MoodCapture: Depression Detection Using In-the-Wild Smartphone Images.
Depression
Face
Facial Expressions
In-the-wild
Machine Learning
Mental Health
Mood
PHQ
Passive Sensing
Smartphones
Journal
Proceedings of the SIGCHI conference on human factors in computing systems. CHI Conference
Titre abrégé: Proc SIGCHI Conf Hum Factor Comput Syst
Pays: United States
ID NLM: 101620299
Informations de publication
Date de publication:
May 2024
May 2024
Historique:
medline:
5
8
2024
pubmed:
5
8
2024
entrez:
5
8
2024
Statut:
ppublish
Résumé
MoodCapture presents a novel approach that assesses depression based on images automatically captured from the front-facing camera of smartphones as people go about their daily lives. We collect over 125,000 photos in the wild from N=177 participants diagnosed with major depressive disorder for 90 days. Images are captured naturalistically while participants respond to the PHQ-8 depression survey question:
Identifiants
pubmed: 39100498
doi: 10.1145/3613904.3642680
pmc: PMC11296678
pii:
doi:
Types de publication
Journal Article
Langues
eng