that the mobile device is configured to monitor, entering a sleep mode.
- View Dependent Claims (2, 3, 4)
- - 2. The method of claim 1, further comprising:
    - when the motion does have a motion signature of a user activity that the mobile device is configured to monitor, monitoring for future motions having the motion signature.
  - 3. The method of claim 1, further comprising, while the mobile device is in the sleep mode:
    - periodically sampling acceleration data at a predetermined sampling rate, wherein each sample includes acceleration data measured by the inertial sensor over a predetermined time period; and
      
      when acceleration data having a motion signature indicative of a user activity that the mobile device configured to monitor is detected within the predetermined time period, exiting the sleep mode.
  - 4. The method of claim 1, wherein the inertial sensor has an inertial wakeup functionality, the method further comprising, while the mobile device is in the sleep mode:
    - detecting a motion sufficient to trigger the inertial wakeup;
      
      sampling acceleration data for a predetermined time period;
      
      determining whether the acceleration data includes a motion signature indicative of a user activity that the mobile device is configured to monitor; and
      
      when the acceleration data includes a motion signature indicative of a user activity that the mobile device is configured to monitor, exiting the sleep mode.

5. A method for a mobile device comprising:
- receiving acceleration data that meets stepping criteria from an accelerometer included in the mobile device;
  
  incrementing a step count in a step count buffer;
  
  when at least one of a) the step count is below a step count threshold, or b) a current user cadence fails to match a step cadence of a user profile, using a default step cadence window to identify a time frame within which to monitor for a next step; and
  
  when the step count is at or above the step count threshold, determining a dynamic step cadence window and using the dynamic step cadence window to identify the time frame within which to monitor for the next step.
- View Dependent Claims (6, 7, 8, 9, 10, 11)
- - 6. The method of claim 5, wherein the step count buffer represents probable steps, the method further comprising:
    - emptying the step count buffer and acknowledging the step counts from the step count buffer as actual steps when the step count buffer reaches the step count threshold; and
      
      entering a stepping mode upon emptying the step count buffer.
  - 7. The method of claim 5, further comprising, upon determining the dynamic step cadence window:
    - examining previous acceleration data to determine whether any additional steps would have been counted if the dynamic step cadence window had been used when the previous acceleration data was received; and
      
      counting those additional steps.
  - 8. The method of claim 5, wherein determining the dynamic step cadence window comprises:
    - computing a rolling average of stepping periods of previously counted steps; and
      
      setting the dynamic step cadence window based on the rolling average of stepping periods.
  - 9. The method of claim 5, wherein the stepping criteria comprise:
    - a first criterion that is satisfied when a current acceleration measurement has a greater magnitude than a previous acceleration measurement;
      
      a second criterion that is satisfied when the current acceleration measurement has a greater magnitude than a lower threshold; and
      
      a third criterion that is satisfied when the current acceleration measurement has a lesser magnitude than an upper threshold.
  - 10. The method of claim 5, further comprising:
    - determining an orientation of the mobile device with respect to gravity;
      
      assigning a dominant axis based on the orientation; and
      
      comparing only acceleration data for the dominant axis to the to the stepping criteria to make a determination that the acceleration data meets the stepping criteria.
  - 11. The method of claim 5, further comprising:
    - when the current user cadence matches the step cadence of a user profile, using a stored step cadence window of the user profile to identify the time frame within which to monitor for the next step.

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Current Assignee
Uniloc 2017 LLC (SoftBank Group Corp.)
Original Assignee
DP Technologies, Inc.
Inventors
Kahn, Philippe, Kinsolving, Arthur, Christensen, Mark Andrew, Lee, Brian Y., Vogel, David
Primary Examiner(s)
Cosimano, Edward R

Application Number

US12/694,135
Time in Patent Office

371 Days
Field of Search

337/00, 337/01, 73/10.1, 73/13.7, 73/13.8, 73/17.5, 73/17.6, 73/17.7, 73/17.8, 73/17.9, 73/18.1, 377/1, 377/13, 377/15, 377/17, 377/20, 377/24, 377/24.1, 377/24.2, 702/1, 702/85, 702/97, 702/127, 702/141, 702/150, 702/155, 702/158, 702/160, 702/187, 702/189
US Class Current

702/160
CPC Class Codes

G01B 21/02 for measuring length, width...

G01C 22/006 Pedometers

Human activity monitoring device

First Claim

2 Assignments

Litigations

4 Petitions

Accused Products

Abstract

257 Citations

11 Claims

Specification

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Human activity monitoring device

First Claim

2 Assignments

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Litigations

4 Petitions

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Accused Products

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Abstract

257 Citations

11 Claims

Specification

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Use Cases

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Others