Towards limb position invariant myoelectric pattern recognition using time-dependent spectral features
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- 作者：Rami N. Khushabaa ; Rami.Khushaba@uts.edu.au" class="auth_mail ; Maen Takrurib ; Maen.Takruri@aurak.edu.ae" class="auth_mail ; Jaime Valls Miroa ; Jaime.VallsMiro@uts.edu.au" class="auth_mail ; Sarath Kodagodaa ; Sarath.Kodagoda@uts.edu.au" class="auth_mail
- 关键词：Electromyogram (EMG) ; Spectral moments ; Signal processing
- 刊名：Neural Networks
- 出版年：July 2014
- 年：2014
- 卷：55
- 期：Complete
- 页码：42-58
- 全文大小：5256 K
文摘
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Human limb position has a substantial impact on the robustness of EMG pattern recognition.
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Invariant power spectral moments described as a solution.
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Real time classification experiments were carried out on 11 subjects.
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Limb position invariant myoelectric pattern recognition achieved.