Our primary research focus is on the design of nonlinear and adaptive control algorithms for functional electrical stimulation (FES) and rehabilitation robots. Currently, we are interested in designing control algorithms that coordinate FES and a powered exoskeleton that assist walking and standing functions in persons with spinal cord injury. Integrating FES and an exoskeleton has many technical and therapeutic benefits. FES induces artificial but active muscle contractions contributing to muscle health and reanimation of paralyzed muscles. However, FES-induced muscle fatigue hinders its clinical implementation. We are designing control algorithms that enable a powered exoskeleton to work in tandem with FES and thus compensate for the muscle fatigue. The control design problem is challenging due to the disparate dynamics of FES and the exoskeleton, need to monitor the state of the muscle, and residual volitional effort of the user, if present. We are also working to include novel muscle state sensing modalities such as ultrasound imaging and surface electromyography. Our research is multidisciplinary and therefore we collaborate with clinicians in physical medicine and rehabilitation, physical and occupational therapists, and faculty specializing in ultrasound imaging.
- Omer Hayou, an international student visiting us from Israel, won first place for his exoskeleton project in his college. Congrats! Omer.
- Congrats! Abdullah Ahmad for passing his M.S. thesis defense
- Congrats! to Zhiyu Sheng for passing his PhD Defense
- Switched Control of an N-Degree-of-Freedom Input Delayed Wearable Robotic System is accepted in Automatica
- A Tube-based Model Predictive Control Method to Regulate a Knee Joint with Functional Electrical Stimulation and Electric Motor Assist accepted in IEEE TCST
- Evaluation of Noninvasive Ankle Joint Effort Prediction Methods for Use in Neurorehabilitation using Electromyography and Ultrasound imaging accepted in IEEE TBME