Interpersonal Relationship Analysis with Dyadic EEG Signals via Learning Spatial-Temporal Patterns
文献类型:期刊论文
作者 | Ji, Wenqi5; Liu, Fang4; Du, Xinxin5; Liu, Niqi5; Zhou, Chao3; Yu, Minjing2; Zhao, Guozhen1; Liu, Yong-Jin5 |
刊名 | arXiv |
出版日期 | 2024 |
通讯作者邮箱 | zhao, guozhen ; liu, yong-jin |
DOI | 10.48550/arXiv.2401.03250 |
英文摘要 | Interpersonal relationship quality is pivotal in social and occupational contexts. Existing analysis of interpersonal relationships mostly rely on subjective self-reports, whereas objective quantification remains challenging. In this paper, we propose a novel social relationship analysis framework using spatio-temporal patterns derived from dyadic EEG signals, which can be applied to quantitatively measure team cooperation in corporate team building, and evaluate interpersonal dynamics between therapists and patients in psychiatric therapy. First, we constructed a dyadic-EEG dataset from 72 pairs of participants with two relationships (stranger or friend) when watching emotional videos simultaneously. Then we proposed a deep neural network on dyadic-subject EEG signals, in which we combine the dynamic graph convolutional neural network for characterizing the interpersonal relationships among the EEG channels and 1-dimension convolution for extracting the information from the time sequence. To obtain the feature vectors from two EEG recordings that well represent the relationship of two subjects, we integrate deep canonical correlation analysis and triplet loss for training the network. Experimental results show that the social relationship type (stranger or friend) between two individuals can be effectively identified through their EEG data.
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收录类别 | EI |
语种 | 英语 |
源URL | [http://ir.psych.ac.cn/handle/311026/46775] |
专题 | 心理研究所_中国科学院行为科学重点实验室 |
作者单位 | 1.CAS, Key Laboratory of Behavioral Science, Institute of Psychology, China 2.College of Intelligence and Computing, Tianjin University, China 3.Institute of Software, Chinese Academy of Sciences, China 4.State Key Laboratory of Media Convergence and Communication, Communication University of China, China 5.BNRist, Department of Computer Science and Technology, MOE, Key Laboratory of Pervasive Computing, Tsinghua University, China |
推荐引用方式 GB/T 7714 | Ji, Wenqi,Liu, Fang,Du, Xinxin,et al. Interpersonal Relationship Analysis with Dyadic EEG Signals via Learning Spatial-Temporal Patterns[J]. arXiv,2024. |
APA | Ji, Wenqi.,Liu, Fang.,Du, Xinxin.,Liu, Niqi.,Zhou, Chao.,...&Liu, Yong-Jin.(2024).Interpersonal Relationship Analysis with Dyadic EEG Signals via Learning Spatial-Temporal Patterns.arXiv. |
MLA | Ji, Wenqi,et al."Interpersonal Relationship Analysis with Dyadic EEG Signals via Learning Spatial-Temporal Patterns".arXiv (2024). |
入库方式: OAI收割
来源:心理研究所
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