PSYCH OpenIR  > 社会与工程心理学研究室
Automatic mental health identification method based on natural gait pattern
Miao, Beibei1,2; Liu, Xiaoqian1,2; Zhu, Tingshao1,2
First AuthorMiao, Beibei
Correspondent Emailliuxiaoqian@psych.ac.cn (xiaoqian liu)
Contribution Rank1
Abstract

Mental health has become a global problem, as over 300 million people worldwide suffer from depression and 200 million from anxiety disorders, which are ranked by the World Health Organization (WHO) as the first and sixth leading causes of disability, respectively. Due to the limited health resources, the traditional method of mental health diagnosis as one-to-one consultation is difficult to meet the needs of the large number of mental subhealth population. In this article, we propose a new method for mental health recognition that could identify potentially clinically significant symptoms of depression and anxiety based on daily gait. Eighty-eight participants were recruited, and their gaits were recorded by a digital camera. Then they were required to complete two rating scales, the Patient Health Questionnaire (PHQ-9) and the seven-item Generalized Anxiety Disorder Scale (GAD-7), to measure their depression and anxiety levels. Specifically, 18 key points of each individual's body trunk were captured from video, and both time-domain features and frequency-domain behavioral features were extracted for each key point. Lastly, machine-learning algorithms were utilized to build the mental health recognition models. Results showed that the proposed method is feasible and effective, with a correlation coefficient of depression (measured by PHQ-9) recognition above 0.5 and anxiety (measured by GAD-7) recognition above 0.4, achieving medium correlation. This new, low-cost, and convenient mental health recognition pattern could be applied in daily monitoring of mental health and large-scale preliminary screening of mental diseases.

Keywordanxiety depression gait analysis mental health automatic recognition
2021-02-10
Language英语
DOI10.1002/pchj.434
Source PublicationPSYCH JOURNAL
ISSN2046-0252
Pages12
Subtype实证研究
Indexed BySCI
PublisherWILEY
WOS Research AreaPsychology
WOS SubjectPsychology, Multidisciplinary
WOS IDWOS:000616729700001
Citation statistics
Document Type期刊论文
Identifierhttp://ir.psych.ac.cn/handle/311026/38540
Collection社会与工程心理学研究室
Corresponding AuthorLiu, Xiaoqian
Affiliation1.Chinese Acad Sci, Inst Psychol, 16 Lincui Rd, Beijing 100101, Peoples R China
2.Univ Chinese Acad Sci, Dept Psychol, 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
Miao, Beibei,Liu, Xiaoqian,Zhu, Tingshao. Automatic mental health identification method based on natural gait pattern[J]. PSYCH JOURNAL,2021:12.
APA Miao, Beibei,Liu, Xiaoqian,&Zhu, Tingshao.(2021).Automatic mental health identification method based on natural gait pattern.PSYCH JOURNAL,12.
MLA Miao, Beibei,et al."Automatic mental health identification method based on natural gait pattern".PSYCH JOURNAL (2021):12.
Files in This Item:
File Name/Size DocType Version Access License
Automatic mental hea(1430KB)期刊论文出版稿限制开放CC BY-NC-SAApplication Full Text
Related Services
Recommend this item
Bookmark
Usage statistics
Export to Endnote
Google Scholar
Similar articles in Google Scholar
[Miao, Beibei]'s Articles
[Liu, Xiaoqian]'s Articles
[Zhu, Tingshao]'s Articles
Baidu academic
Similar articles in Baidu academic
[Miao, Beibei]'s Articles
[Liu, Xiaoqian]'s Articles
[Zhu, Tingshao]'s Articles
Bing Scholar
Similar articles in Bing Scholar
[Miao, Beibei]'s Articles
[Liu, Xiaoqian]'s Articles
[Zhu, Tingshao]'s Articles
Terms of Use
No data!
Social Bookmark/Share
All comments (0)
No comment.
 

Items in the repository are protected by copyright, with all rights reserved, unless otherwise indicated.