Document Detail


Real-time fusion of gaze and EMG for a reaching neuroprosthesis.
MedLine Citation:
PMID:  23365998     Owner:  NLM     Status:  In-Data-Review    
Abstract/OtherAbstract:
For rehabilitative devices to restore functional movement to paralyzed individuals, user intent must be determined from signals that remain under voluntary control. Tracking eye movements is a natural way to learn about an intended reach target and, when combined with just a small set of electromyograms (EMGs) in a probabilistic mixture model, can reliably generate accurate trajectories even when the target information is uncertain. To experimentally assess the effectiveness of our algorithm in closed-loop control, we developed a robotic system to simulate a reaching neuroprosthetic. Incorporating target information by tracking subjects' gaze greatly improved performance when the set of EMGs was most limited. In addition we found that online performance was better than predicted by the offline accuracy of the training data. By enhancing the trajectory model with target information the decoder relied less on neural control signals, reducing the burden on the user.
Authors:
Elaine A Corbett; Konrad P Kording; Eric J Perreault
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Publication Detail:
Type:  Journal Article    
Journal Detail:
Title:  Conference proceedings : ... Annual International Conference of the IEEE Engineering in Medicine and Biology Society. IEEE Engineering in Medicine and Biology Society. Conference     Volume:  2012     ISSN:  1557-170X     ISO Abbreviation:  Conf Proc IEEE Eng Med Biol Soc     Publication Date:  2012 Aug 
Date Detail:
Created Date:  2013-01-31     Completed Date:  -     Revised Date:  -    
Medline Journal Info:
Nlm Unique ID:  101243413     Medline TA:  Conf Proc IEEE Eng Med Biol Soc     Country:  United States    
Other Details:
Languages:  eng     Pagination:  739-42     Citation Subset:  IM    
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