Adaptive system and method for altering the motion of a person

• US 20100114256A1
• Filed: 10/31/2008
• Published: 05/06/2010
• Est. Priority Date: 10/31/2008
• Status: Active Grant

• Current Assignee: Gearbox LLC (Intellectual Ventures LLC)
• Original Assignee: The Invention Science Fund I, L.L.C. (Intellectual Ventures LLC)
• Inventors: Wood, Lowell L. JR., Hyde, Roderick A., Kare, Jordin T., Chan, Alistair K.
• Granted Patent: US 8,548,581 B2
• Time in Patent Office: Days
• US Class Current: 607/62
• CPC Class Codes: A61N 1/0456 Specially adapted for transcutaneous electrical nerve stimulation [TENS]
• CPC Class Codes: A61N 1/0492 Patch electrodes A61N1/0412, A61N1/0428 take precedence
• CPC Class Codes: A61N 1/36003 of motor muscles, e.g. for walking assistance
• CPC Class Codes: A61N 1/36025 for treating a mental or cerebral condition

Abstract

A method is generally described which includes producing a sound from a sound device capable of producing sound. The sound device is in communication with a sound data source. The sound data source is associated with at least one set of sounds. The method also includes detecting motions, by a feedback sensor device, the motions associated with the user. The further the method includes providing information from an information source including information associated with at least one characteristic of the at least one set of sounds and providing the information to a control program configured to receive data representative of the detected motions and to receive the information. Further still, the method includes generating, by the control program, control data based on the data representative of the detected motions and the information. The control program is configured to receive data representative of the detected motions and to receive the information. The control program has a control algorithm configured to generate control data based on the data representative of the detected motions and the information. Further still, the method includes running the control program by a controller configured to output control signals based on the control data and adjusting parameters of at least one of the controller, the feedback sensor, the sound source, the information, or the control algorithm, by an adaptive system. Yet further still, the method includes delivering current from the current source to the vestibular system of the user in response to the control signals, by a vestibular stimulation device.

Claims

1. An adaptive system for altering a user'"'"'s motional response to sound, the system comprising:

a current source;

a sound source including at least one set of sounds;

an information source including information associated with at least one characteristic of the at least one set of sounds;

a sound device configured with a sound producing structure and in communication with the sound source;

a feedback sensor device configured to detect motions associated with a user;

a control program configure to receive data representative of the detected motions and to receive the information, the control program having a control algorithm configured to generate control data based on the data representative of the detected motions and the information;

a controller configured to run the control program and output control signals based on the control data;

an adaptive system configured to adjust parameters of at least one of the controller, the feedback sensor device, the sound source, the information, or the control algorithm; and

a vestibular stimulation device configured to deliver a current from the current source to the vestibular system of the user in response to the output control signals.

2. The system of claim 1, wherein the adaptive system includes a self-learning system.

3. The system of claim 1, wherein the adaptive system includes a self-learning system and the self-learning system includes an artificial intelligence program.

4. The system of claim 1, wherein the adaptive system includes a self-learning system and the self-learning system includes a fuzzy logic program.

5. The system of claim 1, wherein the adaptive system includes a self-learning system and the self-learning system includes a neural network program.

6. The system of claim 1, wherein the adaptive system includes an adaptive control law.

7. The system of claim 1, wherein the adaptive system includes an artificial intelligence program.

8. The system of claim 1, wherein the adaptive system includes a fuzzy logic program.

15. The system of claim 1, wherein the adaptive system is a self-learning system and the self-learning system learns during a use phase.

16. The system of claim 1, wherein the adaptive system is a self-learning system and the self-learning system learns during a training phase.

17. The system of claim 1, wherein the adaptive system is a self-learning system and the self-learning system uses a training set of data to learn.

9-14. -14. (canceled)

18. A system for altering a user'"'"'s motional response, the system comprising:

a current source;

a feedback sensor device configured to detect motions associated with a user;

an objective information source, configured to provide information related to an objective of the user'"'"'s motional response;

a control program configured to receive data representative of the detected motions and to receive the information, the control program having a control algorithm configured to generate control data based on the data representative of the detected motions and the information;

a controller configured to run the control program and output control signals based on the control data;

an adaptive system configured to adjust parameters of at least one of the controller, the feedback sensor device, the information, or the control algorithm; and

a vestibular stimulation device configured to deliver a current from the current source to the vestibular system device of the user in response to the output control signals.

19. The system of claim 18, wherein the adaptive system includes a self-learning system.

20. The system of claim 18, wherein the adaptive system includes a self-learning system and the self-learning system includes an artificial intelligence program.

21. The system of claim 18, wherein the adaptive system includes a self-learning system and the self-learning system includes a fuzzy logic program.

22. The system of claim 18, wherein the adaptive system includes a self-learning system and the self-learning system includes a neural network program.

23-32. -32. (canceled)

33. A method for altering a user'"'"'s motional response to sound, the method comprising:

producing a sound from a sound device capable of producing the sound and the sound device in communication with a sound data source, the sound data source associated with at least one set of sounds;

detecting motions, by a feedback sensor device, the motions associated with a user;

providing information from an information source including the information associated with at least one characteristic of the at least one set of sounds, providing the information to a control program configured to receive data representative of the detected motions and to receive the information;

generating, by the control program, control data based on the data representative of the detected motions and the information, the control program configured to receive the data representative of the detected motions and to receive the information, the control program having a control algorithm configured to generate control data based on the data representative of the detected motions and the information;

running the control program by a controller configured to output control signals based on the control data;

adjusting parameters of at least one of the controller, the feedback sensor device, the sound source, the information, or the control algorithm, by an adaptive system; and

delivering a current from the current source to a vestibular system of the user in response to the control signals, by a vestibular stimulation device.

34. The method of claim 33, wherein the adaptive system includes a self-learning system.

35. The method of claim 33, wherein the adaptive system includes a self-learning system and the self-learning system includes an artificial intelligence program.

36. The method of claim 33, wherein the adaptive system includes a self-learning system and the self-learning system includes a fuzzy logic program.

37. The method of claim 33, wherein the adaptive system includes a self-learning system and the self-learning system includes a neural network program.

38. The method of claim 33, wherein the adaptive system includes an adaptive control law.

39. The method of claim 33, wherein the adaptive system includes an artificial intelligence program.

40. The method of claim 33, wherein the adaptive system includes a fuzzy logic program.

41. The method of claim 33, wherein the parameters include control law parameters.

42. The method of claim 33, wherein the parameters include intensity parameters.

43. The method of claim 33, wherein the parameters include feedback sensor sensitivity parameters.

44-48. -48. (canceled)

49. An adaptive system for altering a user'"'"'s motional response to video, the system comprising:

a current source;

a video source including at least one set of images;

an information source including information associated with at least one characteristic of the at least one set of images;

a video device configured with a video producing structure and in communication with the video source;

a feedback sensor device configured to detect motions associated with a user;

a control program configure to receive data representative of the detected motions and to receive the information, the control program having a control algorithm configured to generate control data based on the data representative of the detected motions and the information;

a controller configured to run the control program and output control signals based on the control data;

an adaptive system configured to adjust parameters of at least one of the controller, the feedback sensor device, the video source, the information, or the control algorithm; and

a vestibular stimulation device configured to deliver a current from the current source to the vestibular system of the user in response to the output control signals.

57. The system of claim 49, wherein the parameters include control law parameters.

58. The system of claim 49, wherein the parameters include frame rate parameters.

59. The system of claim 49, wherein the parameters include brightness parameters.

60. The system of claim 49, wherein the parameters include user specific parameters.

61. The system of claim 49, wherein the parameters include feedback sensor sensitivity parameters.

62. The system of claim 49, wherein the parameters include feedback sensor filter parameters.

63. The system of claim 49, wherein the adaptive system is a self-learning system and the self-learning system learns during a use phase.

64. The system of claim 49, wherein the adaptive system is a self-learning system and the self-learning system learns during a training phase.

65. The system of claim 49, wherein the adaptive system is a self-learning system and the self-learning system uses a training set of data to learn.

50-56. -56. (canceled)

66. A method for altering a user'"'"'s motional response to video, the system comprising:

producing a video from a video device capable of producing the video and the video device in communication with a video data source, the video data source associated with at least one set of images;

detecting motions, by a feedback sensor device, the motions associated with a user;

providing information from an information source including the information associated with at least one characteristic of the at least one set of images, providing the information to a control program configured to receive data representative of the detected motions and to receive the information;

generating, by the control program, control data based on the data representative of the detected motions and the information, the control program configured to receive the data representative of the detected motions and to receive the information, the control program having a control algorithm configured to generate the control data based on the data representative of the detected motions and the information;

running the control program by a controller configured to output control signals based on the control data;

adjusting parameters of at least one of the controller, the feedback sensor device, the video source, the information, or the control algorithm, by an adaptive system; and

delivering a current from the current source to a vestibular system of the user in response to the output control signals, by the vestibular stimulation device.

67. The method of claim 66, wherein the adaptive system includes a self-learning system.

68. The method of claim 66, wherein the adaptive system includes a self-learning system and the self-learning system includes an artificial intelligence program.

69. The method of claim 66, wherein the adaptive system includes a self-learning system and the self-learning system includes a fuzzy logic program.

70. The method of claim 66, wherein the adaptive system includes a self-learning system and the self-learning system includes a neural network program.

71. The method of claim 66, wherein the adaptive system includes an adaptive control law.

72. The method of claim 66, wherein the adaptive system includes an artificial intelligence program.

73. The method of claim 66, wherein the adaptive system includes a fuzzy logic program.

74. The method of claim 66, wherein the parameters include control law parameters.

79. The method of claim 66, wherein the parameters include feedback sensor filter parameters.

80. The method of claim 66, wherein the adaptive system is a self-learning system and the self-learning system learns during a use phase.

81. The method of claim 66, wherein the adaptive system is a self-learning system and the self-learning system learns during a training phase.

82. The method of claim 66, wherein the adaptive system is a self-learning system and the self-learning system uses a training set of data to learn.

75-78. -78. (canceled)

83-97. -97. (canceled)