Cardinality as a highly descriptive feature in myoelectric pattern recognition for decoding motor volition
Abstract
Accurate descriptors of muscular activity play an important role in clinical practice and rehabilitation research. Such descriptors are features of myoelectric signals extracted from sliding time windows. A wide variety of myoelectric features have been used as inputs to pattern recognition algorithms that aim to decode motor volition. The output of these algorithms can then be used to control limb prostheses, exoskeletons, and rehabilitation...
Paper Details
Title
Cardinality as a highly descriptive feature in myoelectric pattern recognition for decoding motor volition
Published Date
Oct 29, 2015
Journal
Volume
9
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