ICEP: An Instrumented Cycling Ergometer Platform for the Assessment of Advanced FES Strategies.

BACKGROUND: Functional electrical stimulation (FES) cycling has seen an upsurge in interest over the last decade. The present study describes the novel instrumented cycling ergometer platform designed to assess the efficiency of electrical stimulation strategies. The capabilities of the platform are showcased in an example determining the adequate stimulation patterns for reproducing a cycling movement of the paralyzed legs of a spinal cord injury (SCI) subject. METHODS: Two procedures have been followed to determine the stimulation patterns: (1) using the EMG recordings of the able-bodied subject; (2) using the recordings of the forces produced by the SCI subject's stimulated muscles. RESULTS: the stimulation pattern derived from the SCI subject's force output was found to produce 14% more power than the EMG-derived stimulation pattern. CONCLUSIONS: the cycling platform proved useful for determining and assessing stimulation patterns, and it can be used to further investigate advanced stimulation strategies.

Optimization of Seating Position and Stimulation Pattern in Functional Electrical Stimulation Cycling: Simulation Study.

Two significant challenges facing functional electrical stimulation (FES) cycling are the low power output and early onset of muscle fatigue, mainly due to the non-physiological and superficial recruitment of motor units and weakness of the antagonistic muscles. Thus optimization of the cycling biomechanical properties and stimulation pattern to achieve maximum output power with minimum applied electrical stimulus is of great importance. To find the optimal seating position and stimulation pattern, the previous works either ignored the muscle's force-velocity and force-length properties or employed complicated muscle models which was a massive barrier to clinical experiments. In this work, an easy-to-use and precise muscle model in conjunction with Jacobian-based torque transfer functions were adopted to determine the optimal seating position, trunk angle, crank arm length, and stimulation intervals. Furthermore, the impact of muscle force-velocity factor in finding the optimal seating position and stimulation intervals was investigated. The simulation models showed the trivial effect of the force-velocity factor on the resulting optimal seating position of six healthy simulated subjects. This method can enhance the FES-cycling performance and shorten the time-consuming process of muscle model identification for optimization purposes.