This research uses AI-powered markerless motion capture to preserve Indigenous cultural dances as digital archives. By recording thousands of movement data points, it safeguards intangible cultural heritage for future generations. The work aims to extend this technology globally, ensuring every culture has the tools to preserve its unique traditions.

This research develops a fast, space-efficient method for assessing fall risk in older adults using wearable sensors and AI analysis of a seated foot-tapping task. Early findings show that slower, inconsistent tapping predicts higher fall risk. The approach could improve prevention strategies, reduce healthcare costs, and help older adults maintain independence.