CS@W&M graduate students and faculty receive Best Paper Award at CHASE’24

In a groundbreaking partnership, the Health Comp Group at William & Mary has joined forces with VCU Health and the VCU School of Nursing to explore the potential of machine learning and wearable computing in detecting and treating symptoms of Parkinson's disease. The collaboration has focused on addressing the critical issue of "Freezing of Gait" (FoG), a dangerous symptom that significantly increases the risk of falls and injuries among Parkinson's patients.

The joint effort led to the creation of the Gait-Guard FoG detection and treatment system. This innovative system is closed-loop, non-intrusive, and operates in real-time, making it highly acceptable to patients. Through advanced domain knowledge-driven feature engineering and multivariate time-series transformer models, Gait-Guard has set a new benchmark for FoG detection, achieving the lowest false positive treatment rate among all validated systems proposed to date.

Highlighting the success of this collaboration, the paper titled "Gait-Guard: Turn-aware Freezing of Gait Detection for Non-intrusive Intervention Systems" was awarded the Best Paper Award at the ACM/IEEE Conference on Connected Health: Applications, Systems and Engineering Technologies (CHASE) in June 2024.

The team at William & Mary expressed their enthusiasm for continuing this fruitful partnership with VCU, aiming to enhance how clinicians monitor and treat Parkinson's disease patients.