Phasor-Based Myoelectric Synergy Features: A Fast Hand-Crafted Feature Extraction Scheme for Boosting Performance in Gait Phase Recognition

Gait phase recognition systems based on surface electromyographic signals (EMGs) are crucial for developing advanced myoelectric control schemes that enhance the interaction between humans and lower limb assistive devices. However, machine learning models used in this context, such as Linear Discrim...

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מידע ביבליוגרפי

Principais autores:	Andrea Tigrini, Rami Mobarak, Alessandro Mengarelli, Rami N. Khushaba, Ali H. Al-Timemy, Federica Verdini, Ennio Gambi, Sandro Fioretti, Laura Burattini
פורמט:	Artigo
שפה:	Inglês
יצא לאור:	MDPI AG 2024-09-01
סדרה:	Sensors
נושאים:	gait EMG myoelectric control feature extraction deep learning lower limb
גישה מקוונת:	https://www.mdpi.com/1424-8220/24/17/5828
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