CASIA OpenIR
A survey on big data-driven digital phenotyping of mental health
Liang, Yunji1,2; Zheng, Xiaolong2,4; Zeng, Daniel D.2,3
Source PublicationINFORMATION FUSION
ISSN1566-2535
2019-12-01
Volume52Pages:290-307
Corresponding AuthorZheng, Xiaolong(xiaolong.zheng@ia.ac.cn)
AbstractThe landscape of mental health has undergone tremendous changes within the last two decades, but the research on mental health is still at the initial stage with substantial knowledge gaps and the lack of precise diagnosis. Nowadays, big data and artificial intelligence offer new opportunities for the screening and prediction of mental problems. In this review paper, we outline the vision of digital phenotyping of mental health (DPMH) by fusing the enriched data from ubiquitous sensors, social media and healthcare systems, and present a broad overview of DPMH from sensing and computing perspectives. We first conduct a systematical literature review and propose the research framework, which highlights the key aspects related with mental health, and discuss the challenges elicited by the enriched data for digital phenotyping. Next, five key research strands including affect recognition, cognitive analytics, behavioral anomaly detection, social analytics, and biomarker analytics are unfolded in the psychiatric context. Finally, we discuss various open issues and the corresponding solutions to underpin the digital phenotyping of mental health.
KeywordDigital phenotyping Big data Mental health Data mining Information fusion
DOI10.1016/j.inffus.2019.04.001
WOS KeywordFACIAL EXPRESSION RECOGNITION ; EMOTION RECOGNITION ; CLINICAL DEPRESSION ; RISK-FACTORS ; CLASSIFICATION ; SPEECH ; DISORDERS ; SLEEP ; METAANALYSIS ; SENTIMENT
Indexed BySCI
Language英语
Funding ProjectMinistry of Health of China[2017ZX10303401-002] ; Natural Science Foundation of China[71472175] ; Natural Science Foundation of China[71602184] ; Natural Science Foundation of China[71621002] ; National Key Research and Development Program of China[2016QY02D0305] ; National Key Research and Development Program of China[2017YFC1200302] ; National Institutes of Health[5R01DA037378-04] ; Fundamental Research Funds for the Central Universities[31020180QD140]
Funding OrganizationMinistry of Health of China ; Natural Science Foundation of China ; National Key Research and Development Program of China ; National Institutes of Health ; Fundamental Research Funds for the Central Universities
WOS Research AreaComputer Science
WOS SubjectComputer Science, Artificial Intelligence ; Computer Science, Theory & Methods
WOS IDWOS:000473800600023
PublisherELSEVIER
Citation statistics
Cited Times:2[WOS]   [WOS Record]     [Related Records in WOS]
Document Type期刊论文
Identifierhttp://ir.ia.ac.cn/handle/173211/26868
Collection中国科学院自动化研究所
Corresponding AuthorZheng, Xiaolong
Affiliation1.Northwestern Polytech Univ, Sch Comp Sci, Xian, Shaanxi, Peoples R China
2.Chinese Acad Sci, Inst Automat, State Key Lab Management & Control Complex Syst, Beijing, Peoples R China
3.Univ Arizona, Dept Management Informat Syst, Tucson, AZ 85721 USA
4.Univ Chinese Acad Sci, Beijing, Peoples R China
First Author AffilicationInstitute of Automation, Chinese Academy of Sciences
Corresponding Author AffilicationInstitute of Automation, Chinese Academy of Sciences
Recommended Citation
GB/T 7714
Liang, Yunji,Zheng, Xiaolong,Zeng, Daniel D.. A survey on big data-driven digital phenotyping of mental health[J]. INFORMATION FUSION,2019,52:290-307.
APA Liang, Yunji,Zheng, Xiaolong,&Zeng, Daniel D..(2019).A survey on big data-driven digital phenotyping of mental health.INFORMATION FUSION,52,290-307.
MLA Liang, Yunji,et al."A survey on big data-driven digital phenotyping of mental health".INFORMATION FUSION 52(2019):290-307.
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