Feasibility and acceptability of a mobile-based emotion recognition approach for bipolar disorder

• Verfasst von: Daus, Henning [VerfasserIn]
• Verfasst von: Backenstraß, Matthias [VerfasserIn]
• Titel: Feasibility and acceptability of a mobile-based emotion recognition approach for bipolar disorder
• Verf.angabe: H. Daus, M. Backenstrass
• E-Jahr: 2021
• Jahr: 30 August 2021
• Umfang: 8 S.
• Fussnoten: Gesehen am 20.12.2021
• Titel Quelle: Enthalten in: International journal of interactive multimedia and artificial intelligence
• Ort Quelle: Oviedo : OpenLab, 2008
• Jahr Quelle: 2021
• Band/Heft Quelle: 7(2021), 2, Seite 7-14
• ISSN Quelle: 1989-1660
• DOI: doi:10.9781/ijimai.2021.08.015
• Datenträger: Online-Ressource
• Sprache: eng
• Sach-SW: Assistance Systems
• Sach-SW: Bipolar Disorder
• Sach-SW: Emotion Recognition
• Sach-SW: facial expression
• Sach-SW: Intelligent Systems
• Sach-SW: management
• Sach-SW: Mobile Health
• Sach-SW: mood
• Sach-SW: outcomes
• Sach-SW: psychoeducation
• Sach-SW: smartphones
• Sach-SW: social rhythms
• K10plus-PPN: 1782593373

Abstract

Over the past years, the mobile Health approach has motivated research projects to develop mood monitoring systems for bipolar disorder. Whereas mobile-based approaches have examined self-assessment or sensor data, so far, potentially important emotional aspects of this disease have been neglected. Thus, we developed an emotion-sensitive system that analyzes the verbal and facial expressions of bipolar patients in regard to their emotional cues. In this article, preliminary findings of a pilot study with five bipolar patients with respect to the acceptability and feasibility of the new approach are presented and discussed. There were individual differences in the usage frequency of the participants, and improvements regarding its handling were suggested. From the technical point of view, the video analysis was less dependable than the audio analysis and recognized almost exclusively the facial expressions of happiness. However, the system was feasible and well-accepted. The results indicate that further developments could facilitate the long-term analysis of expressed emotions in bipolar or other disorders without invading the privacy of patients.