A novel STFT-ranking feature of multi-channel EMG for motion pattern recognition

作者：

Highlights：

• STFT-ranking feature is efficient for multi-channel EMG signal analysis.

• STFT-ranking feature can characterize relationships between multi-channel signals.

• Recognition accuracy over 90% was achieved applying the STFT-ranking feature.

• The performance of STFT-ranking feature is superior to conventional features.

• STFT-ranking feature can be applied to other multi-channel signals applications.

摘要

•STFT-ranking feature is efficient for multi-channel EMG signal analysis.•STFT-ranking feature can characterize relationships between multi-channel signals.•Recognition accuracy over 90% was achieved applying the STFT-ranking feature.•The performance of STFT-ranking feature is superior to conventional features.•STFT-ranking feature can be applied to other multi-channel signals applications.

论文关键词：Electromyography,Exoskeleton robot,Motion pattern recognition,Principal component analysis,Support vector machine

论文评审过程：Available online 9 December 2014.

论文官网地址：https://doi.org/10.1016/j.eswa.2014.11.044