email : 14a53d32aced1f56a73f02dc4be6190e0d1670ed7bade13862ce4c3ab6342474fc4b36fd2fcc82977c740f091114366f83828adc70892be11b695ee72dafd2e1fae66cae65950c96e543a6ec4590f1361f5229778a96ffcf1928500e7b961e16133bc9b262cb36e50388a34f1015cecc690767a17bdcc2980fdfe5e0233930c7
Affiliation of Author(s):Shanghai Jiao Tong University
Journal:Applied Psychology: Health and Well-Being
Abstract:Negative emotions such as loneliness, depression, and anxiety (LDA) are prevalent and pose significant challenges to emotional well-being. Traditional methods of assessing LDA, reliant on questionnaires, often face limitations because of participants' inability or potential bias. This study introduces emoLDAnet, an artificial intelligence (AI)-driven psychological framework that leverages video-recorded conversations to detect negative emotions through the analysis of facial expressions and physiological signals...
Document Type:J
Volume:17
Issue:1
Page Number:e12639
Translation or Not:no
Date of Publication:2025-02-17
Included Journals:SSCI
Indexed by:期刊论文
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