Literature DB >> 22151359

Functional electrical stimulation control of standing and stepping after spinal cord injury: a review of technical characteristics.

Gustavo P Braz1, Michael Russold, Glen M Davis.   

Abstract

Objectives. To investigate the different approaches in the field of functional electrical stimulation (FES) control of gait and address fundamental perquisites to enable FES walking systems to become safer, more practical, and therefore clinically efficacious. Design. Systematic review was conducted from electronic data bases up to March 2008. Studies with innovative control strategies were highlighted for analysis, but all relevant literatures were described to deliver a broad viewpoint. Study Selection. FES studies applying 1) open and closed-loop controllers; 2) control algorithm techniques; or 3) feedback information to the control unit of neuromuscular stimulators via biological signals or artificial sensors. These studies were mostly associated to FES gait. Results. By far, more spinal cord-injured users have benefited from open-loop FES walking systems because they have had an easier and faster setup. However, because of their limitations over the control of knee extension, closed-loop control of gait may be a superior approach. The use of electromyogram to quantify quadriceps fatigue was not considered sufficiently appropriate to predict knee-buckle events; instead, the use of motion sensors for such purposes is recommended. Finite state controllers based on a set of deterministic rules to process feedback signals seemed more suitable to provide accurate command-and-control compared with dynamic or neural network controllers. Conclusions. Progress in the development of closed-loop FES walking systems has been impeded by their lack of practicality. In the near future, this obstacle could be overcome via implanted systems, especially if using controllers based on deterministic rule sets derived from motion sensor feedback.
© 2009 International Neuromodulation Society.

Entities:  

Year:  2009        PMID: 22151359     DOI: 10.1111/j.1525-1403.2009.00213.x

Source DB:  PubMed          Journal:  Neuromodulation        ISSN: 1094-7159


  18 in total

Review 1.  Brain computer interfaces, a review.

Authors:  Luis Fernando Nicolas-Alonso; Jaime Gomez-Gil
Journal:  Sensors (Basel)       Date:  2012-01-31       Impact factor: 3.576

2.  Motion control of the rabbit ankle joint with a flat interface nerve electrode.

Authors:  Hyun-Joo Park; Dominique M Durand
Journal:  Muscle Nerve       Date:  2015-09-07       Impact factor: 3.217

3.  The design of and chronic tissue response to a composite nerve electrode with patterned stiffness.

Authors:  M J Freeberg; M A Stone; R J Triolo; D J Tyler
Journal:  J Neural Eng       Date:  2017-03-13       Impact factor: 5.379

4.  Finite state control of a variable impedance hybrid neuroprosthesis for locomotion after paralysis.

Authors:  Thomas C Bulea; Rudi Kobetic; Musa L Audu; John R Schnellenberger; Ronald J Triolo
Journal:  IEEE Trans Neural Syst Rehabil Eng       Date:  2012-11-15       Impact factor: 3.802

5.  Intraoperative Responses May Predict Chronic Performance of Composite Flat Interface Nerve Electrodes on Human Femoral Nerves.

Authors:  Max J Freeberg; Rahila Ansari; Gilles C J Pinault; Lisa M Lombardo; Michael E Miller; Dustin J Tyler; Ronald J Triolo
Journal:  IEEE Trans Neural Syst Rehabil Eng       Date:  2019-11-04       Impact factor: 4.528

6.  An Ambulatory System for Gait Monitoring Based on Wireless Sensorized Insoles.

Authors:  Iván González; Jesús Fontecha; Ramón Hervás; José Bravo
Journal:  Sensors (Basel)       Date:  2015-07-09       Impact factor: 3.576

Review 7.  The effectiveness of FES-evoked EMG potentials to assess muscle force and fatigue in individuals with spinal cord injury.

Authors:  Morufu Olusola Ibitoye; Eduardo H Estigoni; Nur Azah Hamzaid; Ahmad Khairi Abdul Wahab; Glen M Davis
Journal:  Sensors (Basel)       Date:  2014-07-14       Impact factor: 3.576

8.  Reflex control of robotic gait using human walking data.

Authors:  Catherine A Macleod; Lin Meng; Bernard A Conway; Bernd Porr
Journal:  PLoS One       Date:  2014-10-27       Impact factor: 3.240

9.  Nonlinear dynamical model based control of in vitro hippocampal output.

Authors:  Min-Chi Hsiao; Dong Song; Theodore W Berger
Journal:  Front Neural Circuits       Date:  2013-02-20       Impact factor: 3.492

10.  Estimation of Electrically-Evoked Knee Torque from Mechanomyography Using Support Vector Regression.

Authors:  Morufu Olusola Ibitoye; Nur Azah Hamzaid; Ahmad Khairi Abdul Wahab; Nazirah Hasnan; Sunday Olusanya Olatunji; Glen M Davis
Journal:  Sensors (Basel)       Date:  2016-07-19       Impact factor: 3.576

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