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Identifying Psychological Symptoms Based on Facial Movements
Wang, Xiaoyang1,2; Wang, Yilin1,2; Zhou, Mingjie1,2; Li, Baobin2,3; Liu, Xiaoqian1,2; Zhu, Tingshao1,2
First AuthorWang, Xiaoyang
Correspondent Emailliuxiaoqian@psych.ac.cn (xiaoqian liu)
Contribution Rank1
Abstract

Background: Many methods have been proposed to automatically identify the presence of mental illness, but these have mostly focused on one specific mental illness. In some non-professional scenarios, it would be more helpful to understand an individual's mental health status from all perspectives. Methods: We recruited 100 participants. Their multi-dimensional psychological symptoms of mental health were evaluated using the Symptom Checklist 90 (SCL-90) and their facial movements under neutral stimulation were recorded using Microsoft Kinect. We extracted the time-series characteristics of the key points as the input, and the subscale scores of the SCL-90 as the output to build facial prediction models. Finally, the convergent validity, discriminant validity, criterion validity, and the split-half reliability were respectively assessed using a multitrait-multimethod matrix and correlation coefficients. Results: The correlation coefficients between the predicted values and actual scores were 0.26 and 0.42 (P < 0.01), which indicated good criterion validity. All models except depression had high convergent validity but low discriminant validity. Results also indicated good levels of split-half reliability for each model [from 0.516 (hostility) to 0.817 (interpersonal sensitivity)] (P < 0.001). Conclusion: The validity and reliability of facial prediction models were confirmed for the measurement of mental health based on the SCL-90. Our research demonstrated that fine-grained aspects of mental health can be identified from the face, and provided a feasible evaluation method for multi-dimensional prediction models.

Keywordmental health psychological symptoms SCL-90 facial movements machine learning multitrait-multimethod matrix
2020-12-15
Language英语
DOI10.3389/fpsyt.2020.607890
Source PublicationFRONTIERS IN PSYCHIATRY
ISSN1664-0640
Volume11Pages:11
Subtype实证研究
Indexed BySSCI
Funding ProjectKey Research Program of the Chinese Academy of Sciences[ZDRW-XH-2019-4]
PublisherFRONTIERS MEDIA SA
WOS KeywordMENTAL-HEALTH ; ANXIETY DISORDERS ; SOCIAL PHOBIA ; DEPRESSION ; EXPRESSION ; ASSOCIATION ; COMORBIDITY ; RELIABILITY ; CHILDREN ; SCL-90-R
WOS Research AreaPsychiatry
WOS SubjectPsychiatry
WOS IDWOS:000603022000001
WoS QuartileQ2
Citation statistics
Document Type期刊论文
Identifierhttp://ir.psych.ac.cn/handle/311026/38292
Collection社会与工程心理学研究室
Corresponding AuthorLiu, Xiaoqian
Affiliation1.Chinese Acad Sci, Inst Psychol, Beijing, Peoples R China
2.Univ Chinese Acad Sci, Dept Psychol, Beijing, Peoples R China
3.Univ Chinese Acad Sci, Sch Comp Sci & Technol, Beijing, Peoples R China
First Author AffilicationInstitute of Psychology, Chinese Academy of Sciences
Corresponding Author AffilicationInstitute of Psychology, Chinese Academy of Sciences
Recommended Citation
GB/T 7714
Wang, Xiaoyang,Wang, Yilin,Zhou, Mingjie,et al. Identifying Psychological Symptoms Based on Facial Movements[J]. FRONTIERS IN PSYCHIATRY,2020,11:11.
APA Wang, Xiaoyang,Wang, Yilin,Zhou, Mingjie,Li, Baobin,Liu, Xiaoqian,&Zhu, Tingshao.(2020).Identifying Psychological Symptoms Based on Facial Movements.FRONTIERS IN PSYCHIATRY,11,11.
MLA Wang, Xiaoyang,et al."Identifying Psychological Symptoms Based on Facial Movements".FRONTIERS IN PSYCHIATRY 11(2020):11.
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