Reproducibility of surface EMG variables and peak torque during three sets of ten dynamic contractions

Journal of Electromyography and Kinesiology 9 (1999) 351–357 www.elsevier.com/locate/jelekin

Reproducibility of surface EMG variables and peak torque during three sets of ten dynamic contractions Barbro Larsson a, Bjarne Månsson a, Christian Karlberg a, Peter Syvertsson a, Jessica Elert a, Bjo¨rn Gerdle b,* b

a Faculty of Health Sciences, Linko¨ping, Sweden Pain and Rehabilitation Centre, University Hospital, Linko¨ping, Sweden

Received for publication 2 March 1999

Abstract The interpretation of the electromyogram (EMG) of dynamic contractions might be difficult because the movement per se introduces additional factors that could affect its characteristics. There is a lack of studies concerning the reproducibility of surface EMG registrations during dynamic contractions. The aim was to investigate the during-the-day reproducibility (using intra-class correlation; ICC) of the peak torque (PT) and the EMG variables (without removing the electrodes) of dynamic contractions. Ten healthy subjects performed three sets of 10 dynamic maximum right-knee extensions with a one-hour interval in between, using an isokinetic dynamometer and the PT was determined. EMG signals were recorded from the right vastus lateralis, rectus femoris and vastus medialis muscles using surface electrodes and the mean frequency of the power spectrum (MNF [Hz]) and the signal amplitude (RMS [␮V]), were computed. The ability to relax in-between the maximum extensions was calculated as a ratio of the RMS during the passive flexion phase and the RMS during the active extension phase of each contraction cycle: the signal amplitude ratio (SAR). Both PT (ICC ⫽ 0.99) and RMS (ICC ⫽ 0.83–0.98) had good reproducibility. The reproducibility of MNF was good for all muscles when the mean of contraction nos.: 1–10 was used. Vastus lateralis had the highest ICC among the three muscles. The reproducibility of SAR was generally poor (ICC ⬍ 0.60). The present study showed good reproducibility for common EMG variables (MNF and RMS) obtained during maximum isokinetic contractions.  1999 Elsevier Science Ltd. All rights reserved. Keywords: EMG; Human; Mean frequency; Peak torque; Quadriceps; Reproducibility; Reliability; RMS; Signal amplitude

1. Introduction Isokinetic dynamometers are commonly used for assessment of dynamic muscle strength, endurance and fatigue. Peak torque (PT) is the favoured biomechanical variable used to assess muscle performance. The reproducibility (in this context also labelled reliability by some authors) of the assessment is crucial for the interpretation of research findings and has been investigated in several studies on isokinetic dynamometry [1,7]. For measurement of reproducibility, intra-class correlation (ICC) is preferred instead of Pearson’s correlation coefficient (r) due to the fact that the latter is not sensi-

* Corresponding author. Tel.: ⫹ 46-13-221574; fax: ⫹ 46-13224465; e-mail: [email protected]

tive to factors such changes in means and standard deviations [3,4] and it will tend to overestimate the reproducibility [5]. ICC varied between 0.93 and 0.99 when isokinetic knee extensions were performed on three consecutive days [6]. When reproducibility was investigated in a reciprocal protocol, knee extension-knee flexion at two different angular velocities on three different days, the ICC ranged between 0.85 and 0.98 for knee extension and 0.88–0.97 for knee flexion in a single measurement [2]. The electrical activation of the muscle tissue during voluntary contractions can be registered using surface electromyography (EMG). Root mean square (RMS) and mean frequency (MNF) or median frequency (MDF) are commonly used to describe the signal energy and the frequency content of the signal, respectively. The behaviour of the surface EMG during various protocols of

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fatigue has been extensively investigated generally during static sustained contractions [8–10]. Peripheral muscle fatigue during sustained static contractions is generally characterised by increases in signal energy (RMS or iEMG) and shifts in the EMG spectrum towards lower frequencies (spectral shift) [8,11]. EMG registrations during static contractions are generally considered as reproducible (mainly studies of the signal amplitude) [12–17]. However, there is a lack of studies of the reproducibility of surface EMG registrations during dynamic (isokinetic) contractions. Despite this lack of studies a number of studies have been published that have investigated the EMG power spectrum during dynamic exercise: for instance ergometer cycling, running and isokinetic dynamometer exercise, for references see [10,18– 20]. As pointed out by Potvin [10] the interpretation of the EMG from dynamic contractions might be difficult— especially for frequency spectrum variables—because the movement per se introduces additional factors that might affect its characteristics; for instance changes in force throughout the range of motion, changes in fibre and muscle length, movement of the neuromuscular junction with relation to the electrodes position, problems with non-stationary of the signal etc. From static contractions it is known that such factors significantly influence the MNF [21]. It is also well known from static contractions that the electrodes can affect the reproducibility of EMG [8]. Even though repeated tests in clinical practise and research generally involve removal of electrodes it is important, as a first step of investigating the reproducibility of EMG from dynamic contractions, to evaluate how other factors affect the reproducibility. If acceptable reproducibility is achieved then the next step will include removal of the surface electrodes. Hence, the aim of this study was to investigate the during-theday reproducibility (three sets (tests) of ten contractions each) of peak torque and EMG variables (without removal of electrodes) during isokinetic knee extensions. 2. Subjects and methods 2.1. Subjects Ten clinically healthy (no relevant disease) subjects (five men and five women) volunteered in the present study (Table 1). None of them was engaged in regular Table 1 Anthropometric data for the ten subjects (mean values ⫾ one standard deviation) Variable

All subjects (N ⫽ 10) Men (N ⫽ 5) Women (N ⫽ 5)

Age (years) 46 ⫾ 6 Height (cm) 173 ⫾ 9 Weight (kg) 74 ⫾ 15

44 ⫾ 9 179 ⫾ 7 84 ⫾ 12

48 ⫾ 2 167 ⫾ 6 63 ⫾ 9

athletic activities during leisure. Each subject gave informed consent. 2.2. Methods All subjects performed three sets of 10 dynamic maximum right-knee extensions with a one-hour interval in between, using an isokinetic dynamometer (Kin-Com 500H, Chattecx Corporation, Tennessee, USA). Subjects were secured by body straps (pelvic and femoral strapping) and seated comfortably in the dynamometer chair. Before the test started the subjects practised at sub-maximal contraction levels and thereafter they rested for several minutes in a sitting position. Each subject performed a series of 10 repetitive isokinetic knee extensions of the right leg from 90° of flexion to 15°. The dynamometer was motor driven at a constant velocity of 90° s−1. The velocity 90° s−1 was chosen after taking into consideration the results from recent studies investigating the relationships between EMG-variables and mechanical output at different angular velocities [22]. Subjects were encouraged to perform maximally for each contraction throughout the full range of motion (the active phase of the contraction cycle (0.83 s)). Visual feed back was also given using the screen of the computer of the dynamometer. The subjects relaxed as the dynamometer arm moved back to 90° (the passive phase of the contraction cycle (0.83 s)). Each contraction cycle took 1.66 s and no rest were allowed between each contraction cycle. The contraction frequency was thus standardised. EMG signals were recorded from the right vastus lateralis, rectus femoris and vastus medialis muscles using surface electrodes that were positioned prior to the investigation and were not removed between the three tests. The skin was first dry shaved and then cleaned with an alcohol and ether solution (4:1). Each subject performed a short static knee extension and two recording silverchloride electrodes (Medicotest, Ølstykke, Denmark) for each muscle, abraded with redux paste (Medicotest, Ølstykke, Denmark), were placed 20 mm apart (centre to centre distance) on the skin over the most prominent bulge of the muscle [9]. A bipolar multi-channel EMG amplifier (EMGAmp, Braintronics BV ISO-2104, Almere, the Netherlands) was used to register the surface EMG activity. The signals were sampled with a frequency of 2 kHz and analogue-to-digital converted with 12-bit accuracy in the signal range ⫾ 5 V. A 500 Hz analogue low-pass filter was used to eliminate aliasing of the sampled EMG signals. The antialiasing filter used was a fourth Butterworth filter with a cut-off frequency of 500 Hz. A 40 Hz low-pass filter was used for the torque and position signals [23]. A high-pass filter of 16 Hz was used to avoid the influence of movement artefacts and low-frequency noise of the EMG signal. The mean frequency

B. Larsson et al. / Journal of Electromyography and Kinesiology 9 (1999) 351–357

of the power spectrum (MNF [Hz]), and the signal amplitude (root mean square (RMS [␮V]), were computed from the EMG signal for both phases of the contraction cycle (extension and flexion (relaxation) phases). The power-density spectrum was obtained, after Hamming windowing, using the Fourier transform (FFT) technique. To yield a spectral resolution of approximately 2 Hz, a 1024 point FFT was selected. The ability to relax in-between the maximum knee extensions was calculated as the ratio of the RMS during the passive flexion phase and the RMS during the active extension phase of each contraction cycle: the signal-amplitude ratio (SAR). A high SAR means a high activity during the passive knee flexions and thus an inability to relax. For details concerning the data acquisition system for registration and analysis see Karlsson et al. [23]. The following variables from the test have been used in the analysis: Peak torque variables: Peak torquemax: the highest value of the ten contractions (Nm), Peak torquemean: mean of peak torque of contraction nos. 1–10 (Nm) and Peak torqueend: mean of contraction nos. 8–10 (Nm). MNF variables: MNFmax: mean frequency of the EMG (Hz) of the contraction corresponding to peak torquemax, MNFmean: mean of mean frequency of the EMG (Hz) of contraction nos. 1–10 and MNFend: mean of the mean frequency of the EMG (Hz) of contraction nos. 8–10. RMS variables: RMSmax: RMS (␮V) of the contraction corresponding to peak torquemax, RMSmean: mean of RMS (␮V) of contraction nos. 1–10 and RMSend: mean of RMS (␮V) of contraction nos. 8–10. SAR variables: SARmax: SAR of the contraction corresponding to peak torquemax, SARmean: mean of SAR of contraction nos. 1–10 and SARend: mean of SAR of contraction nos. 8–10. 2.3. Statistical analysis All statistics were performed using the statistical packages SPSS for Windows (version 7.5) and MATLAB 5.1 (Mathworks) (i.e. the statistical toolbox). In tables and text, mean values ⫾ one standard deviation ( ⫾ 1 SD) have been presented. Three different sets of parameters were all tested for reproducibility. Besides using the mean values of contraction nos. 1–10 (indicated with the suffix: mean), we also used the parameter values from the contraction where the test person achieved maximum peak torque (indicated with the suffix: max), and the mean of the 8th, 9th, and 10th contraction (indicated with the suffix: end). Using repeated-measures analysis of variance intra-class correlation (ICC; version 3,1 with three raters) was determined as the estimator of test-retest reproducibility [24–26]. The ICC

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(version 3.1 with three raters) was calculated by implementing the algorithm described by Shrout and Fleiss [26] and Rankin and Stokes [25] into MATLAB. (An alternative could have been to use ICC (version 3.1) with one rater, but we have chosen a conservative approach with the purpose of reducing possible influences from the acquisition system (for instance due to changed chemical relations between skin, gel and electrode)). The ICC algorithm generally returns a value between 0 and 1, where 0 stands for no reproducibility and 1 for perfect reproducibility. Sometimes a negative ICC can occur; this means that the within-subject variance exceeds the between-subjects variance (i.e. no reproducibility (ICC ⫽ 0)). Following Sleivert and Wenger [27] the characterisation of ICC was made as follows: good reproducibility: 0.80–1.0, fair reproducibility: 0.60–0.79 and poor reproducibility: ⬍ 0.60. Currier [28] has suggested that an ICC value > 0.8 is acceptable for clinical work. One-way ANOVA was used to test if differences existed between the three tests. P ⱕ 0.05 has been considered as significant in all statistical tests. 3. Results No significant differences between the three tests were found for any of the variables under investigation (Tables 2–4). Peak torque had high reproducibility (0.99) (Tables 2–4). No marked differences in ICC were found for the EMG variables for the three test circumstances (i.e. max, end or mean) except for SAR. Rectus femoris generally had lower ICC than the two other muscles for all EMG variables determined. RMS generally had somewhat higher ICC than the MNF and the reproducibility of RMS was good according to the defined criteria. ICC of MNFmean varied between 0.83–0.93; corresponding figures for MNFmax and MNFend were 0.74–0.87 and 0.77– 0.88, respectively. The reproducibility was good (ICC > 0.80) for all muscles when the mean of contraction nos.: 1–10 was investigated. Vastus lateralis had the highest ICC among the three muscles (0.84–0.87; i.e. good reproducibility). Vastus medialis had good reproducibility except for the maximum contraction (0.79). ICC of SAR was highest for the situation when we used the mean of the ten contractions (Table 2). SAR of vastus lateralis had the highest ICC (0.57–0.82) among the three muscles. The reproducibility of SAR was generally poor (ICC ⬍ 0.60) according to the defined criteria. 4. Discussion Important findings of the present study were the relatively high ICC (i.e. generally good reproducibility) of

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Table 2 Mean values ⫾ one standard deviation ( ⫾ 1SD) for the three tests of the ten subjects (five men and five women) as the mean of the ten contractions of each set (test). The ICC and the result of the comparison (F-value) between the three tests (repeated-measures ANOVA) are given together with the p-value Variable

Peak Torquemean (Nm) MNFmean Rectus Femoris (Hz) MNFmean Vastus Lateralis (Hz) MNFmean Vastus Medialis (Hz) RMSmean Rectus Femoris (␮V) RMSmean Vastus Lateralis (␮V) RMSmean Vastus Medialis (␮V) SARmean Rectus Femoris SARmean Vastus Lateralis SARmean Vastus Medialis

Test 1

Test 2

Test 3

ICC

Mean

Std

Mean

Std

Mean

Std

150 87.7 74.4 74.6 211 377 240 0.07 0.08 0.09

57 13.5 9.6 10.4 71 202 119 0.02 0.05 0.03

145 85.6 76.8 75.4 216 350 218 0.07 0.07 0.07

55 11.2 11.4 9.0 78 199 104 0.02 0.04 0.03

146 85.7 75.9 76.6 215 353 216 0.08 0.08 0.08

54 10.1 12.8 8.8 70 199 101 0.04 0.05 0.04

0.99 0.83 0.91 0.93 0.89 0.98 0.96 0.23 0.82 0.55

Anova F-value

p-value

0.03 0.11 0.11 0.12 0.01 0.06 0.15 0.58 0.08 1.55

0.97 0.90 0.89 0.89 0.99 0.94 0.86 0.57 0.92 0.23

Table 3 Mean values ⫾ one standard deviation ( ⫾ 1SD) for the three tests of the ten subjects (five men and five women) at the contraction with maximum peak torque. The ICC and the result of the comparison (F-value) between the three tests (repeated-measures ANOVA) are given together with the p-value Variable

Peak Torquemax (Nm) MNFmax Rectus Femoris (Hz) MNFmax Vastus Lateralis (Hz) MNFmax Vastus Medialis (Hz) RMSmax Rectus Femoris (␮V) RMSmax Vastus Lateralis (␮V) RMSmax Vastus Medialis (␮V) SARmax Rectus Femoris SARmax Vastus Lateralis SARmax Vastus Medialis

Test 1

Test 2

Test 3

ICC

Mean

Std

Mean

Std

Mean

Std

164 93.9 77.7 76.0 213 365 233 0.07 0.09 0.10

63 17.3 11.3 11.5 81 199 123 0.03 0.07 0.06

159 90.1 80.2 79.1 219 339 210 0.06 0.09 0.07

61 13.2 10.5 10.8 80 170 111 0.04 0.08 0.05

160 88.2 74.9 78.9 211 348 222 0.07 0.06 0.06

60 12.3 10.1 10.9 70 180 111 0.05 0.05 0.03

0.99 0.74 0.87 0.79 0.83 0.97 0.96 0.16 0.57 ⫺ 0.11

Anova F-value

p-value

0.02 0.41 0.61 0.24 0.03 0.05 0.10 0.32 0.56 2.03

0.98 0.67 0.55 0.79 0.97 0.95 0.91 0.73 0.58 0.15

Table 4 Mean values ⫾ one standard deviation ( ⫾ 1SD) for the three tests of the ten subjects (five men and five women) as the mean of the three terminal contractions of each set (test). The ICC and the result of the comparison (F-value) between the three tests (repeated-measures ANOVA) are given together with the p-value Variable

Peak Torqueend (Nm) MNFend Rectus Femoris (Hz) MNFend Vastus Lateralis (Hz) MNFend Vastus Medialis (Hz) RMSend Rectus Femoris (␮V) RMSend Vastus Lateralis (␮V) RMSend Vastus Medialis (␮V) SARend Rectus Femoris SARend Vastus Lateralis SARend Vastus Medialis

Test 1

Test 2

Test 3

ICC

Mean

Std

Mean

Std

Mean

Std

147 84.2 73.0 73.4 221 400 260 0.06 0.07 0.08

57 12.3 9.7 10.7 72 223 125 0.03 0.04 0.03

144 81.8 74.5 74.1 227 377 236 0.06 0.07 0.07

58 11.1 11.6 8.5 81 214 122 0.02 0.04 0.03

143 82.2 74.2 74.9 225 377 227 0.08 0.07 0.07

54 9.9 13.1 9.1 72 216 107 0.05 0.05 0.04

0.99 0.77 0.84 0.88 0.87 0.98 0.94 ⫺ 0.02 0.59 0.36

Anova F-value

p-value

0.01 0.13 0.05 0.07 0.02 0.04 0.21 0.66 0.05 0.22

0.99 0.88 0.95 0.94 0.98 0.96 0.81 0.53 0.95 0.81

B. Larsson et al. / Journal of Electromyography and Kinesiology 9 (1999) 351–357

both MNF (except for rectus femoris) and RMS during dynamic contractions (Tables 2–4). During repetitive maximum dynamic contractions a number of factors exist that, from the MNF point of view could theoretically give low ICC such as: the considerable variability shown in MNF variable per se (c.f. Table 3), the relative gliding between, on the one hand the surface electrodes and on the other hand the active muscle tissue, changes in fibre and muscle lengths, differences in effort, changes in torque throughout the predetermined range of motion etc. However the effort did not appear to differ significantly between the three tests and the PT thus had a very high ICC (Table 3), which is consistent with earlier studies [1,2]. Despite these and other possible factors (for instance the stationary problem during dynamic contractions) a relatively high ICC was found for the MNF variables during the dynamic contractions. One explanation for the high reproducibility could be that we used a highly standardised range-of-motion (ROM). Hence most of these factors had constant influence from contraction to contraction. Generally the ICC of the MNF was highest when we used the mean of the ten contractions. All muscles then had good reproducibility. When we used fewer contractions, the ICC decreased. Our results are in this respect consistent with the con¨ berg [21], who recommended multiple clusions of O measurements or regression analysis to minimise the effect of random variation. Good reproducibility has also been reported for during-the-day and between-days for static contractions [15,29]. However, in the present study only one hour of rest was permitted between each test and the surface electrodes were not removed between the tests, which also probably contributed to the relatively high ICC of the MNF. In a recent study of yearto-year reproducibility of the MNF in different parts of an isokinetic test consisting of repetitive maximum isokinetic shoulder flexions we generally found significant Pearson coefficients [30]. Our results concerning MNF are in agreement with some studies that indicate reproducibility and validity for surface EMG variables in the frequency domain during dynamic contractions [4,20,31]. We have reported that the MNF correspond to physiological properties during dynamic contractions and thus indicate validity; i.e. positive significant correlations have been reported between the proportion of type-2 muscle fibres and MNF during single dynamic (non-fatiguing) contractions of the vastus lateralis and trapezius, respectively [22,32]. Against our results concerning MNF, it could be argued that we have only investigated one angular (concentric) velocity. However, no significant effects of concentric angular velocity have been observed in earlier studies of the three muscles of the quadriceps during isokinetic knee extensions between 0.57–3.14 rad s−1 (30–180° s−1) [22]. Furthermore Potvin [10] reported similar MNF for concentric and eccentric contractions. The differences in ICC

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between the three muscles might be due to anatomical differences (for instance amount of subcutaneous tissue, different degrees of movement between the electrodes and the active muscle fibres, different proportions of fibre types and different amounts of cross-talk). Even though the present results concerning reproducibility of MNF are encouraging it must be pointed out that there is a great need for studies of the validity of MNF determinations during dynamic contractions. As pointed out by Ha¨gg [11] the number of active motor units is changing rapidly during a dynamic contraction, which implies nonstationary spectra and eventually low validity and erroneous interpretations of MNF. The high ICC for RMS during dynamic contractions is consistent with other studies of the signal amplitude of the EMG during static and dynamic contractions [27]. In fact Sleivert and Wenger [27] reported very similar ICC for the signal amplitude (iEMG) during static and dynamic contractions. A high degree of reproducibility (two-year interval) has been reported both for the signal amplitude (iEMG) and the electrical efficacy (work/iEMG) of 200 maximum isokinetic plantar flexions, even though no ICC values or correlation coefficients were presented [31]. Despite the very high ICC for RMS, the SAR variables had a relatively low ICC. A contributory factor to the low ICC could be the fact that SAR is a ratio of two variables (i.e. the ratio between RMS of the passive and the active part of the contraction cycle). The low ICC for SAR might also have been due to the fact that SAR was determined at the beginning of the test. In studies of patients with chronic pain we have investigated SAR at the end of a test consisting of 150–200 maximum isokinetic contractions (generally the final 50 contractions) and significantly increased levels have been found when compared to clinically healthy subjects [32,33]. During the very initial part of such a test (i.e. similar to the present 10 contractions) we have noticed on an earlier occasion marked decreases and variability both at individual and group levels. In recent studies of the knee extensors we have found acceptable reproducibility when SAR (determined as the mean of the final 50 out of 150–200 contractions) was investigated at a one-year interval both for the knee extensors and the shoulder flexors during repetitive maximum isokinetic contractions [19,30]. Studies in progress will concern the short term reproducibility of SAR at the end of an endurance test (i.e. 150–200 maximum contractions).

Acknowledgement The present study was supported by grants from the Swedish Council for Work Life Research (project no 96-0542).

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[23] Karlsson S. Erlandsson, B-E., Gerdle, B., A personal computerbased system for real-time analysis of surface EMG-signals during static and dynamic contractions. J Electromyogr Kinesiol 1994;4:170–80. [24] Norman GR, Streiner DL. Biostatistics: the bare essentials. St. Louis: Mosby, 1994. [25] Rankin G, Stokes M. Reliability of assessment tools in rehabilitation: an illustration of appropriate statistical analyses. Clin Rehabil 1998;12:187–99. [26] Shrout PE, Fleiss JL. Intraclass correlations: uses in assessing rater reliability. Psych Bull 1979;86:420–8. [27] Sleivert GG, Wenger HA. Reliability of measuring isometric and isokinetic peak torque, rate of torque development, integrated electromyography and tibial nerve conduction velocity. Arch Phys Med Rehabil 1994;75:1315–21. [28] Currier DP. Elements of research in Physical Therapy. 2nd ed. Baltimore: Williams and Wilkins, 1984. [29] Daanen HAM, Mazure M, Holewijin M, Van Der Velde EA. Reproducibility of the mean power frequency of the surface electromyogram. Eur J Appl Physiol 1990;61:274–7. [30] Elert J, Karlsson S, Gerdle B. One-year reproducibility and stability of the signal amplitude ratio (SAR) and other variables of the EMG- Test-retest of a shoulder forward flexion test in female workers with neck and shoulder problems. Clin Physiol, 1998;18:529–38. [31] Fugl-Meyer AR, Gerdle B, Eriksson B-E, Jonsson B. Isokinetic plantar flexion endurance. Scand J Rehabil Med 1985;20:89–92. [32] Elert J, Rantapa¨a¨-Dahlqvist S, Henriksson-Larse´n K, Lorentzon R, Gerdle B. Muscle performance, electromyography and fibre type composition in fibromyalgia and work-related myalgia. Scand J Rheumatol 1992;21:28–34. [33] Fredin Y, Elert J, Britschgi N, Vaher A, Gerdle B. A decreased ability to relax between repetitive muscle contractions in patients with chronic symptoms after whiplash trauma of the neck. J Musculoskel Pain 1997;50:55–70. Barbro Larsson PT, is postgraduate graduate student at the Department of Rehabilitation Medicine, Faculty of Health Sciences, Linko¨ping. She has been working with the rehabilitation of children and adults with neurological disabilities for over 20 years. She has also worked as a teacher in physiotherapy at the Faculty of Health Sciences, Linko¨ping.

Bjarne Månsson M.D. is specialist of rehabilitation medicine since 1992 and works at the Pain and Rehabilitation Centre, University Hospital, Linko¨ping. He has been a postgraduate student since 1994 at the Department of Rehabilitation Medicine, Faculty of Health Sciences, Linko¨ping.

B. Larsson et al. / Journal of Electromyography and Kinesiology 9 (1999) 351–357 Christian Karlberg M.Sc has studied Applied Physics and Electrical Engineering at Linko¨ping University. He wrote his masters thesis about the EMG signal in 1997, and has since then participated in different research projects concerning surface EMG at the Department of Rehabilitation Medicine, Faculty of Health Sciences, Linko¨ping. His present work concerns different ways of analysing the EMG signal during dynamic contractions.

Peter Syvertsson PT was research engineer at the Department of Rehabilitation Medicice, Faculty of Health Sciences, Linko¨ping between 1994 and 1998. He is now living in Norway and working as a physiotherapist/test leader.

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Jessica Elert, PhD, PT is senior lecturer in physical therapy at the Faculty of Health Sciences, Linko¨ping, Sweden, since 1993. She has worked as physiotherapist, 1977–1992, University Hospital, Umeå, Sweden, as senior lecturer in physical therapy, University of Umeå, 1992–1993, and as research leader in phyiscal therapy, University Hospital, Umeå 1991–1993. Her specific research fields are the relationship between muscle tension and surface EMG in clinically healthy subjects and in patients with different pain conditions. She has published approximately 15 original papers in international journals. Bjo¨rn Gerdle, MD, PhD, is professor in rehabilitation medicine at the Department of Rehabilitation Medicine, Faculty of Health Sciences, Linko¨ping, Sweden, and has been associated professor in work physiology at the National Institute of Occupational Health in Umeå, Sweden. He has published approximately 80 original papers in international journals mainly within the fields of muscle fatigue, electromyography, clinical pain and rehabilitation. The specific research fields are now muscle tension (electromyography) in relation to muscle pain (occupational muscle pain and fibromyalgia) and the effects of multimodal rehabilitation programmes in patients with mainly nociceptive pain.