Continuous decoding of finger position from surface EMG signals for the control of powered prostheses
Smith, Ryan J.
Tenore, Francesco
Huberdeau, David
Etienne-Cummings, Ralph
Thakor, Nitish V.
Biomedical Engineering department at The Johns Hopkins University, Baltimore, MD, USA;
Abstract
As development toward multi-fingered dexterous prosthetic hands continues, there is a growing need for more flexible and intuitive control schemes. Through the use of generalized electrode placement and well-established methods of pattern recognition, we have developed a basis for asynchronous decoding of finger positions. With the present method, correlations as large as 0.91 and mean overall decoding errors of ∼11% have been achieved with average decoding errors of between decoded and actual conformation of the metacarpophalangeal joints of individual fingers. It is hoped that these results will serve as a foundation from which to encourage further investigation into more intuitive methods of myoelectric control of powered upper limb prostheses.
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