Designing AI-Enabled Video Monitoring Clinician Dashboard for Neuropsychiatric Symptoms: A Survey of User Needs
Abstract
Objective: This study aimed to gather input from clinicians who assess and treat neuropsychiatric symptoms (NPS) to inform the development of a clinician dashboard to accompany an AI-enabled video-based monitoring system. Methods: n Results: The most important NPS to be detected were agitation/aggression, nighttime behaviors, depression, and anxiety. Multiple environmental factors were endorsed as being very important including: behavior frequency, intensity, and time of day. Conclusions: Findings demonstrate that the desired features of the dashboard were consistent across both prescribing and nonprescribing clinicians. Notably, some of the important symptoms and features that clinicians desired in a dashboard could not be extracted from existing sensor-based systems, but would be possible with an AI-enabled video monitoring system.
Fields of Study & Subjects
Digital Mental Health Interventions
Artificial Intelligence in Healthcare and Education
Emotion and Mood Recognition
Publication details
- Journal / source
- The American Journal of Geriatric Psychiatry Open Science Education and Practice
- Volume
- 9
- Pages
- 46–51
- Publication date
- 10 January 2026
- Language
- EN