Effect of window size and contraction types on the stationarity of Biceps Brachii muscle EMG signals

Autor: Thongpanja, S., Phinyomark, A., Quaine, F., Laurillau, Y., Wongkittisuksa, B., Limsakul, C., Pornchai Phukpattaranont

Publikováno v: i-CREATe 2013-IEEE 7th International convention on rehabilitation Engineering and Assistive technology
i-CREATe 2013-IEEE 7th International convention on rehabilitation Engineering and Assistive technology, Aug 2013, Séoul, South Korea
HAL
i-CREATe 2013-IEEE 7th International convention on rehabilitation Engineering and Assistive technology, Aug 2013, Séoul, South Korea. pp.44:1--44:4
Scopus-Elsevier

International audience; In order to analyze surface electromyography (EMG) signals, it is necessary to use techniques based on time (temporal) domain or frequency (spectral) domain. However, these techniques are based on the mathematical assumption o

Externí odkaz: https://explore.openaire.eu/search/publication?articleId=dedup_wf_001::22350708fcac7ea0784e9251c174cdb4
https://hal.archives-ouvertes.fr/hal-00870923

Improving the accuracy of a fall detection algorithm using free fall characteristics.

Autor: Jantaraprim, P., Phukpattaranont, P., Limsakul, C., Wongkittisuksa, B.

Publikováno v: 2010 International Conference on Electrical Engineering/Electronics Computer Telecommunications & Information Technology (ECTI-CON); 2010, p501-504, 4p

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A system for improving fall detection performance using critical phase fall signal and a neural network

Autor: Jantaraprim, P., Pornchai Phukpattaranont, Limsakul, C., Wongkittisuksa, B.

Publikováno v: Scopus-Elsevier
Songklanakarin Journal of Science and Technology (SJST), Vol 34, Iss 6, Pp 637-644 (2012)

We present a system for improving fall detection performance using a short time min-max feature based on the specificsignatures of critical phase fall signal and a neural network as a classifier. Two subject groups were tested: Group A involvingfalls

Externí odkaz: https://explore.openaire.eu/search/publication?articleId=dedup_wf_001::6c47742f229937abe8b71ccd85ef2b7f
http://www.scopus.com/inward/record.url?eid=2-s2.0-84870956580&partnerID=MN8TOARS

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