Elements Influencing sEMG-Based Gesture Decoding: Muscle Fatigue, Forearm Angle and Acquisition Time

The surface Electromyography (sEMG) signal contains information about movement intention generated by the human brain, and it is the most intuitive and common solution to control robots, orthotics, prosthetics and rehabilitation equipment. In recent years, gesture decoding based on sEMG signals has...

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Detalles Bibliográficos
Autores principales: Qing, Zengyu, Lu, Zongxing, Cai, Yingjie, Wang, Jing
Formato: Online Artículo Texto
Lenguaje:English
Publicado: MDPI 2021
Materias:
Article
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8623265/
https://www.ncbi.nlm.nih.gov/pubmed/34833784
http://dx.doi.org/10.3390/s21227713

Internet

https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8623265/
https://www.ncbi.nlm.nih.gov/pubmed/34833784
http://dx.doi.org/10.3390/s21227713

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