Rejecting Unknown Gestures Based on Surface-Electromyography Using Variational Autoencoder

The conventional surface electromyography (sEMG)-based gesture recognition systems exhibit impressive performance in controlled laboratory settings. As most systems are trained in a closed-set setting, the systems's performance may see significant deterioration when novel gestures are presented...

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Veröffentlicht in:	IEEE transactions on neural systems and rehabilitation engineering Jg. 32; S. 750 - 758
Hauptverfasser:	Dai, Qingfeng, Wong, Yongkang, Kankanhalli, Mohan, Li, Xiangdong, Geng, Weidong
Format:	Journal Article
Sprache:	Englisch
Veröffentlicht:	United States IEEE 2024 The Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Schlagworte:	Algorithms Decoding Density Electromyography Electromyography - methods Feature extraction Gaussian distribution Gesture recognition Gestures Hand - physiology Humans Normal distribution Open-set recognition Prototypes Recognition, Psychology Statistical analysis surface electromyography Training variational autoencoder
ISSN:	1534-4320, 1558-0210, 1558-0210
Online-Zugang:	Volltext
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