Project Category: Healthcare and Human Performance

A Transfer Learning Framework for Creating Subject-Specific Musculoskeletal Models of the Hand

This project utilizes machine learning methods to examine how subject-specific differences influence hand function and create subject-specific computer models from easy to obtain clinical data. Completion of this project will critically advance the ability to efficiently create subject-specific models of the hand and understand the biomechanical mechanism underlying hand force production.

Artificial neural networks meet biological neural networks: designing personalized stimulation for the data-driven control of neural dynamics

To address these issues, we will leverage the wealth of data that multi-subject experiments provide, as well as the computational resources newly available at UF.

We will develop new AI methods that utilize in-vivo neural responses to design and implement personalized stimulation in real-time.