Automated EEG signal classification using chaotic local binary pattern

作者：

Highlights：

• We presented a new chaotic local binary pattern.

• Automated abnormal EEG detection model is presented using chaotic local binary pattern.

• TUH dataset is utilized to test the presented model.

• Presented model reached 98.19% accuracy for PZ channel.

摘要

•We presented a new chaotic local binary pattern.•Automated abnormal EEG detection model is presented using chaotic local binary pattern.•TUH dataset is utilized to test the presented model.•Presented model reached 98.19% accuracy for PZ channel.

论文关键词：Fractal hypercube graph pattern,Inception average pooling,Iterative neighborhood component analysis,EEG classification,Epilepsy seizure detection

论文评审过程：Received 12 February 2021, Revised 26 April 2021, Accepted 6 May 2021, Available online 12 May 2021, Version of Record 25 May 2021.

论文官网地址：https://doi.org/10.1016/j.eswa.2021.115175