The patent badge is an abbreviated version of the USPTO patent document. The patent badge does contain a link to the full patent document.
The patent badge is an abbreviated version of the USPTO patent document. The patent badge covers the following: Patent number, Date patent was issued, Date patent was filed, Title of the patent, Applicant, Inventor, Assignee, Attorney firm, Primary examiner, Assistant examiner, CPCs, and Abstract. The patent badge does contain a link to the full patent document (in Adobe Acrobat format, aka pdf). To download or print any patent click here.
Patent No.:
Date of Patent:
Jul. 29, 2014
Filed:
Feb. 17, 2011
Vikash Gilja, San Francisco, CA (US);
Paul Nuyujukian, Stanford, CA (US);
Cynthia a Chestek, Menlo Park, CA (US);
John P Cunningham, Saratoga, CA (US);
Byron M. Yu, San Jose, CA (US);
Stephen I Ryu, Menlo Park, CA (US);
Krishna V. Shenoy, Palo Alto, CA (US);
Vikash Gilja, San Francisco, CA (US);
Paul Nuyujukian, Stanford, CA (US);
Cynthia A Chestek, Menlo Park, CA (US);
John P Cunningham, Saratoga, CA (US);
Byron M. Yu, San Jose, CA (US);
Stephen I Ryu, Menlo Park, CA (US);
Krishna V. Shenoy, Palo Alto, CA (US);
The Board of Trustees of the Leland Stanford Junior University, Palo Alto, CA (US);
Abstract
Artificial control of a prosthetic device is provided. A brain machine interface contains a mapping of neural signals and corresponding intention estimating kinematics (e.g. positions and velocities) of a limb trajectory. The prosthetic device is controlled by the brain machine interface. During the control of the prosthetic device, a modified brain machine interface is developed by modifying the vectors of the velocities defined in the brain machine interface. The modified brain machine interface includes a new mapping of the neural signals and the intention estimating kinematics that can now be used to control the prosthetic device using recorded neural brain signals from a user of the prosthetic device. In one example, the intention estimating kinematics of the original and modified brain machine interface includes a Kalman filter modeling velocities as intentions and positions as feedback.