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dc.contributor.author Zhou, Ping
dc.contributor.author Lowery, Madeleine M.
dc.contributor.author Weir, Richard F.
dc.contributor.author Kuiken, Todd A.
dc.date.accessioned 2010-07-22T19:39:37Z
dc.date.available 2010-07-22T19:39:37Z
dc.date.issued 2005
dc.identifier.citation Proceedings of the MEC’05 conference, UNB; 2005. en_US
dc.identifier.uri http://hdl.handle.net/10161/2759
dc.description.abstract We investigated removal of electrocardiogram (ECG) artifacts from the myoelectric prosthesis control signals, taken from the reinnervated pectoralis muscles of a patient with bilateral amputations at shoulder disarticulation level. The performance of various ECG artifact removal methods including high pass filtering, spike clipping, template subtracting, wavelet thresholding and adaptive filtering was presented. In particular, considering the clinical requirements and memory limitation of commercial prosthesis controllers, we further explored suitable means of ECG artifact removal for clinical application. en_US
dc.format.extent 115310 bytes
dc.format.mimetype application/pdf
dc.language.iso en_US en_US
dc.publisher Myoelectric Symposium en_US
dc.subject myoelectric signals en_US
dc.subject myoelectric prosthesis en_US
dc.title Removal of ECG Artifacts from Myoelectric Prosthesis Control Signals en_US
dc.type Article en_US

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