EEG-FRM: a neural network based familiar and unfamiliar face EEG recognition method

doi:10.1007/s11571-024-10073-5

CASIA OpenIR > 脑图谱与类脑智能实验室

	EEG-FRM: a neural network based familiar and unfamiliar face EEG recognition method
	Chen, Chao 1,2; Fan, Lingfeng 1; Gao, Ying 3; Qiu, Shuang3,4 ; Wei, Wei3 ; He, Huiguang3,4
发表期刊	COGNITIVE NEURODYNAMICS
ISSN	1871-4080
	2024-02-19
页码	14
通讯作者	Wei, Wei(weiwei2018@ia.ac.cn) ; He, Huiguang(huiguang.he@ia.ac.cn)
摘要	Recognizing familiar faces holds great value in various fields such as medicine, criminal investigation, and lie detection. In this paper, we designed a Complex Trial Protocol-based familiar and unfamiliar face recognition experiment that using self-face information, and collected EEG data from 147 subjects. A novel neural network-based method, the EEG-based Face Recognition Model (EEG-FRM), is proposed in this paper for cross-subject familiar/unfamiliar face recognition, which combines a multi-scale convolutional classification network with the maximum probability mechanism to realize individual face recognition. The multi-scale convolutional neural network extracts temporal information and spatial features from the EEG data, the attention module and supervised contrastive learning module are employed to promote the classification performance. Experimental results on the dataset reveal that familiar face stimuli could evoke significant P300 responses, mainly concentrated in the parietal lobe and nearby regions. Our proposed model achieved impressive results, with a balanced accuracy of 85.64%, a true positive rate of 73.23%, and a false positive rate of 1.96% on the collected dataset, outperforming other compared methods. The experimental results demonstrate the effectiveness and superiority of our proposed model.
关键词	Familiar/unfamiliar face recognition Electroencephalogram (EEG) Convolutional neural network Attention module Supervised contrastive learning
DOI	10.1007/s11571-024-10073-5
关键词[WOS]	CLASSIFICATION ; POTENTIALS
收录类别	SCI
语种	英语
资助项目	National Natural Science Foundation of China[62206285] ; General program of China Postdoctoral science foundation[2021M703490]
项目资助者	National Natural Science Foundation of China ; General program of China Postdoctoral science foundation
WOS研究方向	Neurosciences & Neurology
WOS类目	Neurosciences
WOS记录号	WOS:001164249400001
出版者	SPRINGER
引用统计
文献类型	期刊论文
条目标识符	http://ir.ia.ac.cn/handle/173211/55613
专题	脑图谱与类脑智能实验室
通讯作者	Wei, Wei; He, Huiguang
作者单位	1.Tianjin Univ Technol, Key Lab Complex Syst Control Theory & Applicat, Tianjin, Peoples R China 2.Tianjin Univ, Acad Med Engn & Translat Med, Tianjin, Peoples R China 3.Chinese Acad Sci, Inst Automat, Key Lab Brain Cognit & Brain inspired Intelligence, State Key Lab Multimodal Artificial Intelligence S, Beijing 100190, Peoples R China 4.Univ Chinese Acad Sci, Beijing, Peoples R China
通讯作者单位	中国科学院自动化研究所
推荐引用方式 GB/T 7714	Chen, Chao,Fan, Lingfeng,Gao, Ying,et al. EEG-FRM: a neural network based familiar and unfamiliar face EEG recognition method[J]. COGNITIVE NEURODYNAMICS,2024:14.
APA	Chen, Chao,Fan, Lingfeng,Gao, Ying,Qiu, Shuang,Wei, Wei,&He, Huiguang.(2024).EEG-FRM: a neural network based familiar and unfamiliar face EEG recognition method.COGNITIVE NEURODYNAMICS,14.
MLA	Chen, Chao,et al."EEG-FRM: a neural network based familiar and unfamiliar face EEG recognition method".COGNITIVE NEURODYNAMICS (2024):14.