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dc.contributor.author Garcia, Gonzalo A.
dc.contributor.author Keller, Thierry
dc.date.accessioned 2010-07-28T18:26:58Z
dc.date.available 2010-07-28T18:26:58Z
dc.date.issued 2008
dc.identifier.citation Proceedings of the MEC’08 conference, UNB; 2008. en_US
dc.identifier.uri http://hdl.handle.net/10161/2777
dc.description.abstract In spite of the great advances in the mechanical and electronic components of prosthetic hands, they still lack the high number of degrees of freedom present in the real human hand. That is due, not to technical deficiencies, but to the much reduced amount of independent control signals available when using surface electromyography (s-EMG) from the forearm stump or other artificial sensors. Cross-talk between adjacent muscles produces interferences that bury the s-EMG of the target muscle and reduce selectivity. In a single case study, surface-EMG signals from an able-bodied subject’s forearm were recorded with a surface, 5x13-electrode array while the subject performed eleven different isometric contractions. In order to reduce the cross-talk between s-EMG signals from different muscles, we applied a blind source separation (BSS) technique called JADE. Although the results are not fully conclusive, they indicate that BSS techniques could provide an important reduction in s-EMG cross-talk and hence BSS is able to increase the selectivity of recordings for myoelectric control. en_US
dc.language.iso en_US en_US
dc.publisher Myoelectric Symposium en_US
dc.subject Signal Processing en_US
dc.subject forearm en_US
dc.title ADVANCED SIGNAL PROCESSING TECHNIQUES APPLIED TO CROSS-TALK REDUCTION IN FOREARM S-EMG en_US
dc.type Article en_US

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