Self-Optimizing Electrical Muscle Stimulation Garments for Rehabilitation

Injuries to the nervous system, such as spinal cord injury or stroke, can limit a person’s ability to control their muscles. Functional electrical stimulation (FES) is a therapy that uses electrical pulses applied through electrodes on the skin to activate muscles. FES can improve strength and coordination, but it is difficult to use. Electrodes must be placed precisely over specific muscle locations. This is a time-consuming process that relies on skilled clinicians and must be repeated each session. This project will develop a smart wearable garment that can automatically find the best locations for stimulation. By testing different stimulation patterns and measuring responses, the system will learn how to activate muscles effectively without manual setup. This technology will allow more people with movement impairments to benefit from therapy at home, improve comfort and consistency of treatment, and reduce healthcare costs. The project will also engage students in hands-on research and create teaching materials on wearable medical devices. The project will enable new advances in rehabilitation technology and help train the next generation of engineers and scientists. This project will advance a self-optimizing system for FES that eliminates the need for manual electrode placement. The system is designed to maintain reliable skin contact across different anatomies and movements. Real-time, machine learning-based control algorithms will be developed to identify optimal electrode placement corresponding to motor point locations on muscles. The system will automatically tune stimulation parameters and location to account for individual variability, posture changes, and session-to-session differences. The integrated hardware and algorithms will be evaluated against traditional manually placed FES. The project will advance the understanding of neuromuscular physiology and human-centered engineering. The results of this project will help guide the design of future stimulation technologies. This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.