Methods and devices for identifying users based on tremor

• US 20050243061A1
• Filed: 05/02/2005
• Published: 11/03/2005
• Est. Priority Date: 04/30/2004
• Status: Active Grant

• Current Assignee: DRNC Holdings, Inc. (InterDigital, Inc.)
• Original Assignee: Hillcrest Communications, Inc. (CEVA Incorporated)
• Inventors: Liberty, Matthew G., Simpkins, Daniel S., Roller, Christopher D., Gritton, Charles W.K.
• Granted Patent: US 7,236,156 B2
• Time in Patent Office: Days
• US Class Current: 345/158
• CPC Class Codes: A61B 5/1101 Detecting tremor
• CPC Class Codes: A61B 5/117 Identification of persons methods or arrangements for recognising patterns, e.g. fingerprints, G06F18/00, G06V40/00; identification of persons by analysing their voice or speech G10L17/00
• CPC Class Codes: A61B 5/1171 based on the shapes or appearances of their bodies or parts thereof
• CPC Class Codes: A61B 5/6825 Hand
• CPC Class Codes: A61B 5/6897 Computer input devices, e.g. mice or keyboards
• CPC Class Codes: G06F 21/32 using biometric data, e.g. fingerprints, iris scans or voiceprints
• 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: G06F 3/0346 with detection of the device orientation or free movement in a 3D space, e.g. 3D mice, 6-DOF [six degrees of freedom] pointers using gyroscopes, accelerometers or tilt-sensors
• CPC Class Codes: G06F 3/038 Control and interface arrangements therefor, e.g. drivers or device-embedded control circuitry
• CPC Class Codes: G06V 40/10 Human or animal bodies, e.g. vehicle occupants or pedestrians; Body parts, e.g. hands
• CPC Class Codes: G08C 2201/32 Remote control based on movements, attitude of remote control device
• CPC Class Codes: G08C 2201/61 Password, biometric
• CPC Class Codes: H04N 21/42204 User interfaces specially adapted for controlling a client device through a remote control device; Remote control devices therefor constructive details of casings for the remote control device H01H9/0235; user interfaces for controlling a tuning device of a television receiver through a remote control H03J9/00; remote control of peripheral devices connected to a television receiver through the remote control device of the television receiver H04B1/205
• CPC Class Codes: H04N 21/42222 Additional components integrated in the remote control device, e.g. timer, speaker, sensors for detecting position, direction or movement of the remote control, microphone or battery charging device

Abstract

Systems and methods according to the present invention address these needs and others by providing a handheld device, e.g., a free space pointing device, which uses hand tremor as an input. One or more sensors within the handheld device detect a user'"'"'s hand tremor and identify the user based on the detected tremor.

Claims

1. A handheld, pointing device comprising:

a first rotational sensor for determining rotation of said pointing device about a first axis and generating a first rotational output associated therewith;

a second rotational sensor for determining rotation of said pointing device about a second axis and generating a second rotational output associated therewith;

an accelerometer for determining an acceleration of said pointing device and outputting an acceleration output associated therewith; and

a processing unit for receiving said first and second rotational outputs and said acceleration output and for;

(a) establishing, during a training period, a plurality of hand tremor classes each of which is associated with a user by processing training data derived from at least one of said first and second rotational outputs and said acceleration output while said user is holding said pointing device without intentional movement; and

(b) determining, subsequent to said training period, an identity of a current user of said pointing device by comparing data derived from at least one of a current first rotational output, a current second rotational output and a current acceleration output to said plurality of hand tremor classes established during said training period.

2. The pointing device of claim 1, wherein said first rotational sensor further comprises:

a first resonating mass attached to a first frame, wherein said first resonating mass in said first rotational sensor resonates along said first axis;

wherein displacement of said first resonating mass along said first axis is measured by said first rotational sensor using the Coriolis acceleration effect to generate said first rotational output.

3. The pointing device of claim 2, wherein said second rotational sensor further comprises:

a second resonating mass attached to a second frame, wherein said second resonating mass in said second rotational sensor resonates along said second axis;

wherein displacement of said second resonating mass along said second axis is measured by said second rotational sensor using the Coriolis acceleration effect to generate said second rotational output.

4. A method for identifying a user of a handheld device comprising the steps of:

detecting a hand tremor associated with a user holding said handheld device; and

identifying said user based on said detected hand tremor.

5. The method of claim 4, further comprising the step of:

selectively turning on a system associated with said handheld device on based upon said step of identifying.

6. The method of claim 4, further comprising the step of:

restricting access to a system associated with said handheld device based upon an identity of said user.

7. The method of claim 6, wherein said system is a media system and said step of restricting access further comprises the step of:

selectively permitting said user to access a media item based upon said identifying step.

8. The method of claim 4, further comprising the step of:

determining an identity of said user by comparing a set of detected tremor features with a plurality of stored tremor classes.

9. The method of claim 8, wherein said detected tremor features and said plurality of stored tremor classes are associated with frequency domain data.

10. The method of claim 8, wherein said detected tremor features and said plurality of stored tremor classes are associated with time domain data.

11. The method of claim 8, wherein if a match does not occur between said detected tremor features and said plurality of stored tremor classes, then said detected tremor features are used to establish a new user identity.

12. The method of claim 8, wherein if a match does not occur between said tremor features and said plurality of stored tremor classes, then said user is assigned a default set of system access permissions.

13. The method of claim 4, further comprising the step of:

retrieving preference settings associated with said user in response to said identifying step.

14. A handheld device comprising:

at least one motion sensor capable of generating data associated with movement of said handheld device; and

a processing unit for detecting hand tremor data based on said movement data and for identifying a user based on said hand tremor data.

15. The handheld device of claim 14, wherein said at least one motion sensor includes at least one of:

a rotational sensor, a gyroscope, an accelerometer, an inertial sensor, a magnetic sensor, an optical sensor and a camera.

16. The handheld device of claim 14, wherein said processing unit detects said hand tremor data in a frequency domain.

17. The handheld device of claim 14, wherein said processing unit detects said hand tremor data in a time domain.

18. The handheld device of claim 14, wherein said processing unit performs a pattern recognition technique adapted to distinguish between hand tremors of different users to identify said user.

19. The handheld device of claim 14, wherein said processing unit performs a training operation wherein data associated with different users holding said handheld device without introducing intentional movement thereto is recorded and processed.

20. The handheld device of claim 14, wherein said handheld device is a free space pointing device.

21. A handheld device comprising:

means for generating data associated with movement of said handheld device; and

means for detecting hand tremor data based on said movement data and for identifying a user based on said hand tremor data.

22. A computer-readable medium, capable of storing program instructions which, when executed perform the steps of:

detecting a hand tremor associated with a user holding said handheld device; and

identifying said user based on said detected hand tremor.

23. A method for operating a handheld device using hand tremor as an input thereto, the method comprising the steps of:

(a) training said handheld device by having a plurality of users each hold said handheld device for a training period;

(b) detecting movement of said handheld device during each training period;

(b) establishing, based on said training periods, a plurality of hand tremor classes each of which is associated with one of said plurality of users, by processing data derived from said detected movement for a respective training period; and

(b) determining, subsequent to said training period, an identity of a current user of said handheld device by comparing data derived from current movement of said handheld device with said plurality of hand tremor classes.

24. The method of claim 23, wherein said training period is variable as between said plurality of users.

25. The method of claim 23, wherein said users hold said handheld device without intentional movement thereof during said training periods.

26. The method of claim 23, wherein said users intentionally move said handheld device during said training periods.

27. The method of claim 23, further comprising the step of:

entering an identification of said user during said training period into a user interface associated with said handheld device; and

associating said identification with a corresponding hand tremor class.

28. A method for processing sample data from at least one motion sensor in a handheld device comprising the steps of:

(a) determining that said handheld device is in a stable state, wherein a user is holding said handheld device without intentionally introducing movement thereto; and

(b) processing sample data from said at least one motion sensor in response to said determining step.

29. The method of claim 28, wherein said step of processing further comprises the step of:

(c) using said sample data to identify a user based upon tremor data analysis.

30. The method of claim 28, wherein said step of processing includes linear filtering.

31. A method for processing sample data from at least one motion sensor in a handheld device comprising the steps of:

(a) determining that said handheld device is in an active state, wherein a user is holding said handheld device and is intentionally introducing movement thereto; and

(b) processing sample data from said at least one motion sensor in response to said determining step into first data associated with said intentional movement and second data associated with unintentional movement.

32. The method of claim 31, further comprising the step of:

(c) using said second data associated with said unintentional movement to identify a user based upon tremor data analysis.

33. The method of claim 31, wherein said processing step includes one or more of:

linear filtering, Kalman filtering, Kalman smoothing, state-space estimation, Expectation-Maximization, or other model-based techniques for separating said first data and said second data.