Calculating Turns/Amplitude peak ratio of EMG interference pattern by using logistic curve fitting |
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| Affiliation: | 1. Second Department of Neurology, “Attikon” Hospital, School of Medicine, National and Kapodistrian University of Athens, Chaidari 12462, Athens, Greece;2. First Department of Neurology, School of Medicine, National and Kapodistrian University of Athens, Athens, Greece;1. Programa de Engenharia Biomédica (COPPE), Universidade Federal do Rio de Janeiro, Rio de Janeiro, RJ, Brazil;2. Centre of Precision Rehabilitation for Spinal Pain (CPR Spine), School of Sport, Exercise and Rehabilitation Sciences, College of Life and Environmental Sciences, University of Birmingham, Birmingham, UK;3. Department of Clinical and Experimental Sciences, Università degli Studi di Brescia, Brescia, Italy;4. Laboratorio di Ingegneria del Sistema Neuromuscolare (LISiN), Politecnico di Torino, Torino, TO, Italy;5. PolitoBIOMed Lab, Politecnico di Torino, Torino, Italy;1. Division of Applied Mechanics, Department of Mechanical Engineering, Polytechnique Montréal, Canada;2. Department of Physical Activity Sciences, University of Sherbrooke, Canada;3. Institut de recherche Robert Sauvé en santé et en sécurité du travail, Montréal, Canada;4. Department of Mechanical Engineering, Sharif University of Technology, Tehran, Iran;5. Center for Interdisciplinary Research in Rehabilitation of Greater Montreal (CRIR), Institut universitaire sur la réadaptation en déficience physique de Montréal (IURDPM), Centre intégré universitaire de santé et de services sociaux du Centre-Sud-de-l’Ile-de-Montréal (CCSMTL), Canada;1. Research Centre on Aging, CIUSSS de l’Estrie - CHUS, Sherbrooke, QC, Canada;2. Department of Mechanical Engineering, Université de Sherbrooke, Sherbrooke, QC, Canada;3. School of Rehabilitation, Université de Sherbrooke, Sherbrooke, QC, Canada;4. Department of Health Sciences, Université du Québec à Chicoutimi, Chicoutimi, QC, Canada;5. Research Centre on Health, CIUSSS du Saguenay-Lac-Saint-Jean, Chicoutimi, QC, Canada;1. Swedish School of Sport and Health Sciences (GIH), Sweden;2. Department of CLINTEC, Karolinska Institute, Sweden;1. Swedish School of Sport and Health Sciences (GIH), Sweden;2. Department of Neuroscience, Karolinska Institutet, Sweden;1. Faculty of Sport and Health Sciences, Neuromuscular Research Centre, University of Jyvaskyla, Finland;2. School of Sport and Exercise, University of Gloucestershire, UK;1. The University of Queensland, Laboratory for Motor Control and Pain Research, School of Biomedical Sciences, St Lucia, 4072 QLD, Australia;2. KK Women’s and Children’s Hospital, Physiotherapy Department, 229899, Singapore;3. The University of Queensland, School of Health & Rehabilitation Sciences, St Lucia, 4072 QLD, Australia;4. Royal Brisbane and Women’s Hospital, Tess Cramond Pain and Research Centre, Herston 4029, Australia;5. Queensland University of Technology at the Centre for Children’s Health Research, Biomechanics and Spine Research Group, South Brisbane, 4101 QLD, Australia |
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| Abstract: | The aim of the study was to test whether logistic curve fitting (LCF) of Turns = f(Amplitude) plots of single muscle contractions can provide a reliable alternative method for peak-ratio calculation. EMG signals from 74 biceps and 62 triceps contractions were analyzed by applying LCF to Turns = f(Amplitude) plots. Peak-ratio (peak-ratio2) could then be calculated as the point of the fitted line with the highest Turn/Amplitude value. LCF yielded R2 values > 0.95 in the vast majority of contractions studied (68/74 biceps and 53/62 triceps). Peak-ratio2 values had a very strong linear relationship with the corresponding values calculated by the traditional method (peak-ratio1) in both normal and neurogenic conditions. Furthermore, ROC curve analysis showed that peak-ratio1 and peak-ratio2 had similar AUC values. Based on the LCF equation, peak-ratio = T2*(p − 1)/A0*p*(p − 1)1/p. Therefore, peak-ratio is proportional to the maximum number of turns (T2), positively correlated to the rate of turns’ increment at the midpoint of the curve (p) and negatively correlated to the mean amplitude at the midpoint of the curve (A0). A0 is the variable that best discriminates between normal and neurogenic conditions. We provide an alternative method for peak-ratio calculation and show the variables that influence this sensitive marker of neurogenic disease. |
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| Keywords: | Turn Amplitude analysis Interference Electromyography Peak ratio |
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