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Myoelectric digit action decoding with multi-label, multi-class classification: an offline analysis
[article]
2020
biorxiv/medrxiv
pre-print
ABSTRACTThe ultimate goal of machine learning-based myoelectric control is simultaneous and independent control of multiple degrees of freedom (DOFs), including wrist and digit artificial joints. For prosthetic finger control, regression-based methods are typically used to reconstruct position/velocity trajectories from surface electromyogram (EMG) signals. Although such methods have produced highly-accurate results in offline analyses, their success in real-time prosthesis control settings has
doi:10.1101/2020.03.24.005710
fatcat:h36slwyqzjgynir2fnh4iyyq74