Surface electromyography (SEMG) normalization method based on pre fatigue maximal voluntary contraction
Surface electromyography (sEMG) pattern recognition task requires high accuracy classification. However, current technology suffers from two main problems. The first problem is inconsistent pattern due to fatigue while the second is robustness of sEMG features due to low signal to noise ratio, SNR....
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| Format: | Thesis |
| Language: | English English |
| Published: |
2017
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| Online Access: | http://eprints.utem.edu.my/id/eprint/20616/1/Surface%20Electromyography%20%28SEMG%29%20Normalization%20Method%20Based%20On%20Pre%20Fatigue%20Maximal%20Voluntary%20Contraction.pdf http://eprints.utem.edu.my/id/eprint/20616/2/Surface%20electromyography%20%28SEMG%29%20normalization%20method%20based%20on%20pre%20fatigue%20maximal%20voluntary%20contraction.pdf http://eprints.utem.edu.my/id/eprint/20616/ https://plh.utem.edu.my/cgi-bin/koha/opac-detail.pl?biblionumber=106115&query_desc=kw%2Cwrdl%3A%20Surface%20electromyography |
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http://eprints.utem.edu.my/id/eprint/20616/1/Surface%20Electromyography%20%28SEMG%29%20Normalization%20Method%20Based%20On%20Pre%20Fatigue%20Maximal%20Voluntary%20Contraction.pdfhttp://eprints.utem.edu.my/id/eprint/20616/2/Surface%20electromyography%20%28SEMG%29%20normalization%20method%20based%20on%20pre%20fatigue%20maximal%20voluntary%20contraction.pdf
http://eprints.utem.edu.my/id/eprint/20616/
https://plh.utem.edu.my/cgi-bin/koha/opac-detail.pl?biblionumber=106115&query_desc=kw%2Cwrdl%3A%20Surface%20electromyography