Improving Fast EMG Classification for Hand Gesture Recognition: A Comprehensive Analysis of Temporal, Spatial, and Algorithm Configurations for Healthy and Post-Stroke Subjects

Electromyography-based assistive and rehabilitation devices have shown potential for restoring mobility, especially for post-stroke patients. However, the variability of biological signals and the processing delays caused by signal acquisition and feature extraction influence myoelectric control sys...

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Vydáno v:	Sensors (Basel, Switzerland) Ročník 25; číslo 22; s. 6980
Hlavní autoři:	Montecinos, Camila, Espinoza, Jessica, Zamora Zapata, Mónica, Meruane, Viviana, Fernandez, Ruben
Médium:	Journal Article
Jazyk:	angličtina
Vydáno:	Switzerland MDPI AG 15.11.2025
Témata:	Accuracy Adult Aged Algorithms Analysis assistive technology Classification classification algorithms Data mining Datasets electromyography Electromyography - methods feature extraction Female Gestures Hand - physiology Hand - physiopathology Humans Machine Learning Male Middle Aged Muscle function myoelectric control Rehabilitation Signal processing Signal Processing, Computer-Assisted Stroke Stroke - physiopathology Stroke Rehabilitation Support vector machines Wavelet transforms classification algorithms dimensionality reduction feature extraction electromyography myoelectric control assistive technology machine learning stroke
ISSN:	1424-8220, 1424-8220
On-line přístup:	Získat plný text
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