A Novel Unsupervised Adaptive Learning Method for Long-Term Electromyography (EMG) Pattern Recognition
Abstract
Performance degradation will be caused by a variety of interfering factors for pattern recognition-based myoelectric control methods in the long term. This paper proposes an adaptive learning method with low computational cost to mitigate the effect in unsupervised adaptive learning scenarios. We presents a particle adaptive classifier (PAC), by constructing a particle adaptive learning strategy and universal incremental least square support...
Paper Details
Title
A Novel Unsupervised Adaptive Learning Method for Long-Term Electromyography (EMG) Pattern Recognition
Published Date
Jun 13, 2017
Journal
Volume
17
Issue
6
Pages
1370 - 1370
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