A Novel Unsupervised Adaptive Learning Method for Long-Term Electromyography (EMG) Pattern Recognition

A Novel Unsupervised Adaptive Learning Method for Long-Term Electromyography (EMG) Pattern Recognition

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 pr...

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Bibliographic Details
Main Authors: Qi Huang, Dapeng Yang, Li Jiang, Huajie Zhang, Hong Liu, Kiyoshi Kotani
Format: Article
Language:English
Published: MDPI AG 2017-06-01
Series:Sensors
Subjects:
long-term EMG pattern recognition
adaptive learning
concept drift
particle adaption
support vector classifier
Online Access:http://www.mdpi.com/1424-8220/17/6/1370

Internet

http://www.mdpi.com/1424-8220/17/6/1370

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