The best ways to maximize mobility and even prevent back pain. Walk, work and wake better with these hamstring stretches. Breakthroughs, discoveries, and DIY tips sent six days a week. We have some news you're gonna want to sit down for--but you probably shouldn't: Your hamstrings are, in all likelihood, an anatomical disaster for a number of possible reasons, not least of which being excessive time spent seated on them. "The hamstrings are three muscles located on the back of your thigh, and they're responsible for bending your knee and extending your hip," says Marissa Cummo, PT, DPT, assistant director of physical therapy at NYC Health + Hospitals Bellevue .

Functional electrical stimulation (FES) has been increasingly integrated with other rehabilitation devices, including robots. FES cycling is one of the common FES applications in rehabilitation, which is performed by stimulating leg muscles in a certain pattern. The appropriate pattern varies across individuals and requires manual tuning which can be time-consuming and challenging for the individual user. Here, we present an AI-based method for finding the patterns, which requires no extra hardware or sensors. Our method has two phases, starting with finding model-based patterns using reinforcement learning and detailed musculoskeletal models. The models, built using open-source software, can be customised through our automated script and can be therefore used by non-technical individuals without extra cost. Next, our method fine-tunes the pattern using real cycling data. We test our both in simulation and experimentally on a stationary tricycle. In the simulation test, our method can robustly deliver model-based patterns for different cycling configurations. The experimental evaluation shows that our method can find a model-based pattern that induces higher cycling speed than an EMG-based pattern. By using just 100 seconds of cycling data, our method can deliver a fine-tuned pattern that gives better cycling performance. Beyond FES cycling, this work is a showcase, displaying the feasibility and potential of human-in-the-loop AI in real-world rehabilitation.