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Critical Reviews™ in Biomedical Engineering

Published 6 issues per year

ISSN Print: 0278-940X

ISSN Online: 1943-619X

SJR: 0.262 SNIP: 0.372 CiteScore™:: 2.2 H-Index: 56

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Myoelectric Control in Neurorehabilitation

Volume 38, Issue 4, 2010, pp. 381-391
DOI: 10.1615/CritRevBiomedEng.v38.i4.30
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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.

CITED BY
  1. Graimann Bernhard, Dietl Hans, Introduction to Upper Limb Prosthetics, in Introduction to Neural Engineering for Motor Rehabilitation, 2013. Crossref

  2. Ambrosini Emilia, Ferrante Simona, Pedrocchi Alessandro, Design of Myocontrolled Neuroprosthesis, in Applications, Challenges, and Advancements in Electromyography Signal Processing, 2014. Crossref

  3. Liu Jie, Feature dimensionality reduction for myoelectric pattern recognition: A comparison study of feature selection and feature projection methods, Medical Engineering & Physics, 36, 12, 2014. Crossref

  4. Ambrosini Emilia, Ferrante Simona, Schauer Thomas, Klauer Christian, Gaffuri Marina, Ferrigno Giancarlo, Pedrocchi Alessandra, A myocontrolled neuroprosthesis integrated with a passive exoskeleton to support upper limb activities, Journal of Electromyography and Kinesiology, 24, 2, 2014. Crossref

  5. Ambrosini Emilia, Bejarano Noelia Chia, Pedrocchi Alessandra, Sensors for Motor Neuroprosthetics, in Emerging Theory and Practice in Neuroprosthetics, 2014. Crossref

  6. Liu Jie, Li Xiaoyan, Li Guanglin, Zhou Ping, EMG feature assessment for myoelectric pattern recognition and channel selection: A study with incomplete spinal cord injury, Medical Engineering & Physics, 36, 7, 2014. Crossref

  7. Moreno Juan C., del Ama Antonio J., de los Reyes-Guzmán Ana, Gil-Agudo Ángel, Ceres Ramón, Pons José L., Neurorobotic and hybrid management of lower limb motor disorders: a review, Medical & Biological Engineering & Computing, 49, 10, 2011. Crossref

  8. Fang Yinfeng, Liu Honghai, Li Gongfa, Zhu Xiangyang, A Multichannel Surface EMG System for Hand Motion Recognition, International Journal of Humanoid Robotics, 12, 02, 2015. Crossref

  9. Fang Yinfeng, Liu Honghai, Robust sEMG electrodes configuration for pattern recognition based prosthesis control, 2014 IEEE International Conference on Systems, Man, and Cybernetics (SMC), 2014. Crossref

  10. Fanta Kathryn, Pierce Scott, Extracting information from myoelectric signals, 2015 Systems and Information Engineering Design Symposium, 2015. Crossref

  11. Atoufi B., Kamavuako E. N., Hudgins B., Englehart K., Classification of hand and wrist tasks of unknown force levels using muscle synergies, 2015 37th Annual International Conference of the IEEE Engineering in Medicine and Biology Society (EMBC), 2015. Crossref

  12. Ibitoye Morufu, Estigoni Eduardo, Hamzaid Nur, Wahab Ahmad, Davis Glen, The Effectiveness of FES-Evoked EMG Potentials to Assess Muscle Force and Fatigue in Individuals with Spinal Cord Injury, Sensors, 14, 7, 2014. Crossref

  13. Gonzalez-Vargas Jose, Dosen Strahinja, Amsuess Sebastian, Yu Wenwei, Farina Dario, Bensmaia Sliman J., Human-Machine Interface for the Control of Multi-Function Systems Based on Electrocutaneous Menu: Application to Multi-Grasp Prosthetic Hands, PLOS ONE, 10, 6, 2015. Crossref

  14. Delis Ioannis, Panzeri Stefano, Pozzo Thierry, Berret Bastien, A unifying model of concurrent spatial and temporal modularity in muscle activity, Journal of Neurophysiology, 111, 3, 2014. Crossref

  15. Lu Huiyang, Zhang Haoshi, Lin Mouguang, Wang Ruomei, A Robust Feature Set for Wearable Multichannel Myoelectric Devices in Practice, 2016 6th International Conference on Digital Home (ICDH), 2016. Crossref

  16. Lu Huiyang, Zhang Haoshi, Wang Zhong, Wang Ruomei, Li Guanglin, Using spatial features for classification of combined motions based on common spatial pattern, 2017 39th Annual International Conference of the IEEE Engineering in Medicine and Biology Society (EMBC), 2017. Crossref

  17. Liu Jie, Kang Sang Hoon, Xu Dali, Ren Yupeng, Lee Song Joo, Zhang Li-Qun, EMG-Based Continuous and Simultaneous Estimation of Arm Kinematics in Able-Bodied Individuals and Stroke Survivors, Frontiers in Neuroscience, 11, 2017. Crossref

  18. Deng Jia, Niu Jian, Wang Kun, Xie Li, Yang Geng, Discriminant Analysis Based EMG Pattern Recognition for Hand Function Rehabilitation, in Wireless Mobile Communication and Healthcare, 247, 2018. Crossref

  19. Li Gongfa, Zhang Leilei, Sun Ying, Kong Jianyi, Towards the sEMG hand: internet of things sensors and haptic feedback application, Multimedia Tools and Applications, 78, 21, 2019. Crossref

  20. Markovic Marko, Dosen Strahinja, Farina Dario, Switching between the Modes of Control: Implications for the Closed Loop Control of Prostheses, in Converging Clinical and Engineering Research on Neurorehabilitation, 1, 2013. Crossref

  21. Lambrecht Stefan, Urra Oiane, Grosu Svetlana, Nombela Soraya Pérez, Emerging Rehabilitation in Cerebral Palsy, in Emerging Therapies in Neurorehabilitation, 4, 2014. Crossref

  22. Paredes L. P., Graimann B., Advanced Myoelectric Control of Prostheses: Requirements and Challenges, in Converging Clinical and Engineering Research on Neurorehabilitation, 1, 2013. Crossref

  23. Sanderson Andy, Rushton Alison B, Martinez Valdes Eduardo, Heneghan Nicola R, Gallina Alessio, Falla Deborah, The effect of chronic, non-specific low back pain on superficial lumbar muscle activity: a protocol for a systematic review and meta-analysis, BMJ Open, 9, 10, 2019. Crossref

  24. Cunningham Ryan J., Loram Ian D., Estimation of absolute states of human skeletal muscle via standard B-mode ultrasound imaging and deep convolutional neural networks, Journal of The Royal Society Interface, 17, 162, 2020. Crossref

  25. McDonald Craig G., Sullivan Jennifer L., Dennis Troy A., O'Malley Marcia K., A Myoelectric Control Interface for Upper-Limb Robotic Rehabilitation Following Spinal Cord Injury, IEEE Transactions on Neural Systems and Rehabilitation Engineering, 28, 4, 2020. Crossref

  26. Campanini Isabella, Disselhorst-Klug Catherine, Rymer William Z., Merletti Roberto, Surface EMG in Clinical Assessment and Neurorehabilitation: Barriers Limiting Its Use, Frontiers in Neurology, 11, 2020. Crossref

  27. Agostini Valentina, Ghislieri Marco, Rosati Samanta, Balestra Gabriella, Knaflitz Marco, Surface Electromyography Applied to Gait Analysis: How to Improve Its Impact in Clinics?, Frontiers in Neurology, 11, 2020. Crossref

  28. Nim Casper Glissmann, O’Neill Søren, Geltoft Anne Gellert, Jensen Line Korsholm, Schiøttz-Christensen Berit, Kawchuk Gregory Neil, A cross-sectional analysis of persistent low back pain, using correlations between lumbar stiffness, pressure pain threshold, and heat pain threshold, Chiropractic & Manual Therapies, 29, 1, 2021. Crossref

  29. Guo Lin, Lu Zongxing, Yao Ligang, Human-Machine Interaction Sensing Technology Based on Hand Gesture Recognition: A Review, IEEE Transactions on Human-Machine Systems, 51, 4, 2021. Crossref

  30. Jiang Ning, Vest-Nielsen Johnny LG, Muceli Silvia, Farina Dario, EMG-based simultaneous and proportional estimation of wrist/hand kinematics in uni-lateral trans-radial amputees, Journal of NeuroEngineering and Rehabilitation, 9, 1, 2012. Crossref

  31. Palumbo Arrigo, Vizza Patrizia, Calabrese Barbara, Ielpo Nicola, Biopotential Signal Monitoring Systems in Rehabilitation: A Review, Sensors, 21, 21, 2021. Crossref

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