Adjusting a power mode of a wearable computing device based on motion data

• US 9,009,516 B1
• Filed: 06/03/2014
• Issued: 04/14/2015
• Est. Priority Date: 02/19/2014
• Status: Active Grant

• Current Assignee: Google LLC (Alphabet Inc.)
• Original Assignee: Google Inc. (Alphabet Inc.)
• Inventors: Gabayan, Kevin, Brown, William Haldean
• Primary Examiner(s): Bae, Ji H
• Application Number:
  US14/295,295
• Time in Patent Office: 315 Days
• Field of Search: None
• US Class Current: 713/323
• CPC Class Codes: G01P 15/003 Kinematic accelerometers, i.e. measuring acceleration in relation to an external reference frame, e.g. Ferratis accelerometers G01P15/001, G01P15/16, G01P15/165 take precedence
• CPC Class Codes: G01P 15/165 for measuring angular accelerations
• CPC Class Codes: G01P 15/18 in two or more dimensions
• CPC Class Codes: G01P 3/44 for measuring angular speed G01P3/56 takes precedence
• CPC Class Codes: G06F 1/163 Wearable computers, e.g. on a belt
• CPC Class Codes: G06F 1/1694 the I/O peripheral being a single or a set of motion sensors for pointer control or gesture input obtained by sensing movements of the portable computer
• CPC Class Codes: G06F 1/26 Power supply means, e.g. regulation thereof for memories G11C
• CPC Class Codes: G06F 1/3206 Monitoring of events, devices or parameters that trigger a change in power modality
• CPC Class Codes: G06F 1/3231 Monitoring the presence, absence or movement of users
• CPC Class Codes: G06F 1/3265 Power saving in display device
• CPC Class Codes: G06F 1/3287 by switching off individual functional units in the computer system
• CPC Class Codes: G06F 3/017 Gesture based interaction, e.g. based on a set of recognized hand gestures interaction based on gestures traced on a digitiser G06F3/04883
• CPC Class Codes: Y02D 10/00 Energy efficient computing, e.g. low power processors, power management or thermal management

Abstract

In one example, a method includes determining, based on motion data generated by a motion sensor of a wearable computing device, a plurality of motion vectors, wherein one or more components operatively coupled to the wearable computing device are operating in a first power mode during a first time period; determining, based on the plurality of motion vectors, a plurality of values. In this example, the method also includes, responsive to determining that each of the plurality of values satisfies a corresponding threshold, transitioning, by at least one component of the one or more components, from operating in the first power mode to operating in a second power mode.

Claims

1. A method comprising:

determining, by a processor of a wearable computing device and based on motion data generated by a motion sensor of the wearable computing device, a plurality of motion vectors, wherein one or more components of the wearable computing device are operating in a first power mode during a first time period, and wherein the motion data indicates movement of the wearable computing device during the first time period;

determining, by the processor, that a first angle between a first motion vector of the plurality of motion vectors and a second motion vector of the plurality of motion vectors satisfies a first angular threshold, wherein the first motion vector is associated with a first time, wherein the second motion vector is associated with a second time, and wherein the second time is later than the first time;

determining, by the processor, that a time difference between the first time and the second time satisfies a threshold amount of time;

determining, by the processor, that a second angle between a plane parallel to a display of the wearable computing device and a plane perpendicular to a gravity vector satisfies a second angular threshold; and

responsive to determining that the first angle satisfies the first angular threshold, that the time difference satisfies the threshold amount of time, and that the second angle satisfies the second angular threshold, transitioning, by at least one component of the one or more components, from operating in the first power mode to operating in a second power mode, wherein the at least one component consumes more power while operating in the second power mode than while operating in the first power mode.

2. The method of claim 1, further comprising:

determining a plurality of difference vectors, wherein each respective difference vector from the plurality of difference vectors is based on a respective difference between at least two respective motion vectors from the plurality of motion vectors;

determining, based on a first subset of the plurality of difference vectors, a first energy value;

responsive to determining that the first energy value satisfies an energy threshold, determining that a particular difference vector from the first subset is based on the first motion vector;

determining, based on a second subset of the plurality of difference vectors, a second energy value, wherein the first subset includes at least one difference vector from the plurality of difference vectors not included in the second subset, and wherein the second subset includes at least one difference vector from the plurality of difference vectors not included in the first subset; and

responsive to determining that the second energy value does not satisfy the energy threshold and that the particular difference vector from the first subset is based on the first motion vector, determining that a particular difference vector from the second subset and not from the first subset is based on the second motion vector.

3. The method of claim 2, wherein the first subset and the second subset include a same number of difference vectors.

4. The method of claim 2, wherein:

determining the first energy value comprises determining a sum of the squared norms of each difference vector from the first subset, and

determining the second energy value comprises determining a sum of the squared norms of each difference vector from the second subset.

5. The method of claim 1, wherein each motion vector from the plurality of motion vectors is a respective filtered motion vector determined based on a moving average of a plurality of unfiltered motion vectors, the plurality of unfiltered motion vectors being determined based on the motion data.

6. The method of claim 1, wherein:

the motion sensor includes an accelerometer, and

the wearable computing device does not include a gyroscope.

7. The method of claim 1, wherein the one or more components include at least one of:

a display; and

an application processor, wherein the application processor is not the processor.

8. The method of claim 7, wherein transitioning, by the at least one component of the one or more components, from operating in the first power mode to operating in the second power mode comprises activating the display.

9. The method of claim 1, further comprising:

responsive to determining that the first angle satisfies the first angular threshold, that the time difference satisfies the threshold amount of time, and that the second angle satisfies the second angular threshold, determining, by the processor, that a user of the wearable computing device is likely viewing the wearable computing device.

10. The method of claim 1, wherein the threshold amount of time is a first threshold amount of time, the method further comprising:

determining that a particular value of a current motion vector of the plurality of motion vectors satisfies a motion threshold;

determining that a particular value of a previous motion vector of the plurality of motion vectors does not satisfy the motion threshold, wherein the particular value of the current motion vector and the particular value of the previous motion vector are both associated with a particular axis of motion;

determining a plurality of difference vectors, wherein each respective difference vector from the plurality of difference vectors is based on a respective difference between at least two respective motion vectors from the plurality of motion vectors;

determining that a first energy value based on a first subset of the plurality of difference vectors satisfies a first energy threshold;

responsive to determining that the particular value of the current motion vector satisfies the motion threshold, that the particular value of the previous motion vector does not satisfy the motion threshold, and that the first energy value satisfies the first energy threshold, determining that the current motion vector is the first motion vector and that a user of the wearable computing device is walking at the first time;

determining, based on a second subset of the plurality of difference vectors, a second energy value, wherein the first subset includes at least one difference vector from the plurality of difference vectors not included in the second subset, and wherein the second subset includes at least one difference vector from the plurality of difference vectors not included in the first subset; and

responsive to determining that the second energy value does not satisfy a second energy threshold, determining that a particular difference vector from the second subset and not from the first subset is based on the second motion vector.

11. The method of claim 10, wherein a difference vector from the plurality of difference vectors included in the second subset but not included in the first subset is associated with a third time, the method further comprising:

responsive to determining that a time difference between the first time and the third time satisfies a second threshold amount of time, determining that the user of the wearable computing device is still walking at the third time, wherein the third time is later than the first time;

responsive to determining that the user of the wearable computing device is still walking at the third time, determining whether or not the second energy value satisfies the second energy threshold.

12. The method of claim 10, further comprising:

determining the first energy value based on values of the first set of difference vectors; and

determining the second energy value based on values of the second set of difference vectors, wherein the values of the first set of difference vectors the values of the second set of difference vectors are both associated with the particular axis of motion.

13. The method of claim 10, further comprising:

determining, based on values of a set of the plurality of motion vectors that are associated with the particular axis of motion, the motion threshold.

14. A wearable computing device comprising:

a plurality of processors including;

a first motion processor; and

an application processor;

a motion sensor;

a display; and

a storage device storing at least one module, wherein the at least one module is executable by at least one of the plurality of processors to;

determine, based on motion data generated by the motion sensor, a plurality of motion vectors, wherein one or more components of the wearable computing device are operating in a first power mode during a first time period, and wherein the motion data indicates movement of the wearable computing device during the first time period;

determine that a first angle between a first motion vector of the plurality of motion vectors and a second motion vector of the plurality of motion vectors satisfies a first angular threshold, wherein the first motion vector is associated with a first time, wherein the second motion vector is associated with a second time, and wherein the second time is later than the first time;

determine that a time difference between the first time and the second time satisfies a threshold amount of time;

determine that a second angle between a plane parallel to the display and a plane perpendicular to a gravity vector satisfies a second angular threshold; and

responsive to determining that the first angle satisfies the first angular threshold, that the time difference satisfies the threshold amount of time, and that the second angle satisfies the second angular threshold, cause at least one component of the one or more components to transition, from operating in the first power mode to operating in a second power mode, wherein the at least one component consumes more power while operating in the second power mode than while operating in the first power mode.

15. The wearable computing device of claim 14, wherein the at least one module is further executable by the at least one processor to:

determine a plurality of difference vectors, wherein each respective difference vector from the plurality of difference vectors is based on a respective difference between at least two respective motion vectors from the plurality of motion vectors;

determine, based on a first subset of the plurality of difference vectors, a first energy value;

responsive to determining that the first energy value satisfies an energy threshold, determine that a particular difference vector from the first subset is based on the first motion vector;

determine, based on a second subset of the plurality of difference vectors, a second energy value, wherein the first subset includes at least one difference vector from the plurality of difference vectors not included in the second subset, and wherein the second subset includes at least one difference vector from the plurality of difference vectors not included in the first set; and

responsive to determining that the second energy value does not satisfy the energy threshold and that the particular difference vector from the first subset is based on the first motion vector, determine that a particular difference vector from the second subset and not from the first subset is based on the second motion vector.

16. The wearable computing device of claim 15, wherein the first subset and the second subset include a same number of difference vectors.

17. The wearable computing device of claim 15, wherein:

the at least one module is executable by the at least one processor to determine the first energy value by at least determining a sum of the squared norms of each difference vector from the first subset, and

the at least one module is executable by the at least one processor to determine the second energy value by at least determining a sum of the squared norms of each difference vector from the second subset.

18. The wearable computing device of claim 14, wherein each motion vector from the plurality of motion vectors is a respective filtered motion vector determined based on a moving average of unfiltered motion vectors, the plurality of unfiltered motion vectors being determined based on the motion data.

19. The wearable computing device of claim 14, wherein:

the motion sensor includes an accelerometer, and

the wearable computing device does not include a gyroscope.

20. The wearable computing device of claim 14, wherein the one or more components include at least one of:

the display; and

the application processor.

21. The wearable computing device of claim 20, wherein the at least one module is executable by the at least one processor to transition, by the at least one component of the one or more components, from operating in the first power mode to operating in the second power mode by at least activating the display.

22. The wearable computing device of claim 14, wherein the at least one module is further executable by the at least one processor to:

responsive to determining that the first angle satisfies the first angular threshold, that the time difference satisfies the threshold amount of time, and that the second angle satisfies the second angular threshold, determine, that a user of the wearable computing device is likely viewing the wearable computing device.

23. The wearable computing device of claim 14, wherein the threshold amount of time is a first threshold amount of time, wherein the at least one module is further executable by the at least one processor to:

determine that a particular value of a current motion vector of the plurality of motion vectors satisfies a motion threshold;

determine that a particular value of a previous motion vector of the plurality of motion vectors does not satisfy the motion threshold, wherein the particular value of the current motion vector and the particular value of the previous motion vector are both associated with a particular axis of motion;

determine a plurality of difference vectors, wherein each respective difference vector from the plurality of difference vectors is based on a respective difference between at least two respective motion vectors from the plurality of motion vectors;

determine that a first energy value based on a first subset of the plurality of difference vectors satisfies a first energy threshold;

responsive to determining that the particular value of the current motion vector satisfies the motion threshold, that the particular value of the previous motion vector does not satisfy the motion threshold, and that the first energy value satisfies the first energy threshold, determine that the current motion vector is the first motion vector and that a user of the wearable computing device is walking at the first time;

determine, based on a second subset of the plurality of difference vectors, a second energy value, wherein the first subset includes at least one difference vector from the plurality of difference vectors not included in the second subset, and wherein the second subset includes at least one difference vector from the plurality of difference vectors not included in the first subset; and

responsive to determining that the second energy value does not satisfy a second energy threshold, determine that a particular difference vector from the second subset and not from the first subset is based on the second motion vector.

24. The wearable computing device of claim 23, wherein a difference vector from the plurality of difference vectors included in the second subset but not included in the first subset is associated with a third time, and wherein the at least one module is executable by the at least one processor to:

responsive to determining that a time difference between the first time and the third time satisfies a second threshold amount of time, determine that the user of the wearable computing device is still walking at the third time, wherein the third time is later than the first time;

responsive to determining that the user of the wearable computing device is still walking at the third time, determine whether or not the second energy value satisfies the second energy threshold.

25. The wearable computing device of claim 23, wherein the at least one module is executable by the at least one processor to:

determine the first energy value based on values of the first set of difference vectors; and

determine the second energy value based on values of the second set of difference vectors, wherein the values of the first set of difference vectors the values of the second set of difference vectors are both associated with the particular axis of motion.

26. The wearable computing device of claim 23, wherein the at least one module is executable by the at least one processor to:

determine, based on values of a set of the plurality of motion vectors that are associated with the particular axis of motion, the motion threshold.

27. A non-transitory computer-readable storage medium storing instructions that, when executed, cause at least one processor of a wearable computing device to:

determine, based on motion data generated by a motion sensor of the wearable computing device, a plurality of motion vectors, wherein one or more components operatively coupled to the wearable computing device are operating in a first power mode during a first time period, and wherein the motion data indicates movement of the wearable computing device during the first time period;

determine that a first angle between a first motion vector of the plurality of motion vectors and a second motion vector of the plurality of motion vectors satisfies a first angular threshold, wherein the first motion vector is associated with a first time, wherein the second motion vector is associated with a second time, and wherein the second time is later than the first time;

determine that a time difference between the first time and the second time satisfies a threshold amount of time;

determine that a second angle between a plane parallel to a display of the wearable computing device and a plane perpendicular to a gravity vector satisfies a second angular threshold; and

responsive to determining that the first angle satisfies the first angular threshold, that the time difference satisfies the threshold amount of time, and that the second angle satisfies the second angular threshold, at least one component of the one or more components to transition, from operating in the first power mode to operating in a second power mode, wherein the at least one component consumes more power while operating in the second power mode than while operating in the first power mode.

28. The non-transitory computer-readable storage medium of claim 27, further storing instructions that, when executed, cause the at least one processor to:

determine a plurality of difference vectors, wherein each respective difference vector from the plurality of difference vectors is based on a respective difference between at least two respective motion vectors from the plurality of motion vectors;

determine, based on a first subset of the plurality of difference vectors, a first energy value;

responsive to determining that the first energy value satisfies an energy threshold, determine that a particular difference vector from the first subset is based on the first motion vector;

determine, based on a second subset of the plurality of difference vectors, a second energy value, wherein the first subset includes at least one difference vector from the plurality of difference vectors not included in the second subset, and wherein the second subset includes at least one difference vector from the plurality of difference vectors not included in the first subset; and

responsive to determining that the second energy value does not satisfy the energy threshold and that the particular difference vector from the first subset is based on the first motion vector, determine that a particular difference vector from the second subset and not from the first subset is based on the second motion vector.

29. A method comprising:

determining, by a processor of a wearable computing device and based on motion data generated by a motion sensor of the wearable computing device, a plurality of motion vectors, wherein one or more components of the wearable computing device are operating in a first power mode during a first time period, and wherein the motion data indicates movement of the wearable computing device during the first time period;

responsive to determining, by the processor, that a first energy value based on a first subset of the plurality of motion vectors satisfies a first energy threshold, determining that a particular motion vector from the first subset is a starting motion vector;

responsive to determining, by the processor, that a second energy value based on a second subset of the plurality of motion vectors satisfies a second energy threshold, determining that a particular motion vector from the second subset is an ending motion vector, wherein the first subset includes at least one motion vector from the plurality of motion vectors not included in the second subset, and wherein the second subset includes at least one motion vector from the plurality of motion vectors not included in the first subset; and

responsive to determining, by the processor, that a difference between the starting motion vector and the ending motion vector indicates that a user of the wearable computing device is viewing the wearable computing device, transitioning, by at least one component of the one or more components, from operating in the first power mode to operating in a second power mode, wherein the at least one component consumes more power while operating in the second power mode than while operating in the first power mode.

30. The method of claim 29, wherein determining, by the processor, that the difference between the starting motion vector and the ending motion vector indicates that the user of the wearable computing device is viewing the wearable computing device comprises:

determining, by the processor, that a first angle between the starting motion vector and the ending motion vector satisfies a first angular threshold, wherein the starting motion vector is associated with a first time, wherein the ending motion vector is associated with a second time, and wherein the second time is later than the first time;

determining, by the processor, that a time difference between the first time and the second time satisfies a threshold amount of time; and

determining, by the processor, that a second angle between a plane parallel to a display of the wearable computing device and a plane perpendicular to a gravity vector satisfies a second angular threshold.

31. A wearable computing device comprising:

a plurality of processors including;

a first motion processor; and

an application processor;

a motion sensor;

a display; and

a storage device storing at least one module, wherein the at least one module is executable by at least one of the plurality of processors to;

determine, based on motion data generated by the motion sensor, a plurality of motion vectors, wherein one or more components of the wearable computing device are operating in a first power mode during a first time period, and wherein the motion data indicates movement of the wearable computing device during the first time period;

responsive to determining that a first energy value based on a first subset of the plurality of motion vectors satisfies a first energy threshold, determine that a particular motion vector from the first subset is a starting motion vector;

responsive to determining that a second energy value based on a second subset of the plurality of motion vectors satisfies a second energy threshold, determine that a particular motion vector from the second subset is an ending motion vector, wherein the first subset includes at least one motion vector from the plurality of motion vectors not included in the second subset, and wherein the second subset includes at least one motion vector from the plurality of motion vectors not included in the first subset; and

responsive to determining that a difference between the starting motion vector and the ending motion vector indicates that a user of the wearable computing device is viewing the wearable computing device, cause at least one component of the one or more components to transition from operating in the first power mode to operating in a second power mode, wherein the at least one component consumes more power while operating in the second power mode than while operating in the first power mode.

32. The wearable computing device of claim 31, wherein the at least one module is executable by at least one of the plurality of processors to determine that the difference between the starting motion vector and the ending motion vector indicates that the user of the wearable computing device is viewing the wearable computing device by at least:

determining that a first angle between the starting motion vector and the ending motion vector satisfies a first angular threshold, wherein the starting motion vector is associated with a first time, wherein the ending motion vector is associated with a second time, and wherein the second time is later than the first time;

determining that a time difference between the first time and the second time satisfies a threshold amount of time; and

determining that a second angle between a plane parallel to a display of the wearable computing device and a plane perpendicular to a gravity vector satisfies a second angular threshold.

33. A non-transitory computer-readable storage medium storing instructions that, when executed, cause at least one processor of a wearable computing device to:

determine, based on motion data generated by a motion sensor of the wearable computing device, a plurality of motion vectors, wherein one or more components of the wearable computing device are operating in a first power mode during a first time period, and wherein the motion data indicates movement of the wearable computing device during the first time period;

responsive to determining that a first energy value based on a first subset of the plurality of motion vectors satisfies a first energy threshold, determine that a particular motion vector from the first subset is a starting motion vector;

responsive to determining that a second energy value based on a second subset of the plurality of motion vectors satisfies a second energy threshold, determine that a particular motion vector from the second subset is an ending motion vector, wherein the first subset includes at least one motion vector from the plurality of motion vectors not included in the second subset, and wherein the second subset includes at least one motion vector from the plurality of motion vectors not included in the first subset; and

responsive to determining that a difference between the starting motion vector and the ending motion vector indicates that a user of the wearable computing device is viewing the wearable computing device, cause at least one component of the one or more components to transition from operating in the first power mode to operating in a second power mode, wherein the at least one component consumes more power while operating in the second power mode than while operating in the first power mode.

34. The non-transitory computer-readable storage medium of claim 33, wherein the instructions that cause the at least one processor to determine that the difference between the starting motion vector and the ending motion vector indicates that the user of the wearable computing device is viewing the wearable computing device comprise instructions that cause the at least one processor to:

determine that a first angle between the starting motion vector and the ending motion vector satisfies a first angular threshold, wherein the starting motion vector is associated with a first time, wherein the ending motion vector is associated with a second time, and wherein the second time is later than the first time;

determine that a time difference between the first time and the second time satisfies a threshold amount of time; and

determine that a second angle between a plane parallel to a display of the wearable computing device and a plane perpendicular to a gravity vector satisfies a second angular threshold.