Simple action for depression detection: using kinect-recorded human kinematic skeletal data

• Published in: BMC psychiatry Vol. 21; no. 1; pp. 205 - 11
• Main Authors: Li, Wentao, Wang, Qingxiang, Liu, Xin, Yu, Yanhong
• Format: Journal Article
• Language: English
• Published: England BioMed Central 22.04.2021; BMC
• Subjects: Age; Biomechanical Phenomena; Classification; Computer applications; Data collection; Datasets; Depression - diagnosis; Depression detection; Design; Experiments; Female; Gender; Human skeleton joints; Humans; Insomnia; Kinect sensor; Kinematics; Learning algorithms; Logistic Models; Machine Learning; Male; Mathematical models; Mental depression; Mental disorders; Mental health; Predictions; Psychiatry; Questionnaires; Skeleton; Suicides & suicide attempts; Support Vector Machine; Depression detection; Kinect sensor; Human skeleton joints; Machine learning

Depression, a common worldwide mental disorder, which brings huge challenges to family and social burden around the world is different from fluctuant emotion and psychological pressure in their daily life. Although body signs have been shown to present manifestations of depression in general, few re...