Feature optimization based on improved novel global harmony search algorithm for motor imagery electroencephalogram classification.

Bin Shi,Xiaokai Chen,Zan Yue,Feixiang Zeng,Shuai Yin,Benguo Wang,Jing Wang

Frontiers in computational neuroscience（2022）

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摘要

These superior experimental results demonstrate that the optimal frequency band and time interval selected by the INGHS algorithm could significantly improve the decoding accuracy compared with the traditional CSP method. This method has a potential to improve the performance of MI-based BCI systems.

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关键词

brain-computer interface (BCI),common spatial pattern (CSP),electroencephalogram (EEG),frequency band,improved novel global harmony search (INGHS),time interval

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