Activating applications based on accelerometer data

• US 8,065,508 B2
• Filed: 11/10/2008
• Issued: 11/22/2011
• Est. Priority Date: 11/09/2007
• Status: Active Grant

• Current Assignee: Google LLC (Alphabet Inc.)
• Original Assignee: Google Inc. (Alphabet Inc.)
• Inventors: Rubin, Andrew E., Conway, David P.
• Primary Examiner(s): BUTLER, DENNIS
• Application Number:
  US12/268,279
• Publication Number:
  US 20090132197A1
• Time in Patent Office: 1,107 Days
• Field of Search: None
• US Class Current: 713/1
• 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 5/6898 Portable consumer electronic devices, e.g. music players, telephones, tablet computers
• CPC Class Codes: G01C 21/12 executed aboard the object being navigated; Dead reckoning
• CPC Class Codes: G01C 21/20 Instruments for performing navigational calculations G01C21/24, G01C21/26 take precedence
• 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 15/177 Initialisation or configuration control processor initialisation G06F9/4405
• CPC Class Codes: G06N 20/00 Machine learning
• CPC Class Codes: G06N 5/022 Knowledge engineering; Knowledge acquisition
• CPC Class Codes: H04L 67/535 Tracking the activity of the user network monitoring arrangements H04L43/00; recording of computer activity G06F11/34
• CPC Class Codes: H04M 1/72448 with means for adapting the functionality of the device according to specific conditions
• CPC Class Codes: H04M 1/72451 according to schedules, e.g. using calendar applications
• CPC Class Codes: H04M 1/72457 according to geographic location
• CPC Class Codes: H04M 2250/10 including a GPS signal receiver
• CPC Class Codes: H04M 2250/12 including a sensor for measuring a physical value, e.g. temperature or motion telephones including GPS signal receivers H04M2250/10
• CPC Class Codes: H04W 4/00 Services specially adapted for wireless communication networks; Facilities therefor
• CPC Class Codes: H04W 4/027 using movement velocity, acceleration information

Abstract

In some implementations, a computer-implemented method includes storing a plurality of acceleration profiles in a mobile device; receiving accelerometer data from an accelerometer in the mobile device; correlating the accelerometer data with one accelerometer profile in the plurality of accelerometer profiles; and activating a user application of the mobile device that is associated with the correlated accelerometer profile. Each acceleration profile can correspond to a sequence of acceleration forces a mobile device would be subjected to when carried with a user during an activity that corresponds to the correlated acceleration profile.

Claims

1. A computer-implemented method comprising:

storing a plurality of acceleration profiles, each acceleration profile corresponding to a sequence of acceleration forces a mobile device would be subjected to when carried with a user during one of a plurality of activities corresponding to the plurality of acceleration profiles, each acceleration profile being further associated with a time at which user input was received to launch one of a plurality of user applications that are associated with the plurality of acceleration profiles;

receiving accelerometer data from an accelerometer in the mobile device;

correlating the accelerometer data with one acceleration profile in the plurality of acceleration profiles; and

activating the user application of the mobile device that is associated with the correlated one acceleration profile.

2. The computer-implemented method of claim 1, wherein a particular acceleration profile of the acceleration profiles is generated based on analysis of a plurality of devices that are distinct from the mobile device.

3. The computer-implemented method of claim 2, wherein the particular acceleration profile is pre-stored in the mobile device before the mobile device is delivered to the user.

4. The computer-implemented method of claim 2, wherein the particular acceleration profile is wirelessly downloaded from a content provider to the mobile device.

5. The computer-implemented method of claim 1, wherein at least one sequence of acceleration forces is stored by the mobile device during a training mode in which actual acceleration forces to which the mobile device is subjected are sampled in real-time and stored in the mobile device.

6. The computer-implemented method of claim 1, wherein correlating comprises sampling the received accelerometer data and comparing the sampled accelerometer data to one or more of the plurality of acceleration profiles using a comparison algorithm to determine if the sampled accelerometer data matches an acceleration profile in the plurality of acceleration profiles.

7. The computer-implemented method of claim 1, wherein storing the plurality of acceleration profiles comprises storing the plurality of acceleration profiles at a network-accessible location external to the mobile device;

wherein correlating the accelerometer data comprises accessing the network-accessible location after receiving the accelerometer data.

8. The computer-implemented method of claim 1, wherein correlating the accelerometer data comprises processing the accelerometer data to remove effects of positional orientation of the mobile device.

9. The computer-implemented method of claim 8, wherein processing the accelerometer data comprises translating multi-axis accelerometer data to a different coordinate system than a coordinate system in which the multi-axis data was captured.

10. A method of automatically activating an application in a mobile device that runs a plurality of applications, the method comprising:

in a training mode;

receiving training acceleration data for a mobile computing device,

receiving user input to launch an application in the plurality of applications,

generating one or more training signatures based on the received acceleration data and the user input,

receiving additional acceleration data for the mobile computing device and additional user input to launch the application, and

adaptively refining the one or more training signatures, wherein the training signature is further generated based on a time at which the user input is received;

receiving accelerometer data from an accelerometer in the mobile computing device;

generating a signature based on the received accelerometer data;

correlating the generated signature to an acceleration profile that is stored in the mobile computing device; and

activating an application in the mobile computing device that is associated with the acceleration profile to which the generated signature is correlated.

11. The method of claim 10, wherein correlating comprises comparing the generated signature to one or more acceleration profiles that are stored in the mobile computing device and determining when the generated signature and one of the one or more acceleration profiles match within a threshold measure of similarity.

12. The method of claim 10, wherein receiving training acceleration data comprises receiving data from the accelerometer in the mobile computing device.

13. The method of claim 12, wherein the training acceleration data comprises acceleration data for the mobile computing device in at least two axes.

14. The method of claim 13, wherein receiving training acceleration data comprises periodically receiving the training acceleration data for the mobile computing device at a rate of at least 25 Hz.

15. The method of claim 10, further comprising storing the received training acceleration data in a first-in, first-out circular buffer such that a predetermined amount of recently received training acceleration data is stored at a given time.

16. The method of claim 10, wherein the training signature is further generated based on a day of the week on which the user input is received.

17. The method of claim 10, wherein the training signature is further generated based on a location of the mobile computing device when the user input is received.

18. The method of claim 10, further comprising generating a first training signature based on the training acceleration data and the user input to launch the application being received at a first time, and generating a second, distinct training signature based on second training acceleration data and second user input to launch the application being received at a second time that is different than the first time by at least a predetermined threshold.

19. The method of claim 10, wherein generating the training signature comprises generating the training signature based on the training acceleration data being received for a predetermined period of time prior to receiving the user input to launch the application.

20. The method of claim 19, wherein generating the training signature further comprises generating the training signature based on second training acceleration data that is received for a second predetermined period of time following receiving the user input to launch the application.

21. A method of automatically activating an application in a mobile device that runs a plurality of applications, the method comprising:

receiving training acceleration data for a mobile device;

receiving user input to launch an application in the plurality of applications;

generating a training signature based on (a) the received training acceleration data, (b) the user input, and (c) a time at which the user input is received;

receiving accelerometer data from an accelerometer in the mobile device;

generating a signature based on the received accelerometer data;

correlating the generated signature to the training signature; and

activating the application in the mobile device that is associated with the training signature to which the generated signature is correlated.

22. The method of claim 21, wherein correlating comprises comparing the generated signature to one or more existing training signatures that are stored in a network-accessible device that is external to the mobile device.

23. The method of claim 21, further comprising receiving confirmation input from a user of the mobile device prior to activating the application.

24. The method of claim 21, wherein the training signature is further generated based on a day of the week on which the user input is received.

25. A system comprising:

a programmable processor; and

a computer-readable storage medium coupled to the processor and having instructions stored therein, which when executed by the processor causes the processor to perform a method that includes;

storing a plurality of acceleration profiles, each acceleration profile corresponding to a sequence of acceleration forces a mobile device would be subjected to when carried with a user during one of a plurality of activities corresponding to the plurality of acceleration profiles, each acceleration profile being further associated with a time at which user input was received to launch one of a plurality of user applications that are associated with the plurality of acceleration profiles;

receiving accelerometer data from an accelerometer in the mobile device;

correlating the accelerometer data with one acceleration profile in the plurality of acceleration profiles; and

activating the user application of the mobile device that is associated with the correlated one acceleration profile.

26. A system comprising:

a programmable processor; and

a computer-readable storage medium coupled to the processor and having instructions stored therein, which when executed by the processor causes the processor to perform a method that includes;

receiving training acceleration data for a mobile device;

receiving user input to launch an application in a plurality of applications;

generating a training signature based on (a) the received training acceleration data, (b) the user input, and (c) a time at which the user input is received;

receiving accelerometer data from an accelerometer in the mobile device;

generating a signature based on the received accelerometer data;

correlating the generated signature to the training signature; and

activating the application in the mobile device that is associated with the training signature to which the generated signature is correlated.