Abstract:Mechanomyography (MMG) is a low-frequency signal emitted during muscle contraction; it can overcome the inherently unreliable defects of electromyography (EMG) and electroencephalography (EEG). For MMG-based movement pattern recognition, this paper proposes an innovative kernel extreme learning machine (KELM) based on the chaotic particle swarm optimization (CPSO), namely CPSO–KELM. By using CPSO–KELM in MMG-based movement pattern recognition, the classification accuracy of upper-limb movement has been improve… Show more
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