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Human-like motion is a primary goal for many robotic assistive devices.Emulating the strategy of the human neuromuscular system may aid the control ofsuch powered devices, yet many challenges remain. In this study, weinvestigated the potential for using the winding filament model (WFM) of muscleto predict the net muscle moment of the ankle. The long-term goal is to usethis model to improve ankle control of a commercial powered exoskeleton. Theinnovation aspects of this study are: First, there have been no commercializedactive ankle exoskeletons available in the market. All the availableexoskeletons have passive ankle joints, which cannot mimic human movement,especially in normal and fast walking [1]. Second, the Winding Filament ModelController (WFMC) is the first control strategy based on a muscle model thatdoes not use an electromyographic (EMG) signal as an input. The activation,which is calculated from EMG, is a crucial input parameter for almost all ofthe control strategies based on muscle modeling. However, the winding filamentmuscle model can predict muscle force by using muscle length as the primaryinput, and the activation input signal could be either a square wave [33] or asimple bell shape function like our study. This is one of the most importantbenefits of the WFMC strategy, since it makes this bioinspired strategyapplicable for all patient populations, even those with impaired muscleactivities or without muscle activities (e.g. stroke, spinal cord injury,Parkinson disease, etc.). Third, the WFMC is adaptive to different tasks likewalking at different speeds, as well as walking over the incline and overstairs.

Simulating Ankle Torque during Walking Using a new Bioinspired Muscle Model with Application for Controlling a Powered Exoskeleton