Bio

My research group is interested in deriving control methods that provide a safe and stable physical human-robot interaction for people with mobility disorders undergoing neurorehabilitation. Specifically, my research group has designed assistive control methods for a lower-limb hybrid exoskeleton that combines functional electrical stimulation (FES) and a powered exoskeleton to enable people with complete paraplegia to stand and walk. Our long-term goal is to derive control methods that enable people with paraplegia to achieve functional independence. To support this goal, we use a variety of tools and methods from control theory that may include Robust Nonlinear Control, Model Predictive Control, Reinforcement Learning, and Neural Networks-based Adaptive Control. To provide stable interaction between the hybrid exoskeleton and a user, we are also investigating optimal surrogate signals derived from ultrasound imaging that inform residual muscle activity and the onset of FES-induced muscle fatigue. The lower-limb muscle activity or changes in muscle contractility are used to design a stable and controlled-assist from the exoskeleton. Other interests include control of time-delayed robotic systems such as during teleoperation, optimizing dosage of FES to minimize muscle fatigue and control of an acoustic-powered microrobot.

Research Interests

Robust Adaptive Nonlinear Control of Functional electrical Stimulation (FES)
Synergistic Control of Powered Exoskeleton and FES
Ultrasound Imaging for intent detection
Ultrasound Imaging to model FES-induced muscle fatigue

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Awards

2019 IEEE CSS Control Systems Technology Award
2018 NSF CAREER AWARD
2011 Alberta Innovates Postdoctoral Fellowship
2011 MAE Best Dissertation Award
2009 O Hugo Schuck Award for Best Application Paper

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Courses Taught

BME 205 Introduction to Biomedical Mechanics

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