| Improving Myoelectric Pattern Recognition Robustness to Electrode Shift by Changing Interelectrode Distance and Electrode Configuration. | |
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MedLine Citation:
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PMID: 22147289 Owner: NLM Status: Publisher |
Abstract/OtherAbstract:
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Pattern recognition of myoelectric signals for prosthesis control has been extensively studied in research settings and is close to clinical implementation. These systems are capable of intuitively controlling the next generation of dexterous prosthetic hands. However, pattern recognition systems perform poorly in the presence of electrode shift, defined as movement of surface electrodes with respect to the underlying muscles. This work focused on investigating the optimal interelectrode distance, channel configuration, and EMG feature sets for myoelectric pattern recognition in the presence of electrode shift. Increasing interelectrode distance from 2 cm to 4 cm improved pattern recognition system performance in terms of classification error and controllability (p<0.01). Additionally, for a constant number of channels, an electrode configuration that included electrodes oriented both longitudinally and perpendicularly with respect to muscle fibers improved robustness in the presence of electrode shift (p<0.05). We investigated the effect of the number of recording channels with and without electrode shift and found that four to six channels were sufficient for pattern recognition control. Finally, we investigated different feature sets for pattern recognition control using a LDA classifier and found that an autoregressive set significantly (p<0.01) reduced sensitivity to electrode shift compared to a traditional time-domain feature set. |
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Authors:
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A J Young; L J Hargrove; T A Kuiken |
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Publication Detail:
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Type: JOURNAL ARTICLE Date: 2011-11-29 |
Journal Detail:
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Title: IEEE transactions on bio-medical engineering Volume: - ISSN: 1558-2531 ISO Abbreviation: - Publication Date: 2011 Nov |
Date Detail:
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Created Date: 2011-12-7 Completed Date: - Revised Date: - |
Medline Journal Info:
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Nlm Unique ID: 0012737 Medline TA: IEEE Trans Biomed Eng Country: - |
Other Details:
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Languages: ENG Pagination: - Citation Subset: - |
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From MEDLINE®/PubMed®, a database of the U.S. National Library of Medicine
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