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Due to the limited health resources, the traditional method of mental health diagnosis as one\u2010to\u2010one 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\u2010eight 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\u20109) and the seven\u2010item Generalized Anxiety Disorder Scale (GAD\u20107), to measure their depression and anxiety levels. Specifically, 18 key points of each individual's body trunk were captured from video, and both time\u2010domain features and frequency\u2010domain behavioral features were extracted for each key point. Lastly, machine\u2010learning 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\u20109) recognition above 0.5 and anxiety (measured by GAD\u20107) recognition above 0.4, achieving medium correlation. This new, low\u2010cost, and convenient mental health recognition pattern could be applied in daily monitoring of mental health and large\u2010scale preliminary screening of mental diseases.<\/jats:p>","DOI":"10.1002\/pchj.434","type":"journal-article","created":{"date-parts":[[2021,2,11]],"date-time":"2021-02-11T06:55:31Z","timestamp":1613026531000},"page":"453-464","update-policy":"https:\/\/doi.org\/10.1002\/crossmark_policy","source":"Crossref","is-referenced-by-count":21,"title":["Automatic mental health identification method based on natural gait pattern"],"prefix":"10.1002","volume":"10","author":[{"ORCID":"https:\/\/orcid.org\/0000-0002-1237-964X","authenticated-orcid":false,"given":"Beibei","family":"Miao","sequence":"first","affiliation":[{"name":"Institute of Psychology Chinese Academy of Sciences  Beijing China"},{"name":"Department of Psychology University of Chinese Academy of Sciences  Beijing China"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Xiaoqian","family":"Liu","sequence":"additional","affiliation":[{"name":"Institute of Psychology Chinese Academy of Sciences  Beijing China"},{"name":"Department of Psychology University of Chinese Academy of Sciences  Beijing China"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"ORCID":"https:\/\/orcid.org\/0000-0003-0020-3812","authenticated-orcid":false,"given":"Tingshao","family":"Zhu","sequence":"additional","affiliation":[{"name":"Institute of Psychology Chinese Academy of Sciences  Beijing China"},{"name":"Department of Psychology University of Chinese Academy of Sciences  Beijing China"}],"role":[{"role":"author","vocabulary":"crossref"}]}],"member":"311","published-online":{"date-parts":[[2021,2,10]]},"reference":[{"key":"e_1_2_7_2_1","doi-asserted-by":"publisher","DOI":"10.1177\/001872677602900801"},{"key":"e_1_2_7_3_1","doi-asserted-by":"crossref","unstructured":"American Psychiatric Association. 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