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Rehabilitation robotics is an emerging tool for motor recovery from various neurological impairments. However, balancing the human and robot contribution is an open problem. While the motor input can reduce fatigue, which is often a limiting factor of functional electrical stimulation (FES) exercises, too much assistance can slow progress. For a person with a neurological impairment, FES can assist by strategically contracting their muscle(s) to achieve a desired limb movement; however, feasibility can be limited due to factors such as subject comfort, muscle mass, unnatural muscle fiber recruitment, and stimulation saturation. Thus, motor assistance in addition to FES can be useful for prolonging exercise while still ensuring physical effort from the person. In this paper, FES is applied to the biceps brachii to perform biceps curls, and motor assistance is applied intermittently whenever the FES input reaches a pre-set comfort threshold. Exponential stability of the human–robot system is proven with a Lyapunov-like switched systems stability analysis. Experimental results from participants with neurological conditions demonstrate the feasibility and performance of the controller. 

For individuals with neurological conditions (NCs) affecting the muscles of their legs, motorized functional electrical stimulation (FES) cycling is a rehabilitation strategy which offers numerous health benefits. Motorized FES cycling is an example of cooperative physical human-robot interaction where both the cycle’s motor and rider’s muscles (through electrical stimulation) must be well controlled to achieve desired performance. Since every NC is unique, adaptive control of motorized FES cycling is motivated over a one-size-fits-all approach. In this paper, a robust sliding-mode controller is employed on the rider’s muscles while an adaptive neural network admittance controller is employed on the cycle’s motor to preserve rider comfort and safety. Through a Lyapunov-like switched systems stability analysis, global asymptotic stability of the cycle controller is guaranteed and the muscle controller is proven to be passive with respect to the cycle. Experiments on one able-bodied participant were conducted to validate the control design. 

A wide variation in muscle strength and asymmetry exists in people with movement disorders. Functional electrical stimulation (FES) can be used to induce muscle contractions to assist and a motor can be used to both assist and resist a person’s volitional and/or FES-induced pedaling. On a traditional cycle with coupled pedals, people with neuromuscular asymmetries can primarily use their dominant (i.e., stronger) side to successfully pedal at a desired cadence, neglecting the side that would benefit most from rehabilitation. In this paper, a multi-level switched system is applied to a two-sided control objective to maintain a desired range of cadence using FES, an electric motor, and volitional pedaling. The non-dominant leg tracks the cadence range while the dominant leg tracks the position (offset by 180 degrees) and cadence of the first leg. Assistive, uncontrolled, and resistive modes are developed based on cadence and position for the non-dominant and dominant legs, respectively. Lyapunov-based methods for switched systems are used to prove global exponential tracking to the desired cadence range for the combined FES-motor control system.