Multi-finger movement decoding using EMG
DC Field | Value | Language |
---|---|---|
dc.contributor.author | You, K.-J. | - |
dc.contributor.author | Shin, H.-C. | - |
dc.date.available | 2019-04-10T11:01:12Z | - |
dc.date.created | 2018-04-17 | - |
dc.date.issued | 2010 | - |
dc.identifier.isbn | 9780889868694 | - |
dc.identifier.uri | http://scholarworks.bwise.kr/ssu/handle/2018.sw.ssu/33374 | - |
dc.description.abstract | We provide a novel method to infer finger flexing motions using a four-channel surface electromyogram (EMG). Surface EMG signals can be recorded from the human body non-invasively and easily. Surface EMG signals in this study were obtained from four channel electrodes placed around the forearm. The motions consist of the flexion of five single fingers (thumb, index finger, middle finger, ring finger, and little finger) and three multi-finger motions. The maximum likelihood estimation was used to infer the finger motions. Experimental results have shown that this method can successfully infer the finger flexing motions. The average accuracy was as high as 97:75%. | - |
dc.relation.isPartOf | Proceedings of the 5th IASTED International Conference on Human-Computer Interaction, HCI 2010 | - |
dc.title | Multi-finger movement decoding using EMG | - |
dc.type | Conference | - |
dc.type.rims | CONF | - |
dc.identifier.bibliographicCitation | 5th IASTED International Conference on Human-Computer Interaction, HCI 2010, pp.236 - 239 | - |
dc.description.journalClass | 2 | - |
dc.identifier.scopusid | 2-s2.0-84862090035 | - |
dc.citation.conferenceDate | 2010-08-23 | - |
dc.citation.conferencePlace | Maui, HI | - |
dc.citation.endPage | 239 | - |
dc.citation.startPage | 236 | - |
dc.citation.title | 5th IASTED International Conference on Human-Computer Interaction, HCI 2010 | - |
dc.contributor.affiliatedAuthor | Shin, H.-C. | - |
dc.type.docType | Conference Paper | - |
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