Types of Data with Algorithms for Assessing Mental Health Conditions

被引:0
|
作者
Gore, Ela [1 ]
Rathi, Sheetal [1 ]
机构
[1] TCET, Dept Comp Engn, Mumbai, Maharashtra, India
关键词
Mental Health Illness; statistics; sensors; machine learning algorithms; PREVALENCE; DISORDER;
D O I
10.1109/iccubea47591.2019.9128667
中图分类号
TP [自动化技术、计算机技术];
学科分类号
0812 ;
摘要
Mental Health assessment is done by psychiatrists. With the advent of technology several types of data have been used to detect mental health illness and provide an access to the people. Paper tries to give an overall view of the types of data used for monitoring mental health by various authors. The types of data taken for studies in assessing mental health conditions are speech/audio clips, email conversations, wrist sensors, f-MRI scans, EOG data, structural-MRI scans, resting state EEG, questionnaire based/survey data, Twitter data, wireless monitoring with the help of computer algorithms. This paper gives a survey of kinds of data and the algorithms studied and applied by multiple authors.
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页数:8
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