Repeatability of surface EMG variables during voluntary isometric contractions of the biceps brachii muscle
Introduction
The value of surface electromyography techniques for non-invasive muscle characterization has been demonstrated by many authors 13, 17, 18, 22, 26, 33, 36, 40, 44, 48. Either voluntary or electrically elicited isometric contractions have been adopted for the purpose of associating EMG variables to muscle conditions. Spectral features such as the mean and the median frequency (MNF and MDF), amplitude features such as the average rectified value and the root mean square value (ARV and RMS) and muscle fiber conduction velocity (CV) have been the variables chosen by most investigators to quantify myoelectric manifestations of muscle fatigue. Such manifestations consist in a “slowing” of the signal reflected by a compression of its power spectrum, a decrease of MDF and MNF and an increase of ARV and RMS. These changes have been demonstrated to reflect muscle properties and fiber constituency 16, 18, 19, 25, 33, 44, 46, 48, recruitment strategies 3, 43, 45 and have been applied in ergonomics 13, 22, 23, back analysis 4, 5, 14, 40, 43 and dentistry [17]. Studies have been performed during isometric constant force contractions as well as during isometric ramp and stepwise contractions using surface electrodes 6, 7, 8, 9 as well as wires [12]. The potential clinical usefulness of this technique is unquestionable but conditioned by an acceptable level of repeatability of the estimates of the variables of interest.
Literature data on repeatability are neither complete nor satisfactory, concern mostly test–retest situations or their variations, or are largely focused on electrically evoked signals 4, 5, 13, 26, 35, 36, 41, 47. Only a few reports provide results or conclusions with the proper statistical support 40, 43. It is the purpose of this work to contribute additional knowledge to the issue of repeatability of (a) estimates of spectral and amplitude variables and muscle fiber CV and (b) estimates of the rate of change of these variables in the biceps brachii muscle of healthy subjects during voluntary contractions sustained at different torque levels. This work is meant to provide a statistical basis for the investigation of functional muscle structure in normal and pathological subjects by means of surface EMG.
Section snippets
Experimental protocol
Ten healthy male subjects with age ranging from 23 to 43 years (average=30.2 years, std. dev.=6.1 years) participated in this evaluation after giving informed consent. Each subject laid on his back with the right dominant arm horizontal and abducted at 90°. The forearm was at 120° with respect to the arm. The arm and forearm were placed in an isometric brace equipped with two torque transducers (one on each side of the arm) and connected to a display which provided the subject with visual
Results
Table 1Table 2 show the results of the ICC analysis for MNF, ARV and CV. The ICC values reported in Table 1 indicate that MNF initial values are the most “reliable” parameters in the sense that they (a) are the most repeatable across experimental sessions and trials performed on the same subject and (b) are sensitive to individual differences between subjects. Initial values of ARV show higher ICC values at higher contraction levels. CV displays a very small inter-subject variability at 50% MVC
Discussion
The main issue discussed in this work is the repeatability of estimates of EMG signal variables during sustained isometric voluntary contractions of the biceps brachii. A secondary issue is the relationship between these estimates and the muscle contraction force. The first issue has been addressed in previous work, in the same as well as in different muscles but mostly in relation to electrically elicited contractions. The second issue has been discussed often but with limited statistical
Conclusions
The high quality of estimate of EMG variables in biceps brachii is probably due to the long and parallel fibers of the muscle and to the availability of sufficient space to place the EMG electrodes between the motor points and the tendon endings [42]. The inter-subject repeatability of estimates of CV obtained during voluntary contractions is even higher than that obtained from single twitch evoked contractions and with needles [15]. For this muscle, the estimates of CV are more reproducible
Acknowledgements
This work was supported by the European Concerted Action SENIAM, Camera di Commercio di Torino, Compagnia di San Paolo, Fondazione CRT di Torino, and Regione Piemonte. The data acquisition routines have been written by A. Granata, F. Laterza and M. Matacchione. The collaboration of M. Migliorini is gratefully acknowledged.
Alberto Rainoldi was born in Torino, Italy, on December 9, 1964 and graduated in Physics in 1991. He worked as a consultant in the industrial quality control field until 1995 by using neural network techniques. Since 1996 he is with Politecnico di Torino with a research fellowship. He works in the field of modeling and with clinicians to test surface EMG techniques both in normal and in pathological subjects. He has published two papers in International journals, several contributions in
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Cited by (0)
Alberto Rainoldi was born in Torino, Italy, on December 9, 1964 and graduated in Physics in 1991. He worked as a consultant in the industrial quality control field until 1995 by using neural network techniques. Since 1996 he is with Politecnico di Torino with a research fellowship. He works in the field of modeling and with clinicians to test surface EMG techniques both in normal and in pathological subjects. He has published two papers in International journals, several contributions in International congresses and two papers in National journals.
Giuseppe Galardi was born in Capaccio, Italy, on May 28, 1954. He received the MD degree in 1981 and the Neurology certification in 1985 at the University of Milan. Since 1984 he has worked in the Clinical Neurophysiology Department of the Scientific Institute San Raffaele of Milan, at the beginning as fellow (1984) then as assistant (1987) and now as vice-chairman (1997). He is currently in charge of the Electromyography service in the Department of Clinical Neurophysiology at the Institute San Raffaele of Milan and he is the Principal Investigator of the Department of Neuroscience's Movement Disorders Unit. His scientific work combines an intense clinical activity in neurophysiological diagnosis of neuromuscular diseases and movement disorders and a research activity in different neurological pathologies such as neuropathies, distonias and multiple sclerosis.
Luca Maderna was born in Como, Italy, on January 20, 1965. He received the MD degree in 1991 and Clinical Neurophysiology certification in 1996. Since 1992 he has worked at the Department of Clinical Neurophysiology of the Scientific Institute San Raffaele of Milan combining clinical application of ENG and EMG technique with Neurophysiological research. His research interests were focused on the electrophysiological study of the neuropathies and of chronic fatigue in MS patients. Currently his main research field is the clinical application of multielectrode surface electromiography in central and peripheral neurological diseases.
Giancarlo Comi was born in Carvico, Italy, on December 15, 1947. He received his MD degree from the Medical School of Milan University in 1973 and, from the same University, in 1977 he received the Neurological Certification. From 1974 he joined the Department of Neurology, Milan University, Scientific Institute H San Raffaele, as Assistent Professor in 1974, vice-Chairman of Dept. of Neurology in 1986 and Chairman of Dept. of Neurophysiology in 1996. His main research interests are related to Multiple Sclerosis, Peripheral Neuropathies, Clinical Neurophysiology.
Loredana Lo Conte graduated “summa cum laude” in Computer Science from the University of Torino, Italy. She has been a Visting Scientist at the NeuroMuscular Research Center in Boston, USA and at the MRC Laboratory of Molecular Biology in Cambridge, England. She is now at the Department of Biochemistry of the University College of London, England. Her research interests are in the field of pattern recognition, signal processing and, in general, computer science applied to biological problems.
Roberto Merletti graduated in Electronics Engineering from Politecnico di Torino, Italy and obtained the M.S. and the Ph.D. from the Ohio State University. He is Associate Professor of Biomedical Instrumentation at the Department of Electronics of Politecnico di Torino and at the Department of Biomedical Engineering of Boston University, and Director of the Laboratory for Neuromuscular System Engineering in Torino, Italy. His research focuses on surface electromyography, myoelectric signal processing, electrical stimulation and neuromuscular control.