Automatic detection of epileptic seizure based on approximate entropy, recurrence quantiﬁcation analysis and convolutional neural networks

作者：

Highlights：

• ApEn is used to quantify the complexity of the epileptic seizure.

• RQA estimates the recurrence behaviors of the epileptic seizure.

• A new method for automatic epileptic EEG recordings based on the ApEn and RQA combined with CNN is proposed.

• The classification accuracy using the proposed method can reach to 99.26%.

摘要

•ApEn is used to quantify the complexity of the epileptic seizure.•RQA estimates the recurrence behaviors of the epileptic seizure.•A new method for automatic epileptic EEG recordings based on the ApEn and RQA combined with CNN is proposed.•The classification accuracy using the proposed method can reach to 99.26%.

论文关键词：EEG,Approximate entropy,Recurrence quantification analysis,Convolutional neural network

论文评审过程：Received 5 June 2019, Revised 9 August 2019, Accepted 30 August 2019, Available online 7 September 2019, Version of Record 20 December 2019.

论文官网地址：https://doi.org/10.1016/j.artmed.2019.101711