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Functional Electrical Stimulation (FES) systems are successful in restoringmotor function and supporting paralyzed users. Commercially available FESproducts are open loop, meaning that the system is unable to adapt to changingconditions with the user and their muscles which results in muscle fatigue andpoor stimulation protocols. This is because it is difficult to close the loopbetween stimulation and monitoring of muscle contraction using adaptivestimulation. FES causes electrical artefacts which make it challenging tomonitor muscle contractions with traditional methods such as electromyography(EMG). We look to overcome this limitation by combining FES with novelmechanomyographic (MMG) sensors to be able to monitor muscle activity duringstimulation in real time. To provide a meaningful task we built an FES cyclingrig with a software interface that enabled us to perform adaptive recording andstimulation, and then combine this with sensors to record forces applied to thepedals using force sensitive resistors (FSRs), crank angle position using amagnetic incremental encoder and inputs from the user using switches and apotentiometer. We illustrated this with a closed-loop stimulation algorithmthat used the inputs from the sensors to control the output of a programmableRehaStim 1 FES stimulator (Hasomed) in real-time. This recumbent bicycle rigwas used as a testing platform for FES cycling. The algorithm was designed torespond to a change in requested speed (RPM) from the user and change thestimulation power (% of maximum current mA) until this speed was achieved andthen maintain it.

Mechanomyography based closed-loop Functional Electrical Stimulation cycling system