DYNAMIC CONTROL OF SAMPLING RATE OF MOTION TO MODIFY POWER CONSUMPTION

• US 20140288876A1
• Filed: 03/12/2014
• Published: 09/25/2014
• Est. Priority Date: 03/15/2013
• Status: Abandoned Application

• Current Assignee: JB IP Acquisitions LLC
• Original Assignee: AliphCom, Inc. (AliphCom Corp.)
• Inventors: Donaldson, Thomas Alan
• Application Number:
  US14/207,235
• Publication Number:
  US 20140288876A1
• Time in Patent Office: Days
• US Class Current: 702/141
• CPC Class Codes: A61B 2560/0209 adapted for power saving
• CPC Class Codes: A61B 2562/0219 Inertial sensors, e.g. accelerometers, gyroscopes, tilt switches
• CPC Class Codes: A61B 5/1118 Determining activity level
• CPC Class Codes: A61B 5/681 Wristwatch-type devices
• 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

Abstract

Embodiments of the relate generally to electrical and electronic hardware, computer software, wired and wireless network communications, and wearable computing devices for facilitating health and wellness-related information. More specifically, disclosed are systems, methods, devices, computer readable medium, and apparatuses configured to determine activity and activity types, including gestures, from sensed motion signals using, for example, a wearable device (or carried device) and one or more motion sensors. In one embodiment, an apparatus can include a wearable housing and a motion sensor. The apparatus can also include a signal preprocessor, which may include a sample rate controller configured to modify a sample rate of a motion sensor signal to form an adjusted sample rate with which to sample the motion sensor signal. Further, the apparatus can include an intermediate motion signal generator and an activity processor configured to identify an activity based on the intermediate motion signals.

Claims

1. An apparatus comprising:

a wearable housing;

a motion sensor configured to sense motion associated with the wearable housing and to generate a motion sensor signal;

a signal preprocessor including;

a sample rate controller configured to modify the sample rate of the motion sensor signal to form an adjusted sample rate with which to sample the motion sensor signal;

an intermediate motion signal generator configured to receive the motion sensor signal sampled at the adjusted sample rate, and further configured to generate intermediate motion signals based on the motion sensor signal; and

an activity processor configured to identify an activity based on the intermediate motion signals.

2. The apparatus of claim 1, wherein the motion sensor comprises:

an accelerometer.

3. The apparatus of claim 1, wherein the sample rate controller is configured to:

receive usage data from the activity processor indicating a level of activity; and

generate control data to modify the sample rate responsive to the level of activity.

4. The apparatus of claim 3, wherein the sample rate controller is further configured to:

receive a first subset of usage data from the activity processor indicating a first level of activity; and

select a first sample rate as a function of the first subset of usage data.

5. The apparatus of claim 4, wherein the first level of activity is indicative of motion associated with running

6. The apparatus of claim 3, wherein the sample rate controller is further configured to:

receive a second subset of usage data from the activity processor indicating a second level of activity; and

select a second sample rate as a function of the second subset of usage data.

7. The apparatus of claim 6, wherein the second level of activity is indicative of motion associated with sleeping.

8. The apparatus of claim 1, wherein the sample rate controller is configured to:

monitor a spectrum of the motion sensor signal; and

inject generated noise into a frequency band to form a noise-injected sample rate signal.

9. The apparatus of claim 8, wherein the sample rate controller is further configured to:

modify the sample rate of the noise-injected sample rate signal.

10. The apparatus of claim 8, wherein the generated noise has a magnitude substantially similar to a sensor noise floor of the motion sensor.

11. A method comprising:

receiving data representing a motion sensor signal from a motion sensor disposed in a housing of a wearable device;

monitoring a spectrum associated with the motion sensor signal;

modifying a sample rate of the motion sensor signal to form an adjusted sample rate based on an amount of energy associated with the spectrum;

generating intermediate motion signals using the calibrated motion sensor signal; and

identifying an activity based on the intermediate motion signals.

12. The method of claim 11, wherein monitoring the spectrum comprises:

determining the amount of energy associated with one or more frequency bands;

iterating the calibration of the calibrated motion sensor signal.

13. The method of claim 12, wherein determining the amount of energy associated with the one or more frequency bands comprises:

determining the amount of energy associated one or more upper frequency bands.

14. The method of claim 12, further comprising:

determining the amount of energy associated is near or at a noise floor of the motion sensor; and

reducing the sample rate to form the adjusted sample rate.

15. The method of claim 12, further comprising:

determining the amount of energy associated is greater than a noise floor of the motion sensor; and

increasing the sample rate to form the adjusted sample rate.

16. The method of claim 11, further comprising:

generating noise energy equivalent to a noise floor of the motion sensor;

injecting the noise energy into one or more frequency bands; and

adjusting rate at which the sample rate changes responsive to injecting the noise energy.

17. The method of claim 11, further comprising:

determining an activity level; and

generating control data to modify the sample rate responsive to the level of activity.

18. The method of claim 17, further comprising:

receiving usage data;

determining a subset of the usage data is associated with one of a first subset of usage data indicating a first level of activity and a second subset of usage data indicating a second level of activity; and

selecting the adjusted sample rate as a function of the subset of usage data.

19. The method of claim 18, wherein selecting the adjusted sample rate comprises:

determining the subset of the usage data is associated with the first subset of usage data indicating the first level of activity; and

increasing the sample rate to form the adjusted sample rate,

wherein the first level of activity is associated with a higher level of activity than the second level of activity.

20. The method of claim 19, further comprising:

capturing increased amounts of data.