An EEG based familiar and unfamiliar person identification and classification system using feature extraction and directed functional brain network

作者:

Highlights:

• Proposes an multi-channel EEG based approach for person recognition.

• Directed functional network is analyzed to identify familiar from unfamiliar person.

• Several EEG signal complexities are analyzed in person recognition.

• Network parameters combined with complexities form the feature set for classification.

• Delta wave is the best frequency band for person recognition.

摘要

•Proposes an multi-channel EEG based approach for person recognition.•Directed functional network is analyzed to identify familiar from unfamiliar person.•Several EEG signal complexities are analyzed in person recognition.•Network parameters combined with complexities form the feature set for classification.•Delta wave is the best frequency band for person recognition.

论文关键词:Familiar/unfamiliar person recognition,Electroencephalogram (EEG),Feature extraction,Directed functional connectivity,Brain signal complexity,Classification

论文评审过程:Received 1 August 2019, Revised 8 January 2020, Accepted 10 April 2020, Available online 11 May 2020, Version of Record 20 May 2020.

论文官网地址:https://doi.org/10.1016/j.eswa.2020.113448

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