Personal identification based on brain networks of EEG signals - Kong, Wanzeng; Jiang, Bei; Fan, Qiaonan; Zhu, Li; Wei, Xuehui (Zielona Góra: Uniwersytet Zielonogórski)
Personal identification is particularly important in information security. There are numerous advantages of using electroencephalogram (EEG) signals for personal identification, such as uniqueness and anti-deceptiveness. Currently, many researchers focus on single-dataset personal identification, instead of the cross-dataset. In this paper, we propose a method for cross-dataset personal identification based on a brain network of EEG signals.
Keywords: EEG; personal identification; brain network; phase synchronization