Consensus for experimental design in electromyography (CEDE) project: Amplitude normalization matrix |
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| Institution: | 1. School of Health and Rehabilitation Sciences, The University of Queensland, Brisbane, Australia;2. Worcester Polytechnic Institute, Worcester, MA, USA;3. Department of Human Movement Sciences, Vrije Universiteit Amsterdam, Amsterdam Movement Sciences, Amsterdam, the Netherlands;4. Faculty of Sport Sciences, Laboratory “Movement, Interactions, Performance” (EA 4334), University of Nantes, Nantes, France;5. Institut Universitaire de France (IUF), Paris, France;6. School of Electrical and Electronic Engineering, University College Dublin, Dublin, Ireland;7. LISiN, Department of Electronics and Telecommunications, Politecnico di Torino, Torino, Italy;8. Department of Clinical Research and Department of Sports Science and Clinical Biomechanics, University of Southern Denmark, Odense, Denmark;9. Centre for Health, Exercise and Sports Medicine, Department of Physiotherapy, University of Melbourne, Parkville, Australia;10. Auckland Bioengineering Institute and Department of Engineering Science, University of Auckland, Auckland, New Zealand;11. Trinity College Institute of Neuroscience, School of Psychology, Trinity College Dublin, Dublin, Ireland;12. School of Psychology, Queen’s University Belfast, Belfast, UK;13. School of Human Movement and Nutrition Sciences, The University of Queensland, Australia;14. Department of Rehabilitation and Prevention Engineering, Institute of Applied Medical Engineering, RWTH Aachen University, Aachen, Germany;15. Department of Integrative Physiology, University of Colorado Boulder, CO, USA;p. Centre of Precision Rehabilitation for Spinal Pain (CPR Spine), School of Sport, Exercise and Rehabilitation Sciences, University of Birmingham, UK;q. Department of Bioengineering, Imperial College London, London, UK;r. Neuroscience Research Australia, University of New South Wales, Sydney, Australia;s. Faculty of Electrical Engineering and Computer Science, University of Maribor, Koroška cesta 46, Maribor, Slovenia;t. Brain and Mind Centre, University of Sydney, Sydney, Australia;u. Department of Neurology, Royal Prince Alfred Hospital, Sydney, Australia;v. US Department of Veterans Affairs, USA;w. Northwestern University, Evanston, IL, USA;x. Shirley Ryan AbilityLab, Chicago, IL, USA;y. Sobell Department of Motor Neuroscience and Movement Disorders, UCL Institute of Neurology, London, UK;z. School of Biomedical Sciences, The University of Queensland, Brisbane, Australia;1. Department of Physical Therapy and Rehabilitation Science, University of Maryland School of Medicine, Baltimore, MD, USA;2. Department of Kinesiology, University of Texas at Austin, Austin, TX, USA;1. EA 7377 BIOTN, Laboratoire Analyse et Restauration du Mouvement, Université Paris-Est, Service de Rééducation Neurolocomotrice, AP-HP, Hôpitaux Universitaires Henri Mondor, Créteil, France;2. LISiN – Laboratorio di Ingegneria del Sistema Neuromuscolare, Dipartimento di Elettronica e Telecomunicazioni, Politecnico di Torino, Torino, Italy;1. Laboratory of Neuromuscular Biomechanics, School of Health and Sport Science, Chukyo University, 101 Tokodachi, Kaizu-cho, Toyota-shi, Aichi 470-0393, Japan;2. Faculty of Electrical Engineering and Computer Science, University of Maribor, Koroška cesta 46, 2000 Maribor, Slovenia;3. Toyota Motor Corporation, 1 Toyotacho, Toyota-shi, Aichi 471-8571, Japan;1. Nantes University, Laboratory “Movement, Interactions, Performance” (EA 4334), Nantes, France;2. The University of Queensland, NHMRC Centre of Clinical Research Excellence in Spinal Pain, Injury and Health, School of Health and Rehabilitation Sciences, Brisbane, Australia;3. Institut Universitaire de France (IUF), Paris, France;4. Legs Walking AbilityLab, Shirley Ryan AbilityLab, Chicago, IL, USA;5. Department of Physical Medicine and Rehabilitation, Northwestern University, Chicago, IL, USA;6. Department of Artificial Intelligence in Biomedical Engineering, Faculty of Engineering, Friedrich-Alexander University, Erlangen-Nuremberg, 91052 Erlangen, Germany;7. Department of Biomedical Sciences, University of Padova, Padua, Italy;8. Department of Bioengineering, Faculty of Engineering, Imperial College London, UK;9. Department of Clinical and Movement Disorders, Institute of Neurology, University College London, London WC1N 3BG, UK;10. Department of Movement, Human and Health Sciences, University of Rome “Foro Italico”, Rome, Italy;11. Faculty of Electrical Engineering and Computer Science, University of Maribor, Slovenia |
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| Abstract: | The general purpose of normalization of EMG amplitude is to enable comparisons between participants, muscles, measurement sessions or electrode positions. Normalization is necessary to reduce the impact of differences in physiological and anatomical characteristics of muscles and surrounding tissues. Normalization of the EMG amplitude provides information about the magnitude of muscle activation relative to a reference value. It is essential to select an appropriate method for normalization with specific reference to how the EMG signal will be interpreted, and to consider how the normalized EMG amplitude may change when interpreting it under specific conditions. This matrix, developed by the Consensus for Experimental Design in Electromyography (CEDE) project, presents six approaches to EMG normalization: (1) Maximal voluntary contraction (MVC) in same task/context as the task of interest, (2) Standardized isometric MVC (which is not necessarily matched to the contraction type in the task of interest), (3) Standardized submaximal task (isometric/dynamic) that can be task-specific, (4) Peak/mean EMG amplitude in task, (5) Non-normalized, and (6) Maximal M-wave. General considerations for normalization, features that should be reported, definitions, and “pros and cons” of each normalization approach are presented first. This information is followed by recommendations for specific experimental contexts, along with an explanation of the factors that determine the suitability of a method, and frequently asked questions. This matrix is intended to help researchers when selecting, reporting and interpreting EMG amplitude data. |
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| Keywords: | Electromyography Muscle activation Amplitude normalization Consensus |
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