Epilepsy seizure detection using complete ensemble empirical mode decomposition with adaptive noise

作者：

Highlights：

• An automated epileptic seizure detection algorithm for EEG signals is proposed.

• A novel signal processing technique, namely-CEEMDAN is employed.

• We introduce adaptive boosting for computerized seizure diagnosis.

• Efficacy of the method is confirmed by statistical and graphical analyses.

• The performance of the proposed scheme, compared to the existing ones is promising.

摘要

•An automated epileptic seizure detection algorithm for EEG signals is proposed.•A novel signal processing technique, namely-CEEMDAN is employed.•We introduce adaptive boosting for computerized seizure diagnosis.•Efficacy of the method is confirmed by statistical and graphical analyses.•The performance of the proposed scheme, compared to the existing ones is promising.

论文关键词：EEG,Epilepsy seizure,CEEMDAN,Normal inverse Gaussian pdf,AdaBoost

论文评审过程：Received 14 November 2018, Revised 30 November 2019, Accepted 30 November 2019, Available online 3 December 2019, Version of Record 8 February 2020.

论文官网地址：https://doi.org/10.1016/j.knosys.2019.105333