Journal
JOURNAL OF NEURAL ENGINEERING
Volume 5, Issue 4, Pages 455-476Publisher
IOP PUBLISHING LTD
DOI: 10.1088/1741-2560/5/4/010
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Funding
- NIH-NINDS [R01 NS 50867-01, NS25074]
- Katie Sarnson Foundation
- Office of Naval Research [N0014-04-1-082, N0014-07-1-0803]
- European Neurobotics Program [FP6-IST-001917]
- Rehabilitation Research and Development Service, Department of Veterans Affairs
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Computer-mediated connections between human motor cortical neurons and assistive devices promise to improve or restore lost function in people with paralysis. Recently, a pilot clinical study of an intracortical neural interface system demonstrated that a tetraplegic human was able to obtain continuous two-dimensional control of a computer cursor using neural activity recorded from his motor cortex. This control, however, was not sufficiently accurate for reliable use in many common computer control tasks. Here, we studied several central design choices for such a system including the kinematic representation for cursor movement, the decoding method that translates neuronal ensemble spiking activity into a control signal and the cursor control task used during training for optimizing the parameters of the decoding method. In two tetraplegic participants, we found that controlling a cursor's velocity resulted in more accurate closed-loop control than controlling its position directly and that Cursor velocity control was achieved more rapidly than position control. Control quality was further improved over conventional linear filters by using a probabilistic method, the Kalman filter, to decode human motor cortical activity. Performance assessment based on standard metrics used for the evaluation of a wide range of pointing devices demonstrated significantly improved cursor control with velocity rather than position decoding.
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