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Krishna V Shenoy

from Palo Alto, CA
Age ~55
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Also known as:
Krishna Vaughn Shenoy, Krishna Vaugh Shenoy, Krishna Te Shenoy, Krishwa Shewoy
Phone and address:
155 Heather Ln, Palo Alto, CA 94303
(650) 843-0551
Related to:
Raghuveer B Shenoy, 57Bach-Nga N Shenoy, 55Terri Nguyen, 53Dung H Nguyen, 49Hong Sy, 63Hong Nguyen, 38
Connected to:
Akshay Shenoy, 39Anil V Shenoy, 45Guruprasad P Shenoy, 42Laxmi L Shenoy, 54Nandita N Shenoy, 53Neha Shenoy, 38Rahul Shenoy, 49Shaista A Shenoy, 37Sonia F Shenoy, 41Sunita P Shenoy, 56

Krishna Shenoy Phones & Addresses

  • 155 Heather Ln, Palo Alto, CA 94303 (650) 843-0551
  • 912 Clark Way, Palo Alto, CA 94304
  • Stanford, CA
  • Los Angeles, CA
  • Glendale, CA
  • Boston, MA
  • Orange, CA
  • Santa Clara, CA
  • 155 Heather Ln, Palo Alto, CA 94303

Work

Company: Stanford university Aug 2001 Position: Professor, stanford university and investigator, howard hughes meducal institute

Education

Degree: Doctorates, Doctor of Philosophy Specialities: Philosophy

Industries

Higher Education

Resumes

Resumes

Krishna Shenoy Photo 1

Professor, Stanford University And Investigator, Howard Hughes Meducal Institute

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Location:
Stanford, CA
Industry:
Higher Education
Work:
Stanford University
Professor, Stanford University and Investigator, Howard Hughes Meducal Institute
Caltech Jul 1995 - Jul 2001
Postdoctoral Fellow

Publications

Us Patents

Processed Neural Signals And Methods For Generating And Using Them

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US Patent:
6731964, May 4, 2004
Filed:
Aug 9, 2002
Appl. No.:
10/216668
Inventors:
Krishna V. Shenoy - Los Angeles CA
Richard A. Andersen - La Canada CA
Sohaib A. Kureshi - Chapel Hill NC
Assignee:
California Institute of Technology - Pasadena CA
International Classification:
A61B 504
US Classification:
600372, 600378, 600544
Abstract:
The present invention provides a processed neural signal that encodes a reach plan, comprising the target location of the planned reach encoded relative to an eye-centered reference frame. The present invention also provides methods for generating and decoding the processed neural signal.

Cognitive State Machine For Prosthetic Systems

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US Patent:
6952687, Oct 4, 2005
Filed:
Jul 10, 2002
Appl. No.:
10/193649
Inventors:
Richard A. Andersen - La Canada CA, US
Bijan Pesaran - Los Angeles CA, US
Partha Mitra - Summit NJ, US
Daniella Meeker - Los Angeles CA, US
Krishna V. Shenoy - Palo Alto CA, US
Shiyan Cao - Pasadena CA, US
Joel W. Burdick - Pasadena CA, US
Assignee:
California Institute of Technology - Pasadena CA
International Classification:
G06F015/18
G06F017/00
US Classification:
706 12, 706 47, 623 24, 623 25
Abstract:
A prosthetic system may use a decoder to predict an intended action, such as a reach, from processed signals generated from measured neural activity. The decoder may included a cognitive state machine, which transitions between cognitive states based on transition rules.

Decoding Of Neural Signals For Movement Control

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US Patent:
7058445, Jun 6, 2006
Filed:
Oct 15, 2004
Appl. No.:
10/966355
Inventors:
Caleb T. Kemere - Menlo Park CA, US
Gopal Santhanam - Sunnyvale CA, US
Byron M. Yu - San Jose CA, US
Teresa H. Meng - Saratoga CA, US
Krishna V. Shenoy - Palo Alto CA, US
Assignee:
The Board of Trustees of the Leland Stanford Junior University - Stanford CA
International Classification:
A61B 5/04
US Classification:
600545, 600544, 623 25
Abstract:
A brain machine interface for decoding neural signals for control of a machine is provided. The brain machine interface estimates and then combines information from two classes of neural activity. A first estimator decodes movement plan information from neural signals representing plan activity. In one embodiment the first estimator includes an adaptive point-process filter or a maximum likelihood filter. A second estimator decodes peri-movement information from neural signals representing peri-movement activity. Each estimator is designed to estimate different aspects of movement such as movement goal variables or movement execution variables.

Implantable Sensing Arrangement And Approach

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US Patent:
8306607, Nov 6, 2012
Filed:
Nov 1, 2004
Appl. No.:
10/979091
Inventors:
Ofer Levi - Los Altos CA, US
Evan P. Thrush - San Francisco CA, US
James S. Harris - Stanford CA, US
Stepehn J. Smith - Los Altos CA, US
Krishna V. Shenoy - Palo Alto CA, US
Assignee:
The Board of Trustees of the Leland Stanford Junior University - Palo Alto CA
International Classification:
A61B 5/00
US Classification:
600473, 600476
Abstract:
Characteristics of biological substances, such as cerebral cortex matter, are sensed. According to an example embodiment, the present invention is directed to a negligibly-intrusive, multi-layer integrated circuit arrangement for monitoring activity of an area of a cerebral cortex that would normally be covered by an anatomical layer. The multi-layer integrated circuit arrangement includes an optics layer located outside the cerebral cortex area that includes an emitter and a detector. The optics layer is adapted for implantation in the anatomical layer and for sensing at least one brain-activity parameter. The multi-layered integrated circuit arrangement also includes a data-processing layer that includes a digital-processing circuit that is adapted for assimilating neural data in response to the optics layer sensing at least one brain-activity parameter.

Cognitive State Machine For Prosthetic Systems

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US Patent:
20050096521, May 5, 2005
Filed:
Nov 12, 2004
Appl. No.:
10/987810
Inventors:
Richard Andersen - La Canada CA, US
Bijan Pesaran - Los Angeles CA, US
Partha Mitra - Summit NJ, US
Daniella Meeker - Los Angeles CA, US
Krishna Shenoy - Palo Alto CA, US
Shiyan Cao - Pasadena CA, US
Joel Burdick - Pasadena CA, US
International Classification:
A61B005/04
US Classification:
600378000
Abstract:
A prosthetic system may use a decoder to predict an intended action, such as a reach, from processed signals generated from measured neural activity. The decoder may included a cognitive state machine, which transitions between cognitive states based on transition rules.

Brain Machine Interface

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US Patent:
20110224572, Sep 15, 2011
Filed:
Feb 17, 2011
Appl. No.:
12/932070
Inventors:
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
International Classification:
A61B 5/04
US Classification:
600545
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.

Brain Machine Interface Utilizing A Discrete Action State Decoder In Parallel With A Continuous Decoder For A Neural Prosthetic Device

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US Patent:
20140081454, Mar 20, 2014
Filed:
Sep 12, 2013
Appl. No.:
14/025100
Inventors:
Jonathan C. Kao - Stanford CA, US
Krishna V. Shenoy - Palo Alto CA, US
International Classification:
G06N 99/00
US Classification:
700246, 901 27, 901 3
Abstract:
A brain machine interface for control of prosthetic devices is provided. In its control, the interface utilizes parallel control of a continuous decoder and a discrete action state decoder. In the discrete decoding, we not only learn states affiliated with the task, but also states related to the velocity of the prosthetic device and the engagement of the user. Moreover, we not only learn the distributions of the neural signals in these states, but we also learn the interactions/transitions between the states, which is crucial to enabling a relatively higher level of performance of the prosthetic device. Embodiments according to this parallel control system enable us to reliably decode not just task-related states, but any “discrete action state,” in parallel with a neural prosthetic “continuous decoder,” to achieve new state-of-the-art levels of performance in brain-machine interfaces.

Processed Neural Signals And Methods For Generating And Using Them

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US Patent:
6609017, Aug 19, 2003
Filed:
Aug 6, 1999
Appl. No.:
09/369953
Inventors:
Krishna V. Shenoy - Los Angeles CA
Richard A. Andersen - La Canada CA
Sohaib A. Kureshi - Chapel Hill NC
Assignee:
California Institute of Technology - Pasadena CA
International Classification:
A61B 504
US Classification:
600372, 600378, 600544
Abstract:
The present invention provides a processed neural signal that encodes a reach plan, comprising the target location of the planned encoded relative to an eye-centered reference frame. The present invention also provides methods for generating and decoding the processed neural signal.
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Krishna V Shenoy from Palo Alto, CA, age ~55 Get Report