MEDIUM DENSITY DIGITAL ELECTROMYOGRAPHY SENSING SYSTEM
DOI :
https://doi.org/10.57922/mec.2513Résumé
Surface electromyographic (EMG) signals are widely used for diagnostic and control purposes. Traditional EMG recordings typically use sparse electrode setups, limiting their use in dynamic environments like prosthetics or virtual reality. We propose a medium-density EMG armband design that leverages digital technology to capture EMG data from 21 channels. This system, designed to be more practical for everyday use and research, was tested against traditional single-channel methods for classifying six hand gestures using machine learning. Our results indicate the medium-density EMG system offers superior gesture classification accuracy, making it a valuable tool for real-world applications. We aim to further enhance this EMG recording setup and introduce it an open-source platform to the MEC community at the conference.
Téléchargements
Publié-e
2024-08-15
Comment citer
[1]
E. Aghchehli, C. Ma, M. Dyson, et K. Nazarpour, « MEDIUM DENSITY DIGITAL ELECTROMYOGRAPHY SENSING SYSTEM », MEC Symposium, août 2024.
Numéro
Rubrique
Myo Control and Sensory Feedback Implementations
