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.

Research Highlights



  • One immediate postdoc position in data-driven control and ultrasound transducer design is available
  • Two Ph.D. positions in ultrasound-based data-driven control are available in Fall 2022.
  • Dr. Sharma wins NIBIB Trailblazer R21 Award for early-stage investigators

Recent Publications

  • An Iterative Learning Controller for a Switched Cooperative Allocation Strategy during Sit-to-Stand Tasks with a Hybrid Exoskeleton accepted in IEEE TCST
  • 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