A LSTM based deep learning network for recognizing emotions using wireless brainwave driven system

作者：

Highlights：

• A novel LSTM based method is implemented for emotion recognition using EEG signals.

• Comparative Analysis of LSTM model.

• A new EEG signal dataset for stimuli is created using portable 4-channel MUSE2.

• A human behaviour analysis is performed for age and gender based responsiveness.

摘要

•A novel LSTM based method is implemented for emotion recognition using EEG signals.•Comparative Analysis of LSTM model.•A new EEG signal dataset for stimuli is created using portable 4-channel MUSE2.•A human behaviour analysis is performed for age and gender based responsiveness.

论文关键词：Emotion recognition,Deep learning,EEG,Empirical mode decomposition,LSTM

论文评审过程：Received 26 February 2020, Revised 20 November 2020, Accepted 14 December 2020, Available online 20 January 2021, Version of Record 2 March 2021.

论文官网地址：https://doi.org/10.1016/j.eswa.2020.114516