Spatial Filtering for Robust Myoelectric Control
DC Field | Value | Language |
---|---|---|
dc.contributor.author | Hahne, Janne Mathias | - |
dc.contributor.author | Graimann, Bernhard | - |
dc.contributor.author | Mueller, Klaus-Robert | - |
dc.date.accessioned | 2021-09-06T20:24:25Z | - |
dc.date.available | 2021-09-06T20:24:25Z | - |
dc.date.created | 2021-06-18 | - |
dc.date.issued | 2012-05 | - |
dc.identifier.issn | 0018-9294 | - |
dc.identifier.uri | https://scholar.korea.ac.kr/handle/2021.sw.korea/108555 | - |
dc.description.abstract | Pattern recognition techniques have been applied to extract information from electromyographic (EMG) signals that can be used to control electrical powered hand prostheses. In this paper, optimized spatial filters that enhance separation properties of EMG signals are investigated. In particular, different multiclass extensions of the common spatial patterns algorithm are applied to high-density surface EMG signals acquired from the forearms of ten healthy subjects. Visualization of the obtained filter coefficients provides insight into the physiology of the muscles related to the performed contractions. The CSP methods are compared with a commonly used pattern recognition approach in a six-class classification task. Cross-validation results show a significant improvement in performance and a higher robustness against noise than commonly used pattern recognition methods. | - |
dc.language | English | - |
dc.language.iso | en | - |
dc.publisher | IEEE-INST ELECTRICAL ELECTRONICS ENGINEERS INC | - |
dc.subject | PATTERN-RECOGNITION | - |
dc.subject | CLASSIFICATION | - |
dc.title | Spatial Filtering for Robust Myoelectric Control | - |
dc.type | Article | - |
dc.contributor.affiliatedAuthor | Mueller, Klaus-Robert | - |
dc.identifier.doi | 10.1109/TBME.2012.2188799 | - |
dc.identifier.scopusid | 2-s2.0-84860356791 | - |
dc.identifier.wosid | 000303201000026 | - |
dc.identifier.bibliographicCitation | IEEE TRANSACTIONS ON BIOMEDICAL ENGINEERING, v.59, no.5, pp.1436 - 1443 | - |
dc.relation.isPartOf | IEEE TRANSACTIONS ON BIOMEDICAL ENGINEERING | - |
dc.citation.title | IEEE TRANSACTIONS ON BIOMEDICAL ENGINEERING | - |
dc.citation.volume | 59 | - |
dc.citation.number | 5 | - |
dc.citation.startPage | 1436 | - |
dc.citation.endPage | 1443 | - |
dc.type.rims | ART | - |
dc.type.docType | Article | - |
dc.description.journalClass | 1 | - |
dc.description.journalRegisteredClass | scie | - |
dc.description.journalRegisteredClass | scopus | - |
dc.relation.journalResearchArea | Engineering | - |
dc.relation.journalWebOfScienceCategory | Engineering, Biomedical | - |
dc.subject.keywordPlus | PATTERN-RECOGNITION | - |
dc.subject.keywordPlus | CLASSIFICATION | - |
dc.subject.keywordAuthor | Common spatial pattern (csp) | - |
dc.subject.keywordAuthor | hand prostheses | - |
dc.subject.keywordAuthor | myoelectric control | - |
dc.subject.keywordAuthor | prosthetic control | - |
dc.subject.keywordAuthor | prosthetics | - |
dc.subject.keywordAuthor | spatial filters | - |
Items in ScholarWorks are protected by copyright, with all rights reserved, unless otherwise indicated.
145 Anam-ro, Seongbuk-gu, Seoul, 02841, Korea+82-2-3290-2963
COPYRIGHT © 2021 Korea University. All Rights Reserved.
Certain data included herein are derived from the © Web of Science of Clarivate Analytics. All rights reserved.
You may not copy or re-distribute this material in whole or in part without the prior written consent of Clarivate Analytics.