Wireless Distributed Architecture for Therapeutic Functional Electrical Stimulation: a technology to design network-based muscle control

2015 7th International IEEE/EMBS Conference on Neural Engineering (NER)

et al. 2015

Functional electrical stimulation (FES) is a useful technique for restoring motor functions for spinal cord injured (SCI) patients. Muscle contractions can be artificially driven through delivery of electrical pulses to impaired muscles, and the electrical activity of contracted muscles under stimulus recorded by electromyography (EMG) is called M-wave. The FES-induced muscle activation which is represented by evoked EMG recordings can indicate the muscle state. Accurate control of muscle activation level by FES is the preliminary step for achieving more complicated FES control tasks. This paper proposes a real-time FES system for control of muscle activation by online modulating pulse width of stimulus. The excitation muscle dynamics is modelled by Hammerstain system with stimulus pulse width and eEMG as input and output respectively. The model predictive control strategy is adopted to compute the pulse width command sent to the Vivaltis wireless stimulator. Four reference muscle activation patterns are provided to test and validate the real-time closed-loop FES control system. Realtime control results on one able-bodied subject show promising control performances.

Section: Resultsmentioning

confidence: 99%

Real-time closed-loop FES control of muscle activation with evoked EMG feedback

Hayashibe

2015 7th International IEEE/EMBS Conference on Neural Engineering (NER)

et al. 2015

“…1 . The system consists of the wireless stimulator [ 31 ] (emanating from a transfer of our technology to Vivaltis Inc., Montpellier, France) as shown in Figs. 2 and 3 , eEMG (MP100, Biopac Systems Inc., Santa Barbara, CA, USA), torque acquisition devices (Biodex 3, Shirley Corp., NY, USA), and a laptop computer with the MATLAB (version 2012a) interface for remote control of wireless stimulator and real-time data acquisition/processing.…”

Section: Methodsmentioning

confidence: 99%

Real-time estimation of FES-induced joint torque with evoked EMG

Guiraud

J NeuroEngineering Rehabil

et al. 2016

BackgroundFunctional electrical stimulation (FES) is a neuroprosthetic technique for restoring lost motor function of spinal cord injured (SCI) patients and motor-impaired subjects by delivering short electrical pulses to their paralyzed muscles or motor nerves. FES induces action potentials respectively on muscles or nerves so that muscle activity can be characterized by the synchronous recruitment of motor units with its compound electromyography (EMG) signal is called M-wave. The recorded evoked EMG (eEMG) can be employed to predict the resultant joint torque, and modeling of FES-induced joint torque based on eEMG is an essential step to provide necessary prediction of the expected muscle response before achieving accurate joint torque control by FES.MethodsPrevious works on FES-induced torque tracking issues were mainly based on offline analysis. However, toward personalized clinical rehabilitation applications, real-time FES systems are essentially required considering the subject-specific muscle responses against electrical stimulation. This paper proposes a wireless portable stimulator used for estimating/predicting joint torque based on real time processing of eEMG. Kalman filter and recurrent neural network (RNN) are embedded into the real-time FES system for identification and estimation.ResultsPrediction results on 3 able-bodied subjects and 3 SCI patients demonstrate promising performances. As estimators, both Kalman filter and RNN approaches show clinically feasible results on estimation/prediction of joint torque with eEMG signals only, moreover RNN requires less computational requirement.ConclusionThe proposed real-time FES system establishes a platform for estimating and assessing the mechanical output, the electromyographic recordings and associated models. It will contribute to open a new modality for personalized portable neuroprosthetic control toward consolidated personal healthcare for motor-impaired patients.

“…The system consists of a wireless stimulator 7 (emanating from a transfer of our technology to Vivaltis Inc., Montpellier, France), eEMG (MP100, Biopac Systems Inc., Santa Barbara, CA, USA), torque acquisition devices (Biodex 3, Shirley Corp., NY, USA), and a laptop computer with the MATLAB (version 2012a) interface for remote control of wireless stimulator and real-time data acquisition/processing. The wireless stimulator is a regulated current dual-channel stimulator.…”

Section: Methodsmentioning

confidence: 99%

A hybrid functional electrical stimulation for real-time estimation of joint torque and closed-loop control of muscle activation

Guiraud

et al. 2016

Eur J Transl Myol

As a neuroprosthetic technique, functional electrical stimulation (FES) can restore lost motor performance of impaired patients. Through delivering electrical pulses to target muscles, the joint movement can be eventually elicited. This work presents a real-time FES system which is able to deal with two neuroprosthetic missions: one is estimating FES-induced joint torque with evoked electromyograph (eEMG), and the other is artificially controlling muscle activation with such eEMG feedback. The clinical experiment results on spinal cord injured (SCI) patients and healthy subjects show promising performance of the proposed FES system.