Classification of the mechanomyogram: its potential as a multifunction access pathway.
Although the mechanomyogram (MMG) has been demonstrated as a viable representation of muscle activity, its potential as a multifunction (>2) control signal has not yet been investigated. This study investigates the discriminability of multiple hand motions using multichannel forearm MMG. With nine able-bodied participants, MMG signals from six sites could be differentiated among eight classes of forearm muscle activity with a mean accuracy of 93+/-9% using 15 features selected by a genetic algorithm and classified by a linear discriminant analysis classifier. These results suggest that, with additional research, MMG may indeed become a usable control signal for multifunction access devices.
Alves
Natasha
N
Chau
Tom
T
D000328:Adult; D000465:Algorithms; D016477:Artifacts; D004576:Electromyography / Q000379:methods*; D004594:Electrophysiology / Q000379:methods; D005260:Female; D006801:Humans; D008297:Male; D008328:Man-Machine Systems; D009132:Muscles / Q000502:physiology*; D010363:Pattern Recognition, Automated; D015203:Reproducibility of Results; D012656:Self-Help Devices; D012815:Signal Processing, Computer-Assisted