Literature DB >> 21133839

Myoelectric control in neurorehabilitation.

Ning Jiang1, Deborah Falla, Andrea d'Avella, Bernhard Graimann, Dario Farina.   

Abstract

A myoelectric signal, or electromyogram (EMG), is the electrical manifestation of a muscle contraction. Through advanced signal processing techniques, information on the neural control of muscles can be extracted from the EMG, and the state of the neuromuscular system can be inferred. Because of its easy accessibility and relatively high signal-to-noise ratio, EMG has been applied as a control signal in several neurorehabilitation devices and applications, such as multi-function prostheses and orthoses, rehabilitation robots, and functional electrical stimulation/therapy. These EMG-based neurorehabilitation modules, which constitute muscle-machine interfaces, are applied for replacement, restoration, or modulation of lost or impaired function in research and clinical settings. The purpose of this review is to discuss the assumptions of EMG-based control and its applications in neurorehabilitation.

Mesh:

Year:  2010        PMID: 21133839     DOI: 10.1615/critrevbiomedeng.v38.i4.30

Source DB:  PubMed          Journal:  Crit Rev Biomed Eng        ISSN: 0278-940X


  8 in total

Review 1.  Neurorobotic and hybrid management of lower limb motor disorders: a review.

Authors:  Juan C Moreno; Antonio J Del Ama; Ana de Los Reyes-Guzmán; Angel Gil-Agudo; Ramón Ceres; José L Pons
Journal:  Med Biol Eng Comput       Date:  2011-08-17       Impact factor: 2.602

2.  EMG feature assessment for myoelectric pattern recognition and channel selection: a study with incomplete spinal cord injury.

Authors:  Jie Liu; Xiaoyan Li; Guanglin Li; Ping Zhou
Journal:  Med Eng Phys       Date:  2014-05-17       Impact factor: 2.242

3.  Human-Machine Interface for the Control of Multi-Function Systems Based on Electrocutaneous Menu: Application to Multi-Grasp Prosthetic Hands.

Authors:  Jose Gonzalez-Vargas; Strahinja Dosen; Sebastian Amsuess; Wenwei Yu; Dario Farina
Journal:  PLoS One       Date:  2015-06-12       Impact factor: 3.240

Review 4.  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

5.  Estimation of absolute states of human skeletal muscle via standard B-mode ultrasound imaging and deep convolutional neural networks.

Authors:  Ryan J Cunningham; Ian D Loram
Journal:  J R Soc Interface       Date:  2020-01-29       Impact factor: 4.118

6.  EMG-based simultaneous and proportional estimation of wrist/hand kinematics in uni-lateral trans-radial amputees.

Authors:  Ning Jiang; Johnny L G Vest-Nielsen; Silvia Muceli; Dario Farina
Journal:  J Neuroeng Rehabil       Date:  2012-06-28       Impact factor: 4.262

7.  EMG-Based Continuous and Simultaneous Estimation of Arm Kinematics in Able-Bodied Individuals and Stroke Survivors.

Authors:  Jie Liu; Sang Hoon Kang; Dali Xu; Yupeng Ren; Song Joo Lee; Li-Qun Zhang
Journal:  Front Neurosci       Date:  2017-08-25       Impact factor: 4.677

8.  The effect of chronic, non-specific low back pain on superficial lumbar muscle activity: a protocol for a systematic review and meta-analysis.

Authors:  Andy Sanderson; Alison B Rushton; Eduardo Martinez Valdes; Nicola R Heneghan; Alessio Gallina; Deborah Falla
Journal:  BMJ Open       Date:  2019-10-31       Impact factor: 2.692

  8 in total

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