Influence of the subcutaneous fat layer, as measured by ultrasound, skinfold calipers and BMI, on the EMG amplitude
Surface electromyography (sEMG) is an important tool to estimate muscular activity at work. There is, however, a great inter-individual variation, even in carefully standardized work tasks. The sEMG signal is attenuated in the subcutaneous tissues, differently for each subject, which requires normalization. This is commonly made in relation to a reference contraction, which by itself, however, introduces a variance. A normalization method that is independent of individual motivation, motor control and pain inhibition would be desirable. The aim of the study was to explore the influence of the subcutaneous tissue thickness on sEMG amplitude. Ultrasound measurements of the muscle to skin surface distance were made bilaterally over the trapezius muscle in 12 females. Skinfold caliper measurements from these sites, as well as from four other sites, were made, body mass index (BMI) was recorded, and sEMG was recorded at maximal and submaximal contractions. The muscle–electrode distance, as measured by ultrasound, explained 33% and 31% (on the dominant and non-dominant sides respectively) of the variance of the sEMG activity at a standardized submaximal contraction (average between the sides, 46%); for maximal contractions the explained variance was 21%. Trapezius skinfold measurements showed poor correlations with sEMG. Instead, the mean of skinfold measurements from other sites explained as much as 68% (submaximal contraction). The corresponding figure for BMI was 67%. In conclusion, skinfold thickness explains a major part of the inter-individual variance in sEMG amplitude, and normalization to this measure is a possibility worth further evaluation.
KeywordsBody mass index Electromyography Ultrasonography Skinfold thickness
Work-related musculoskeletal disorders constitute a widespread problem, associated with much suffering for individuals, as well as high costs for employers and society (Norlund et al. 2000; SBU The Swedish Council on Technology Assessment in Health care 2000). To accomplish effectual interventions in workplaces, the pathogenetic mechanisms underlying the development of these disorders need to be clarified. In this aspect, an important research issue is a correct and relevant characterization of the physical workload. Muscle pain can be related to overload, and in this condition it is mainly located in the musculotendinous region (Ranney et al. 1995). For this reason, assessing the amount of muscular activity at work is of great interest. Surface electromyography (sEMG) is widely used as a tool to describe muscle activation (Hermens et al. 1997; Rempel 1998). Namely, it has been shown that sEMG amplitude can be representative of neuromuscular activation (Basmajian and Luca 1979).
Analyses of sEMG results reveal a large inter-individual variation, which is present even among subjects performing exactly the same task (Balogh et al. 1999). This variation is caused by differences in the thickness and electrical properties of the tissue layers between surface electrodes and muscles, as well as in muscle size, electrode size and position (De Luca 1979; Stegeman et al. 2000). In order to cope with the above-cited limitations, sEMG recordings are commonly normalized to the sEMG amplitude obtained during a standardized contraction. This normalization can basically be made in two different manners (Mathiassen et al. 1995): using a maximal voluntary contraction (MVC) will give the results in relation to the individual maximal capacity, while using a submaximal reference voluntary contraction (RVC), with a standardized submaximal load, relates the recorded values to an external load. Depending on the object of a particular study, one or the other normalization procedure might be preferred.
However, the reference contractions by themselves introduce a variance (Mathiassen et al. 1995). The MVC may be potentially biased due to lack of motivation or pain inhibition in affected subjects. The latter is particularly troublesome when comparing exposure between healthy and affected subjects. The RVC might be biased by differences in motor control, since the same motion and force can be accomplished using different muscles (Palmerud et al. 1998). Thus, even when reference contractions are used for normalization, a large inter-individual variation remains.
Due to these circumstances, it would be desirable to find a normalization method that is independent of individual performance, and instead focuses on the other main source of inter-individual variability; the muscle–electrode inter-space. In paraspinal muscles as much as 81% of the variance in sEMG amplitude at a submaximal reference contraction has been explained by variation in the localized skinfold thickness, measured with calipers (Hemingway et al. 1995). It is not known whether this is also true for other muscles. Further, an even better method for measuring the muscle–surface distance would be ultrasound. A less precise, but much easier method for estimating subcutaneous tissue thickness is body mass index (BMI) (Heitmann 1990).
The aim of this study was to explore the influence of the electrode–muscle distance, as measured by ultrasound as well as skinfold calipers and BMI, on sEMG amplitude of the trapezius muscle.
Age and anthropometric measures for 12 female subjects. Mean values and standard deviations (SD) are given
Body Mass Index (m/kg2)
Muscle-surface distance by ultrasound (mm)
Other four sites, average
During the 3 years that had passed, four had developed neck-shoulder pain, but only one of them was diagnosed with tension neck syndrome at a standardized physical examination (Ohlsson et al. 1994).
The Ethics Committee of Lund University approved the study, and all participants gave their informed consent.
The distance between skin surface and muscle belly was derived using ultrasound equipment with a linear array probe and a frequency of 12 MHz (Logiq 700, GE OEC Medical Systems, Salt Lake City, Utah, USA). The subject was lying in a prone position, with the arms forwards resting on the bed. The probe was stabilized by the examiner; no extra pressure was applied. Ultrasound recordings were made bilaterally over the descending part of the trapezius muscle, 2 cm lateral to the midpoint of the line joining the 7th cervical vertebra and the acromion, marked by a permanent marker pen. Three measurements were made on each side, and the mean value was calculated. There was little variance between the repeated measurements; mean coefficient of variation 4% (SD 2%).
To assess the thickness of the subcutaneous tissue we used skinfold calipers (Harpenden, British Indicators, West Sussex, UK) (Durnin and Rahaman 1967; Durnin and Womersley 1974). Measurements were made at four different sites, on the right side of the body, according to the manufacturer's manual. Folds were thus taken over the anterior surface of the biceps, on the posterior midline of the upper arm, below the scapulae and above the crest of the ilium. The mean value of these four skinfold measurements was used for further analyses.
Additionally, skinfold was measured bilaterally over the trapezius muscle at the same point that was used for the ultrasound recordings. Since there was no standard technique we used a rather small pinch grip and a larger fold.
Further, all subjects were weighed and the body mass index (BMI) was calculated as weight (kg)/height (m)2.
Surface electromyography (EMG)
Electrode positioning was carefully determined in order to avoid errors in sEMG recordings, i.e. due to the end plate region.(Jensen et al. 1993; Mathiassen et al. 1995). Bipolar sEMG measurements were performed over the same region used for ultrasound and skinfold measurements, using Ag/AgCl surface electrodes with a centre-to-centre distance of 20 mm, and an active electrode diameter of 6 mm (Åkesson et al. 1997). The signals were amplified, filtered, and stored in a portable data logger with a 12-bit analogue-to-digital converter, sampling rate 1024 Hz (Hansson et al. 2003). EMG data were sent to a personal computer for off line analyses. The root mean square (RMS) value, calculated for epochs of 1/8 s, was used to characterize muscular electrical activity after subtracting the noise level (Hansson et al. 1997).
The noise level was recorded under resting conditions. The subject was instructed to stand up with her arms hanging down along her sides for 30 s, trying to relax the shoulder muscles, and thereafter to sit down on a chair and relax. An oscilloscope showed the signal recorded, and could be used for biofeedback. The lowest level recorded was then considered to be the noise level. The median noise level for the dominant trapezius muscle was 1.1 μV, for the non-dominant 1.3 μV.
The submaximal reference voluntary electrical activity (RVE) was obtained in a standing position. One arm at a time was elevated to 90° in the scapular plane, and the subject held a dumbbell of 1 kg, with a straight elbow and the dorsal side of the hand upwards, for 10 s.
The maximal voluntary electric activity (MVE) was determined during three maximal voluntary contractions (MVC) performed in the same position as for RVE (Schüldt and Harms-Ringdahl 1988). A strap, connected to a force transducer anchored to the floor, was placed just proximal to the elbow, and the subject was instructed to pull as hard as possible without jerking for 3 s. Maximum exerted force was recorded by the force transducer. A skilled instructor supervised the calibration. Any incorrectly performed trial would thereby be discovered and, if present, excluded from the data. The computer thereafter selected the highest level recorded.
Muscular force and surface electromyographic (sEMG) activity for 12 female subjects. Mean values and standard deviations (SD) are given
Maximal voluntary contraction (N)
Voluntary EMG activity (µV)
Submaximal Reference (RVE)
Maximal Reference (MVE)
The grand average of the four standard sites was 19 (SD 4.4) mm (Table 1), which correlated highly with BMI (r=0.93; p<0.001).
Skinfold thickness of the trapezius on the dominant side was on average 19 (SD 4.3) mm for the small grip (Table 1) and 27 (6.0) mm for the large one (not shown). The correlation between the grips was surprisingly low (r=0.40; p=0.2). On the non-dominant side, the corresponding measures were 19 (SD 2.8) mm and 26 (6.6) mm, respectively (r=0.54; p=0.07). For both sides, the correlation with the ultrasound measurements was rather poor, and non-significant (p>0.05). Furthermore, the average values for the two sides were not significantly related to BMI or to the mean ultrasound values obtained from the two sides. Since the results below were similar for both grips, only those for the small one are reported. Thus, the attempt to measure skinfold directly over the trapezius gave very inconsistent values, and seemed not to be successful. This was possibly due to differences in tissue consistency and adherence between subjects, which made skinfold measurements more difficult.
The average MVE was 780 (SD 220) μV on the dominant side, and 770 (230) µV on the non-dominant side (r=0.68; p=0.01) (Table 2). For the RVE, a mean value of 150 (SD 50) μV, corresponding to 19 (5.1)% of MVE was recorded on the dominant side, 160 (SD 51) μV and 21 (5.3)% on the non-dominant side (r=0.53; p=0.08).
Influence of subcutaneous fat layer on EMG activity
Regression analyses for age, maximal voluntary contraction (MVC), body mass index (BMI), skinfold measurements over the trapezius muscle and as an average of four other standard sites, and muscle–surface distance measured by ultrasound, compared to recorded EMG amplitude at MVC (MVE), and at a submaximal reference contraction (RVE), on the dominant and non-dominant trapezius. For each side separately, as well as the average for both sides, explained variance (r2) is shown for 12 female subjects
As expected, EMG amplitude decreased as a function of increasing muscle–electrode distance, both during maximal and submaximal contraction. Unexpectedly, though, the agreements between EMG amplitude and measurements by either ultrasound or skinfold calipers at the electrode location was rather poor, while the mean value of the skinfold measurements at four standardized other sites, as well as BMI, showed good correlations.
Ultrasound measurements of the muscle–electrode distance were assumed to give the best correlations with the EMG amplitude variation; however, this was not the case. This is consistent with skinfold measurements giving a more precise quantification of subcutaneous body fat than ultrasound measurements, when using computed-tomography as the gold standard (Orphanidou et al. 1994). Further, it indicates that not only the distance but also the electrical properties of the subcutaneous tissue are of great importance for the attenuation of the EMG signal. Body fluid is a good conductor, and the proportion between fat and fluid varies between individuals. Thus, since fluid is not expected to substantially attenuate the EMG signal, a method that only quantifies fat content could be a better estimate of tissue attenuation. Skinfold calipers compress the tissue, conceivably moving the extracellular fluid, which might be of importance, as it seems that this compressed tissue distance gave a better estimate of the attenuation.
Though the thickness of the muscle fascia was not measured, it was obvious from the ultrasound images that it differed between subjects. Further, in ultrasound and conductivity measurements, fibrous membranes have been found, dispersed through the adipose tissue (Booth et al. 1966; Volz and Ostrove 1984), and they can be detected from the ultrasound pictures (Fig. 1). Such membranes will also attenuate the EMG signal. Hence, a varying composition of the subcutaneous tissue will give different attenuations of the electrical signal at identical values of thickness. The importance of considering the material properties of the subcutaneous tissue layer has also been emphasized by Lowery et al. (2002).
An attempt to measure skinfold thickness directly over trapezius was not successful. This is most probably because the adherence of, and the possibility to grasp, the subcutaneous tissue at that site varied from subject to subject.
The average value from other sites gave a surprisingly good agreement with the EMG signals. At the four standard sites, skin and tissues are mobile, making them easier to grasp. The thickness of the subcutaneous fat layer is correlated between different sites. Thus, though it was not possible to measure the skinfold thickness above trapezius adequately, the mean of the standard measurements seemed to give a reasonably good estimate of this thickness.
BMI is a rather rough estimate of the subcutaneous fat, since it also includes intra-abdominal fat, muscle mass and other tissues. Furthermore, it showed a good agreement with EMG as did the mean of the skinfold measurements. This is not surprising, since these two measures were very highly correlated. However, it is not necessarily true for other groups, e.g. athletes with a large muscle mass, or obese subjects with weaker muscles.
The EMG amplitude decreases with distance between electrodes and muscle, according to a power function (Roeleveld et al. 1997). For this reason, as regards amplitude–distance correlations, fit to a power curve was also calculated. However, this did not significantly influence the results.
There is no reason why the thickness of the subcutaneous tissue should differ between the sides (Gwinup et al. 1971), and there was no systematic difference in strength between the dominant and the non-dominant arm. Thus, the improved agreement when using the averages between the dominant and non-dominant sides, for EMG amplitudes as well as ultrasound and skinfold measures, is probably caused by a reduction of random errors introduced by this procedure.
For all three different estimates of subcutaneous tissue amount, the agreement with EMG amplitude was better for the submaximal contractions than for the maximal ones, which might indicate that a low-level standardized contraction gives rise to a more "standardized" EMG signal from the muscle. It is possible that pain inhibition or deficient motivation influences the maximal contraction, giving a more varied signal.
To sum up, a large part of the inter-individual variance in EMG amplitude can be explained by the amount and properties of the subcutaneous tissue that separates the muscle and the electrode. This can be measured either by BMI or, as argued above, more reliably by skinfold calipers. Hence, it might be possible to elaborate a normalization method that is independent of the individual performance in reference contractions. However, how to consider the subcutaneous fat layer in normalizing surface EMG needs further evaluation. If a new method is suggested, it must be evaluated by comparing the inter-individual variance obtained in subjects performing identical work tasks, to the corresponding variances obtained by using reference contractions.
This study was supported by grants from the Swedish Medical Research Council, the Swedish Council for Work Life Research (including Change@Work), the Swedish National Institute of Working Life (Co-operative for Optimization of industrial production systems regarding Productivity and Ergonomics; COPE), the Swedish Council for Planning and Coordination of Research, AFA Insurance, the Medical Faculty of Lund University and the County Councils of Southern Sweden.
- Basmajian JV, Luca CJd (1979) Muscles alive. Their functions revealed by electromyography. Williams and Wilkins, Baltimore, Md.Google Scholar
- Hansson G-Å, Asterland P, Skerfving S (1997) Acquisition and analyses of whole-day electromyographic field recordings. In: Hermens HJ, Hägg G, Freriks B (eds) Proceedings of the second general SENIAM (Surface EMG for Non Invasive Assessment of Muscles) workshop. Roessing Research and Development, Stockholm, Sweden, pp 19–27Google Scholar
- Hansson G-Å, Asterland P, Kellerman M (2003) Modular data logger system for physical workload measurements. Ergonomics 46:407–415Google Scholar
- Hermens HJ, Hägg G, Freriks B (1997) Proceedings of the second general SENIAM workshop. European applications on surface electromyography, Roessingh Research and Development, Stockholm, SwedenGoogle Scholar
- Jensen C, Vasseljen O, Westgaard RH (1993) The influence of electrode position on bipolar surface electromyogram recordings of the upper trapezius muscle. Eur J Appl Physiol 67:266–273Google Scholar
- Norlund A, Pålsson B, Ohlsson K, Skerfving S (2000) Economic consequences of occupational disorders in women with repetitive industrial work. Eur J Publ Health 10:127–132Google Scholar
- Rempel D (1998) Estimating muscle load using surface EMG amplitude. Marconi Research Conference, University of California, MarshallGoogle Scholar
- SBU (2000) Pain in the back and neck. An evidence based compositon of knowledge [in Swedish]. SBU The Swedish Council on Technology Assessment in Health care, StockholmGoogle Scholar
- Schüldt K, Harms-Ringdahl K (1988) Activity levels during isometric test contractions of neck and shoulder muscles. Scand J Rehabil Med 20:117–127Google Scholar