Biomechanics Experiments
We perform human biomechanics experiments in which we record movement kinematics and muscle activity during various walking tasks in controlled lab settings and uncontrolled outdoor environments. We also use wearable sensors to monitor physical activity, balance, and falls during daily-life, providing real-world data to complement our biomechanics experiments. We then employ data science techniques such as machine learning to identify patterns and relationships between muscle activity, movement kinematics, and daily-life mobility.
You may be interested in working in this area if you enjoy: leveraging complex, multi-modal datasets to unravel how the nervous system recruits muscles to optimize performance; working with human participants using motion capture, inertial measurement units, electromyography sensors, low-cost accelerometers, and other similar equipment (see Facilities for more information); developing novel methods to measure walking and balance “in the wild” via wearable sensors; high-performance computing on HiPerGator
Our work in this area has been funded by the National Institutes of Health (F32NS087775, R21AG067388, R15AG068935) and the UF Claude D. Pepper Older American’s Independence Center
current Projects:
- We are exploring how embedding the control of balance into the muscle coordination for walking contributes to daily-life mobility in populations with motor impairments and enhances balance performance in populations with motor expertise. (Example papers: 1, 2, 3)
- In collaboration with our partners at the University of North Carolina, we are exploring biomechanical, neuromuscular, and psychological predictors of poor balance control and increased fall risk in older adults. (Example papers: 1,2)