EEG-based user identification system using 1D-convolutional long short-term memory neural networks

作者：

Highlights：

• Achieve feature extraction from both spatial and temporal domains of EEG signals.

• The proposed network has accuracy up to 99.58% when using 16 EEG channels.

• Reduce number of channels of the EEG systems while maintaining high performance.

摘要

•Achieve feature extraction from both spatial and temporal domains of EEG signals.•The proposed network has accuracy up to 99.58% when using 16 EEG channels.•Reduce number of channels of the EEG systems while maintaining high performance.

论文关键词：User identification,Biometrics,1D-Convolutional LSTM,Electroencephalograms (EEG)

论文评审过程：Received 4 October 2018, Revised 29 January 2019, Accepted 31 January 2019, Available online 6 February 2019, Version of Record 11 February 2019.

论文官网地址：https://doi.org/10.1016/j.eswa.2019.01.080