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

文献类型：期刊论文

作者Chen, Chao3,4; Fan, Lingfeng4; Gao, Ying2; Qiu, Shuang1,2; Wei, Wei2; He, Huiguang1,2
刊名COGNITIVE NEURODYNAMICS
出版日期2024-02-19
页码14
ISSN号1871-4080
关键词Familiar/unfamiliar face recognition Electroencephalogram (EEG) Convolutional neural network Attention module Supervised contrastive learning
DOI10.1007/s11571-024-10073-5
通讯作者Wei, Wei(weiwei2018@ia.ac.cn) ; He, Huiguang(huiguang.he@ia.ac.cn)
英文摘要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.
WOS关键词CLASSIFICATION ; POTENTIALS
资助项目National Natural Science Foundation of China[62206285] ; General program of China Postdoctoral science foundation[2021M703490]
WOS研究方向Neurosciences & Neurology
语种英语
出版者SPRINGER
WOS记录号WOS:001164249400001
资助机构National Natural Science Foundation of China ; General program of China Postdoctoral science foundation
源URL[http://ir.ia.ac.cn/handle/173211/55612]  
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.Univ Chinese Acad Sci, Beijing, Peoples R China
2.Chinese Acad Sci, Inst Automat, Key Lab Brain Cognit & Brain inspired Intelligence, State Key Lab Multimodal Artificial Intelligence S, Beijing 100190, Peoples R China
3.Tianjin Univ, Acad Med Engn & Translat Med, Tianjin, Peoples R China
4.Tianjin Univ Technol, Key Lab Complex Syst Control Theory & Applicat, Tianjin, Peoples R China
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.

入库方式： OAI收割

来源：自动化研究所

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