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Open AccessArticle

FES-Induced Cycling in Complete SCI: A Simpler Control Method Based on Inertial Sensors

Institut National de Recherche en Informatique et en Automatique (INRIA), Université de Montpellier, 34095 Montpellier, France
CRRF La Châtaigneraie, 95180 Menucourt, France
Author to whom correspondence should be addressed.
Sensors 2019, 19(19), 4268;
Received: 22 July 2019 / Revised: 29 August 2019 / Accepted: 26 September 2019 / Published: 1 October 2019
(This article belongs to the Special Issue Multi-Sensor-Based Intelligent Systems for Physical Rehabilitation)
This article introduces a novel approach for a functional electrical stimulation (FES) controller intended for FES-induced cycling based on inertial measurement units (IMUs). This study aims at simplifying the design of electrical stimulation timing patterns while providing a method that can be adapted to different users and devices. In most of studies and commercial devices, the crank angle is used as an input to trigger stimulation onset. We propose instead to use thigh inclination as the reference information to build stimulation timing patterns. The tilting angles of both thighs are estimated from one inertial sensor located above each knee. An IF–THEN rule algorithm detects, online and automatically, the thigh peak angles in order to start and stop the stimulation of quadriceps muscles, depending on these events. One participant with complete paraplegia was included and was able to propel a recumbent trike using the proposed approach after a very short setting time. This new modality opens the way for a simpler and user-friendly method to automatically design FES-induced cycling stimulation patterns, adapted to clinical use, for multiple bike geometries and user morphologies. View Full-Text
Keywords: FES cycling; inertial sensors; neurorehabilitation FES cycling; inertial sensors; neurorehabilitation
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Sijobert, B.; Le Guillou, R.; Fattal, C.; Azevedo Coste, C. FES-Induced Cycling in Complete SCI: A Simpler Control Method Based on Inertial Sensors. Sensors 2019, 19, 4268.

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