MindStep: AI Gait Monitoring of Mental Health

Summary

Mental health issues on college campuses are on the rise, particularly anxiety and depression, which negatively affect academic performance and increase dropout rates. The prevalence of mental health conditions has significantly risen, especially post-COVID-19, emphasizing the need for innovative early detection methods. The proposed interdisciplinary project aims to develop a large-scale, proactive solution using existing surveillance infrastructure and AI-based motion capture to monitor gait parameters such as walking speed and stride length. The goal is to detect worsening mental health conditions on college campuses based on variations in these gait parameters. This approach builds on existing research showing relationships between gait changes and mental health and aims to extend these findings to naturalistic settings.

Team

Moataz Eltoukhy (Kinesiology and Sport Sciences), Jennifer Britton (Psychology)

MindStep: AI Gait Monitoring of Mental Health