Assessing Fall Risk Associated with Aging Through the Lens of Emerging Technology

The focus of this project is to use concepts in biomechanics and exercise prescription to design an exercise program to improve the muscle function and activity in older adults to decrease the risk of falls. The data will also be used in collaboration with the FAST faculty to design and validate an e-textile wearable technology to detect muscle activity during various movements.  

Students will also be able to experimentally test exercise prescription theories using biomechanical tools. Additionally, FAST faculty and students can use data collected from these tools to design wearables and improve the design. The integration of the new technology with the existing material used by faculty and students will enhance the ability to accurately study and analyze movement across different populations..

Integrating technology into learning will allow students to experiment and learn by analyzing movement using biomechanical tools, enhancing their understanding of injury prevention and exercise prescription. This cross-disciplinary initiative seeks to bridge gaps in current education by incorporating practical experiences and expanding knowledge application.

The project also aims to foster faculty collaboration across multiple disciplines, driving custom software development and wearable designs. The outcomes could significantly advance tools for reducing fall risks, thereby improving the quality of life for various populations.