Personalized Augmented Reality Obstacle Navigation Training for Balance and Fall Prevention in Aging Populations

Falls are a major risk for older adults, often leading to injury, reduced independence, and lower quality of life. This project will test a new training program using augmented reality (AR), where participants practice walking through virtual obstacles that reflect real-world challenges. Wearable sensors and the AR game will track balance and movement, while an artificial intelligence (AI) model adjusts difficulty to keep training personalized and safe. To reduce the risk of injury, training will take place in a clear, controlled space with safety supports nearby (e.g., a stable chair/rail), and participants will be supervised by trained staff who can assist immediately if balance is lost; sessions will follow predefined stop rules, and the program can pause or lower difficulty if instability, dizziness, or near-falls occur. The output of this project will be a data-driven and adaptive AR training approach that can support clinicians and researchers in developing more effective fall prevention strategies for older adults.