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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Auteurs principaux: | Zengyu Qing, Zongxing Lu, Yingjie Cai, Jing Wang |
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Format: | article |
Langue: | EN |
Publié: |
MDPI AG
2021
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Accès en ligne: | https://doaj.org/article/68f077a40fa6419187399e1cec853ad9 |
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