Parameter estimation for maximizing controllability of linear brain-machine interfaces

Brain-machine interfaces (BMIs) must be carefully designed for closed-loop control to ensure the best possible performance. The Kalman filter (KF) is a recursive linear BMI algorithm which has been shown to smooth cursor kinematics and improve control over non-recursive linear methods. However, recu...

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Bibliographic Details
Published in:	2012 Annual International Conference of the IEEE Engineering in Medicine and Biology Society Vol. 2012; pp. 1314 - 1317
Main Authors:	Gowda, S., Orsborn, A. L., Carmena, J. M.
Format:	Conference Proceeding Journal Article
Language:	English
Published:	United States IEEE 01.01.2012
Subjects:	Algorithms Animals Biomechanical Phenomena - physiology Brain-Computer Interfaces Computer Simulation Controllability Correlation Decoding Electrodes, Implanted Error analysis Feedback control Kinematics Linear Models Macaca mulatta Male Motor Cortex - physiology Neurons - physiology Signal Processing, Computer-Assisted Task Performance and Analysis Trajectory
ISBN:	1424441196, 9781424441198
ISSN:	1094-687X, 1557-170X, 2694-0604, 2694-0604
Online Access:	Get full text
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