Normalisation of gait EMGs: a re-examination
Introduction
The importance of normalising electromyograms (EMGs) has long been recognised by researchers and clinicians who record them during gait analysis (e.g. [27], [29], [35], [38]). Gait EMGs were first normalised [14] using a method that divided each point that constitutes the processed EMG by the peak value recorded from the same EMG. This method, subsequently referred to as the peak dynamic method, still appears to be popular among gait electromyographers (e.g. [19], [31]). A second and equally popular method, introduced by Dubo et al. [13], divided each data point included in the gait EMG by the peak EMG from an isometric maximal voluntary contraction (MVC) of the same muscle, which is usually performed in the middle of the range of motion. This method, subsequently referred to as the isometric MVC method, was later adopted by Arsenault et al. (e.g. [4]).
Yang and Winter [41] compared a number of normalisation methods in an attempt to establish which would provide a normal gait EMG template and, therefore, improve the use of electromyography as a diagnostic tool in gait analysis. Based on this rationale, the criterion for selecting the best method was the one that most reduced the inter-individual variability of ensemble averaged EMGs [41]. The peak dynamic method and the mean dynamic method (a similar but previously unpublished method that divided each data point within the gait EMG by the mean value recorded from the same EMG) were included in the comparison. Yang and Winter [41] noted that these two methods do not have the potential to provide any information on the degree of muscle activation that occurs during gait. The authors chose not to include the isometric MVC method in their comparison as they had previously [40] reported that EMGs from isometric MVCs displayed poor reliability. Instead, they also included a method that used the peak EMG from an isometric sub-maximal (50%) voluntary contraction of the same muscle as the denominator in the normalisation equation subsequently referred to as the sub-MVC method. Yang and Winter [41] discovered that the peak dynamic method and the mean dynamic method both reduced inter-individual variability in comparison to the un-normalised EMGs and those normalised by the sub-MVC method. As a consequence of this study, the mean dynamic method was adopted by Winter’s group (e.g. [39]) and a number of other researchers (e.g. [25], [28]). Further evidence that the mean dynamic method reduces inter-individual variability more than other normalisation methods was provided by Shiavi et al. [34], [35] who also compared the mean dynamic method with the peak dynamic method. They discovered that the mean dynamic method was slightly better at reducing inter-individual variability, particularly during periods of muscle quiescence, due to a relatively lower standard deviation during these periods. Based on this evidence, Shiavi et al. [34], [35] also advocated the use of the mean dynamic method particularly when wishing to distinguish between periods of muscle activity and inactivity during gait. However, more recently, Allison et al. [2] and Knutson et al. [23] both warned against using the mean dynamic method or peak dynamic method, although not specifically in gait analysis, as they may remove the true biological variation within a group.
By virtue of the nature of the denominator in its normalisation equation, the isometric MVC method is the only one that has the potential to reveal how active a muscle is during gait. Despite criticism by Yang and Winter [41], the isometric MVC method continues to be used in gait analysis (e.g. [7], [12]). However, despite continued use, only Dubo et al. [13] have questioned the suitability of using the EMG from an isometric MVC to normalise gait EMGs, which are clearly recorded during non-isometric contractions. Only a small number of studies have investigated the suitability of using the isometric MVC method to normalise EMGs from non-isometric tasks. Mirka [24] normalised EMGs recorded from sub-maximal isokinetic contractions of the trunk flexor and extensor muscles. Relatively large differences (15–50%) were reported between the isometric MVC method and a method that normalised the task EMGs using EMGs from isometric MVCs performed at the same trunk angle that occurred during the task. In contrast, Knudson and Johnston [22] later reported average absolute differences of less than 7% between the same two methods when used to normalise lower limb muscle EMGs recorded during standing from a seated position. Furthermore, Kellis and Baltzopoulos [21] were the first authors to use EMGs from isokinetic MVCs that had the same muscle action (i.e. concentric or eccentric), joint angle and joint angular velocity as the task EMG as the denominator in the normalisation equation. They discovered a significantly greater (P<0.05) normalised muscle activation amplitude from this method, subsequently referred to as the isokinetic MVC method, when compared to the isometric MVC method when both were used to normalise EMGs from knee flexors and extensors when acting as antagonists during isokinetic MVCs. However, biceps brachii EMGs recorded during isotonic elbow flexions and extensions were not significantly different (P=0.315) when normalised by the isometric MVC method and the isokinetic MVC method [5]. Further comparisons between the isometric MVC method and the isokinetic MVC method are warranted as some researchers have reported that peak EMGs from the knee extensors are greater during concentric MVCs than during either eccentric (e.g. [32], [37]) or isometric (e.g. [6]) MVCs. Alternatively, Ghori et al. [17] and Amiridis et al. [3] demonstrated no difference in peak EMG between different muscle actions. Furthermore, a number of researchers (e.g. [3], [6], [37]) have reported that the amplitude of EMGs from knee extensor muscles increased, rather than remaining constant, as the velocity of the isokinetic dynamometer’s lever arm increased during concentric MVCs.
Section snippets
Aims
Based on the above evidence, the general opinion provided by gait related review articles is that the peak dynamic method or, preferably, the mean dynamic method should be used if the aim of the analysis is to reduce inter-individual variability and produce a general gait-EMG template (e.g. [33], [38]). Alternatively, the isometric MVC method is recommended when the goal is to ascertain the level of muscle activity that is required to walk (e.g. [9], [10], [29]). However, these opinions are not
Participants
Ten males ((mean±SD) age 31.7±5.9 years; height 1.81±0.04 m; mass 80.0±12.2 kg) and two females (age 34.5±2.1 years; height 1.65±0.01 m; mass 61.0±1.4 kg) took part in the investigation after reading and signing an informed consent form. All participants were regularly involved in activities that exercised their quadriceps and hamstrings and had no known gait pathology.
Experimental design
To enable EMGs recorded from lower limb muscles during gait to be normalised by the isometric MVC method and the isokinetic MVC
Intra-individual ensemble averages
Gait EMGs normalised by the isometric MVC method and isokinetic MVC method are shown, for one individual, in Fig. 2, Fig. 3, respectively. The output of both of these methods revealed that gait EMGs were generally less than 20% of the amplitude recorded from MVCs. Some sections of the ensemble averages in Fig. 3 are missing as they could not all be normalised using the isokinetic MVC method. These gaps occurred because not all the maximum lengthening velocities experienced during gait were
Discussion
The overall aim of this investigation was to re-evaluate the three methods that have commonly been used to normalise EMGs recorded during normal gait, and to compare them with the isokinetic MVC method that has not previously been used in gait analysis. The outputs of both the mean dynamic and peak dynamic normalisation methods only serve to inform the researcher or clinician about the level of activity displayed by a muscle throughout the gait cycle in relation to the average and maximum
Conclusion
The isokinetic MVC method resulted in EMGs that had greater intra-individual variability, and were therefore less reliable, than un-normalised EMGs or those normalised by the mean dynamic, peak dynamic or isometric MVC methods. The findings of this investigation also agree with previous research [23], [34], [35], [41] that the dynamic methods, and in particular the mean dynamic method, yield the most homogeneous templates of muscle activity during gait. This is noteworthy as the variance ratio
Acknowledgements
The first author would like to acknowledge the assistance of David Clark in matching gait EMGs with those recorded from MVCs.
Adrian Burden received a B.Sc. degree in sports science from Crewe and Alsager College (1987), a masters from the University of Salford (1991) and a Ph.D. from the University of Brighton (2002). He has held lecturing positions in biomechanics at Brunel University and the University of Brighton, and is currently course leader for the sport, exercise and coaching science degree in the Department of Exercise and Sport Science at Manchester Metropolitan University. His main research interests are
References (41)
- et al.
EMG signal amplitude normalization technique in stretch-shortening cycle movements
Journal of Electromyography and Kinesiology
(1993) - et al.
Normalisation of EMG amplitude: an evaluation and comparison of old and new methods
Medical Engineering & Physics
(1999) - et al.
A gait analysis data collection and reduction technique
Human Movement Science
(1991) - et al.
The effects of signal conditioning on the statistical analyses of gait EMG
Electroencephalography and clinical Neurophysiology
(1994) - et al.
Relationship between torque and EMG activity of a knee extensor muscle during isokinetic concentric and eccentric actions
Journal of Electromyography and Kinesiology
(1995) - et al.
Surface vs. fine-wire electrode ensemble-averaged signals during gait
Journal of Electromyography and Kinesiology
(1995) - et al.
The effects of normalization method on antagonistic activity patterns during eccentric and concentric isokinetic knee extension and flexion
Journal of Electromyography and Kinesiology
(1996) - et al.
A study of various normalization procedures for within day electromyographic data
Journal of Electromyography and Kinesiology
(1994) - et al.
Bilateral electromyographical analysis of the lower limbs during walking in normal adults
Electroencephalography and Clinical Neurophysiology
(1989) - et al.
EMG profiles during normal human walking: stride-to-stride and inter-subject variability
Electroencephalography and Clinical Neurophysiology
(1987)
Reliability of measurements of muscle strength and voluntary activation using twitch interpolation
Muscle and Nerve
Co-activation and tension regulating phenomena during isokinetic knee extension in sedentary and highly skilled humans
European Journal of Applied Physiology
How many strides are required for the analysis of electromyographic data in gait?
Scandinavian Journal of Rehabilitative Medicine
Evaluation of moment–angle curves in isokinetic knee extension
Medicine and Science in Sports and Exercise
An electromyographic analysis of the knee during functional activities—I. The normal profile
The American Journal of Sports Medicine
Analysis of gait
Gait data: reporting, archiving and sharing
An interactive graphics-based model of the lower extremity to study orthopaedic surgical procedures
IEEE Transactions on Biomedical Engineering
Electromyographic analysis of selected lower extremity musculature in normal subjects during ambulation with and without a ‘protonics’ knee brace
Journal of Orthopaedic and Sports Physical Therapy
Electromyographic temporal analysis of gait: normal human locomotion
Archives of Physical Medicine and Rehabilitation
Cited by (0)
Adrian Burden received a B.Sc. degree in sports science from Crewe and Alsager College (1987), a masters from the University of Salford (1991) and a Ph.D. from the University of Brighton (2002). He has held lecturing positions in biomechanics at Brunel University and the University of Brighton, and is currently course leader for the sport, exercise and coaching science degree in the Department of Exercise and Sport Science at Manchester Metropolitan University. His main research interests are the processing and normalisation of electromyograms, and the biomechanics of low back pain.
Marion Trew began her career as a clinical physiotherapist working both in the UK and in Thailand. In 1976, she became a lecturer in physiotherapy at Coventry Polytechnic and in 1989 moved to the University of Brighton to set up occupational therapy and physiotherapy education. Her current research focusses on aspects of exercise and rehabilitation, and includes two projects on exercise in people of retirement age and one related to exercise and Parkinson’s disease.
Vasilios Baltzopoulos received a B.Sc. degree in sports and exercise science from the Aristotelian University of Thessaloniki in Greece and a masters (1988) and Ph.D. degree (1991) from the University of Liverpool in England. He has held positions as lecturer in biomechanics at the University of Liverpool, reader in biomechanics at the Manchester Metropolitan University (MMU) and associate professor of biomechanics at the University of Thessaly in Greece. He is currently a professor of musculoskeletal biomechanics at the Centre for Biophysical and Clinical Research into Human Movement at MMU. His main research interests are measurement and modelling of joint and muscle function and biomechanical data modelling and processing techniques used in inverse dynamics applications.