Wearable Data From Subjects Playing Super Mario, Taking University Exams, or Performing Physical Exercise Help Detect Acute Mood Disorder Episodes via Self-Supervised Learning: Prospective, Exploratory, Observational Study

• Main Authors: Filippo Corponi (Author), Bryan M Li (Author), Gerard Anmella (Author), Clàudia Valenzuela-Pascual (Author), Ariadna Mas (Author), Isabella Pacchiarotti (Author), Marc Valentí (Author), Iria Grande (Author), Antoni Benabarre (Author), Marina Garriga (Author), Eduard Vieta (Author), Allan H Young (Author), Stephen M Lawrie (Author), Heather C Whalley (Author), Diego Hidalgo-Mazzei (Author), Antonio Vergari (Author)
• Format: Book
• Published: JMIR Publications, 2024-07-01T00:00:00Z.
• Subjects: article
• Online Access: Connect to this object online.

BackgroundPersonal sensing, leveraging data passively and near-continuously collected with wearables from patients in their ecological environment, is a promising paradigm to monitor mood disorders (MDs), a major determinant of the worldwide disease burden. However, collecting and annotating wearabl...