Robust detection of epileptic seizures based on L1-penalized robust regression of EEG signals

作者：

Highlights：

• This study introduces a robust detection method of epileptic seizures.

• The performance of the proposed method is examined under ideal and real-life conditions.

• The proposed method achieves 100% classification accuracy under the ideal conditions.

• The proposed method is also proven to be robust in real-life situations.

摘要

•This study introduces a robust detection method of epileptic seizures.•The performance of the proposed method is examined under ideal and real-life conditions.•The proposed method achieves 100% classification accuracy under the ideal conditions.•The proposed method is also proven to be robust in real-life situations.

论文关键词：EEG signals,Epileptic seizures,Robust detection,Feature learning,Random forest

论文评审过程：Received 27 December 2017, Revised 12 March 2018, Accepted 13 March 2018, Available online 16 March 2018, Version of Record 27 March 2018.

论文官网地址：https://doi.org/10.1016/j.eswa.2018.03.022