Mechanomyography based closed-loop Functional Electrical Stimulation cycling system

TL;DR

This paper presents a novel closed-loop FES cycling system that uses mechanomyography sensors to monitor muscle activity in real-time, overcoming limitations of traditional EMG-based monitoring affected by electrical artifacts.

Contribution

It introduces a new FES cycling setup integrating MMG sensors for real-time muscle monitoring and adaptive stimulation control, enhancing system responsiveness and reducing muscle fatigue.

Findings

Successful real-time muscle activity monitoring during FES cycling

Adaptive control of stimulation based on sensor feedback

Potential reduction in muscle fatigue and improved cycling performance

Abstract

Functional Electrical Stimulation (FES) systems are successful in restoring motor function and supporting paralyzed users. Commercially available FES products are open loop, meaning that the system is unable to adapt to changing conditions with the user and their muscles which results in muscle fatigue and poor stimulation protocols. This is because it is difficult to close the loop between stimulation and monitoring of muscle contraction using adaptive stimulation. FES causes electrical artefacts which make it challenging to monitor muscle contractions with traditional methods such as electromyography (EMG). We look to overcome this limitation by combining FES with novel mechanomyographic (MMG) sensors to be able to monitor muscle activity during stimulation in real time. To provide a meaningful task we built an FES cycling rig with a software interface that enabled us to perform adaptive recording and stimulation, and then combine this with sensors to record forces applied to the pedals using force sensitive resistors (FSRs), crank angle position using a magnetic incremental encoder and inputs from the user using switches and a potentiometer. We illustrated this with a closed-loop stimulation algorithm that used the inputs from the sensors to control the output of a programmable RehaStim 1 FES stimulator (Hasomed) in real-time. This recumbent bicycle rig was used as a testing platform for FES cycling. The algorithm was designed to respond to a change in requested speed (RPM) from the user and change the stimulation power (% of maximum current mA) until this speed was achieved and then maintain it.