- Email: [email protected]
Long-term stability of tensiomyography measured under different muscle conditions
Journal of Electromyography and Kinesiology 23 (2013) 558–563
Contents lists available at SciVerse ScienceDirect
Journal of Electromyography and Kinesiology journal homepage: www.elsevier.com/locate/jelekin
Long-term stability of tensiomyography measured under different muscle conditions Massimiliano Ditroilo c,⇑, Iain J. Smith a, Malcolm M. Fairweather b, Angus M. Hunter a a
Health and Exercise Sciences Research Group, University of Stirling, Scotland, United Kingdom Sportscotland Institute of Sport, Stirling, Scotland, United Kingdom c Department of Sport, Health & Exercise Science, Faculty of Science, University of Hull, England, United Kingdom b
a r t i c l e
i n f o
Article history: Received 19 July 2012 Received in revised form 17 January 2013 Accepted 17 January 2013
Keywords: Reliability Minimum detectable change Muscle contractile properties
a b s t r a c t Tensiomyography (TMG) is a technique utilised to measure mechanical and contractile properties of skeletal muscle. Aim of this study was to assess long-term stability of TMG across a variety of muscle conditions. Gastrocnemius Medialis of 21 healthy males was measured using TMG in rested conditions, after a warm-up, after a maximal voluntary contraction and after a fatigue protocol. Participants were re-tested on a second occasion 4 weeks apart. Among the parameters examined, Contraction Time, Sustain Time and Delay time exhibited a good level of absolute reliability (CV = 3.8–9.4%) and poor to excellent level of relative reliability (ICC = 0.56–0.92). On the other hand, relative reliability was good to excellent for muscle Displacement (ICC = 0.86–0.96), whereas its level of absolute reliability was questionable (CV = 8.0–14.8%). Minimum detectable change was less than 20% in most conditions for the aforementioned parameters. Half-relaxation Time yielded overall insufficient reliability. In general, the level of reliability tended to increase after the maximal voluntary contraction and the fatigue protocol were administered, probably because of more controlled conditions preceding the measurement. Information about the long-term stability of TMG across different muscle conditions is essential when intervention studies are undertaken with an exercising population, particularly athletes. Ó 2013 Elsevier Ltd. All rights reserved.
1. Introduction Numerous techniques are available to study muscle function either in the laboratory or in the field setting. Tensiomyography (TMG) has been developed over the last 15 years as a non-invasive technique which makes use of a portable device to assess skeletal muscle mechanical and contractile properties in response to electrical stimuli (Dahmane et al., 2005, 2001; Pišot et al., 2008). This response produces spatial and temporal parameters of the radial displacement of muscle belly (Valencˇicˇ and Knez, 1997). TMG has been used to: (1) predict the proportion of myosin heavy chain I (Dahmane et al., 2005; Šimunicˇ et al., 2011); (2) monitor the change in passive tension as a result of a change in muscle length (Ditroilo et al., 2011); (3) detect muscle damage following eccentric exercise (Hunter et al., 2012); (4) monitor muscle alterations following bed rest (Pišot et al., 2008); and (5) assess the effect of recovery strategies (García-Manso et al., 2011a; Rey et al., 2011).
⇑ Corresponding author. Address: Department of Sport, Health & Exercise Science, Faculty of Science, Don Building, Room 001A, University of Hull, Hull HU6 7RX, England, United Kingdom. Tel.: +44 (0)1482 463859; fax: +44 (0)1482 463855. E-mail address: [email protected] (M. Ditroilo). 1050-6411/$ - see front matter Ó 2013 Elsevier Ltd. All rights reserved. http://dx.doi.org/10.1016/j.jelekin.2013.01.014
Therefore, it would appear that TMG is an attractive tool for practitioners and researchers seeking to establish muscle status across a variety of conditions. However, in order to ascertain whether a change in TMG is meaningful or simply measurement error it is important to accurately determine reliability. Previous studies have shown good to excellent inter-rater reliability (Tous-Fajardo et al., 2010) and acceptable to good intra-day reliability (Carrasco et al., 2011; Krizaj et al., 2008) of TMG. Interday reliability has been measured over three consecutive days for vastus lateralis, vastus medial and biceps femoris with good to excellent levels of reliability (Šimunicˇ, 2012). However, when intervention studies are undertaken, the evaluation of the longterm stability of specific variables is critical (Clark et al., 2007). Another important factor within TMG measurement is the capability to reliably measure mechanical and contractile properties of muscles across a number of muscle conditions, e.g., at rest, after warm-up, after a maximal voluntary contraction (MVC) and in fatigued conditions. This versatility across different measurement conditions is particularly relevant for the assessment of an exercising population, especially athletes. Muscle fatigue in particular is a widely investigated topic and in two recent studies TMG successfully detected alterations in the rectus femoris and biceps femoris muscles (García-Manso et al., 2011b) and in the biceps brachii muscle (García-Manso et al., 2012) as a result of fatigue induced
M. Ditroilo et al. / Journal of Electromyography and Kinesiology 23 (2013) 558–563
by an ultra-endurance triathlon and by resistance exercise, respectively. Yet, no information about long term inter-day reliability of the TMG parameters was documented. Accordingly, the aim of this study was to assess the long-term stability of mechanical and contractile properties of gastrocnemius medialis as measured with TMG in rested, exercised and fatigued muscle conditions. Gastrocnemius is one of the propulsive muscles fundamental to different types of human locomotion (e.g. walking, running and cycling) and is clearly measurable by TMG. The results of this reliability study could therefore assist a range of researchers and sport practitioners in tracking meaningful muscle changes as a result of training and recovery. 2. Methods 2.1. Participants Twenty-one healthy males with a mean (±SD) age, height, and mass of 21.3 ± 3.4 years, 182.0 ± 6.1 cm, 79.5 ± 10.0 kg, volunteered and gave their informed consent to participate in this study. The study was performed according to the Declaration of Helsinki and was approved by the local research ethics committee. 2.2. Experimental design Mechanical and contractile properties of the right Gastrocnemius Medialis (GM) were measured using TMG (BMC Ltd., Ljubljana). Participants were also required to undertake a warm-up, a MVC of the right plantar flexors and a protocol to fatigue the GM. As illustrated in Fig. 1, measurements were taken at a number of time points in the following order: TMG (measurement 1, M1), warm-up, TMG (M2), MVC, TMG (M3), fatigue intervention, TMG (M4). TMG measurements were recorded straight after skin marking and electrodes placement at rest (i.e. within 2 min), whereas to limit the effects of post-activation potentiation in the GM muscle (Pääsuke et al., 2007) measurement was taken 3 min after the warm-up, the performance of MVC and the fatigue intervention, which was considered to be sufficient period for the circulating Ca2+ to be transported back into the sarcoplasmic recticulum (Pääsuke et al., 2007). To assess inter-day reliability of the TMG parameters, the testing session was also repeated within 4 weeks’ time. This period was chosen to evaluate the long-term stability of the measured variables, in keeping with context of intervention studies (Clark et al., 2007). To ensure standardised conditions, participants were instructed to refrain from strenuous physical activity 24 h prior to their scheduled lab visit (always at the same time of day) and to ensure a constant hydration status they drank 500 ml of water 2 h before the start of testing.
559
2.4. TMG protocol Measurements were performed in a prone position on a padded bench with a foam pad placed just above the ankle which supported around five degrees of knee flexion (Fig. 2a). A digital displacement transducer (TMG–BMC Ltd., Ljubljana) was then placed perpendicular to the muscle belly of the right GM with a controlled initial pressure of 1.5 10 2 N/mm2. This measuring position was selected by visually and manually pulsating the GM to determine the thickest part of the muscle and then later, if needed, it was slightly adjusted to obtain the highest mechanical response with the least amount of co-activation when externally stimulated; this was typically identified by a second peak in the TMG response curve. Once chosen, this position was marked with a permanent maker pen to ensure the sensor was placed in the exact same position on subsequent measurements. The centre point of the two stimulating electrodes (5 cm2) (Axelgaard, USA) was located approximately half way from the position of the sensor (5 cm) to the start of the respective GM proximal distal tendons. After each measurement these electrodes were left in place and unplugged to avoid any possible changes in muscle response via alterations in surface electrodes distance (Tous-Fajardo et al., 2010). A single 1 ms wide stimulation pulse was delivered, which applied an initial current amplitude of 20 mA. This amplitude was progressively increased by 10 mA increments until maximal response was obtained. In order to minimise the effects of fatigue and potentiation, rest periods of 10 s were given between each mA increments. Typical maximal responses were of a stimulation amplitude between 40 and 70 mA and only the output data for that particular stimulation intensity were used for analysis. As previously documented (Šimunicˇ et al., 2011; Ditroilo et al., 2011), this stimulus is likely to evoke a low torque response, in the order of 10% of MVC. Nonetheless, the high sensitivity of the digital displacement transducer can detect muscle displacement in response to voluntary contractions up to about 68% of MVC (Pišot et al., 2008) and this is consistent with mechanomyography (Akataki et al., 2001), a similar but more established technique of analysis of muscle properties. From each maximal twitch response, five output parameters were extracted and analysed (Tous-Fajardo et al., 2010) (Fig. 2b): Displacement (Dm), the extent of maximal radial deformation (millimetre) of the muscle belly during contraction; Delay time (Td), the time taken from onset of the electrical stimulus to 10% of maximal radial displacement (millisecond); Contraction time (Tc), the time (millisecond) between 10% and 90% of maximal displacement; Sustain time (Ts), the time (millisecond) between 50% of maximal displacement during the contraction phase and 50% of maximal displacement during the relaxation phase, half relaxation time (Tr), the time (millisecond) taken to fall from 90% to 50% of maximal displacement during the relaxation phase.
2.3. Warm-up Participants warmed up by cycling at low intensity (75 W) on an electromagnetically braked cycle ergometer (Lode Ergometer, Netherlands) at a cadence between 80 and 90 rpm for a period of 5 min.
2.5. Maximal voluntary contraction (MVC) protocol Plantar flexor isometric MVC was performed in an isokinetic dynamometer (Kin-Com, Chattanooga Group Inc., USA) with the
Fig. 1. Overview of the testing protocol. TMG = tensiomyography; MVC = maximal isometric voluntary contraction;
560
M. Ditroilo et al. / Journal of Electromyography and Kinesiology 23 (2013) 558–563
Fig. 2. (a) Tensiomyography set-up with the displacement sensor and electrodes placed on gastrocnemius medialis. (b) Typical displacement/time signal recorded as a result of an electrical stimulation. Dm = maximal displacement (mm); Td = delay time (ms); Tc = contraction time (ms); Tr = relaxation time (ms); Ts = sustain time (ms).
participant having their right foot fastened securely into the plantar flexion attachment. The lever arm was lifted to an exact horizontal position using a magnetic spirit level and a 90° ankle angle to the tibia was ensured for each subject. The dynamometer position was set to ensure that the subject’s right leg was straight to maximise the involvement of the gastrocnemius muscles (and minimising soleus involvement) during plantar flexion. Participants were also held in place using two securely fastened shoulder straps and a lap belt. Following two sub-maximal warm-up sets, participants each performed a 5-s MVC of the right plantar flexors. Three trials of the MVC were completed with 60 s recovery between attempts. Participants were verbally motivated to ensure the greatest possible effort for the duration of all attempts.
2.6. Fatigue protocol The fatigue intervention consisted of a 5 min intermittent electrical stimulation of the right GM to evoke fatigue. The stimulation protocol involved continuous repeats of 15 electrical pulses (10 Hz) for a period of 1.5 s with a 1 s gap between the pulses. Participants were asked to endure the maximum current they could to ensure fatigue (110 mA). This protocol was chosen to induce low frequency fatigue which will necessitate greater recovery than high frequency fatigue (Metzger and Fitts, 1987). Furthermore, as motor unit discharge rate rarely exceeds 30 Hz during voluntary contraction the frequency we have chosen can be considered to
be more functionally relevant than using substantially higher frequencies (Allen et al., 2008).
2.7. Statistical analysis Inter-day reliability of TMG was assessed at the time points M1, M2, M3, M4 using indexes of relative and absolute reliability. Intraclass correlation coefficient (ICC) and coefficient of variation (CV) were calculated along with their 95% confidence intervals. The CV is defined as (s/mean) 100, where s is the standard deviation and mean is the mean of the change scores of the measure (Atkinson and Nevill, 1998). The ICC is defined as (V v)/V, where V is the between-subject variance averaged over the two trials analysed, and v is the within-subject square of the standard error of measurement averaged across the subjects (Weir, 2005). The standard error of measurement (SEM), defined as S (1-ICC)1/2, where S is the standard deviation of the scores from all subjects, was also calculated together with the minimum detectable change (MDC), i.e., the minimum meaningful change in a variable over time, defined as 1.96 21/2 SEM (Weir, 2005). The minimum detectable change is also expressed as a percentage: (MDC/mean of all observations) 100 (Webber and Porter, 2010). Systematic bias between the two measurements at each time point was analysed using a paired t-test (Atkinson and Nevill, 1998). Reference to a study by Tous-Fajardo et al. (2010) was applied to interpret the CV values with an analytical goal set at 10% whereas ICC was examined in conjunction with
561
M. Ditroilo et al. / Journal of Electromyography and Kinesiology 23 (2013) 558–563
CV without setting a priori criteria since it has been argued that there is no consensus in its interpretation (Weir, 2005). 3. Results CV and ICC, along with their 95% confidence intervals are reported in Table 1 for the five TMG parameters. Generally, there is an improvement in reliability when moving from M1 to M4, which is evident from the decrease in CV and the increase in ICC. Tc, Ts and Td exhibited an acceptable to good level of reliability, although the ICC is quite low for Tc and Td. Dm showed a moderate to good level of reliability with excellent ICCs. The level of reliability for the Tr parameter is insufficient with CVs around 30% and questionable levels of ICCs. Systematic bias was only detected for Dm at M1 (3.4 vs. 3.9 mm, p < 0.05) and at M2 (3.6 vs. 4.0 mm, p < 0.01) time points. Table 2 shows the SEM, MDC and %MDC for the aforementioned parameters. Similarly to the other reliability indexes, SEM decreased across the four time points of measurement. Likewise, the smallest MDC and %MDC were at time point M4. The %MDC are in the order of 15–20% for Tc, Ts, Td and Dm parameters with values as low as 9.49% and 7.33% at time point M4 for Ts and Tc, respectively. Tr displayed %MDC ranging from 44.12% to 70.11%. 4. Discussion TMG is a technique that utilises a portable device to record radial muscle belly displacement as a result of an electrical stimulus. Once it is set-up a measure can be obtained in a few seconds, therefore it is ideal to be used in a field setting and across a variety of applications as demonstrated by the growing body of literature on TMG. The aim of this study was to assess the long-term stability of a number of TMG parameters under four muscle conditions: at rest, after warm-up, after a MVC and in fatigued condition. Although CVs and ICCs yielded somehow inconsistent results, overall the parameters with the highest level of inter-day reliability are three contractile properties of the GM, namely Tc, Ts and Td. Moreover, for all parameters there was a trend towards an increase in reliability after the muscle had performed MVC and had undergone a fatigue protocol. Only Dm showed bias at two measurement points (at rest and after warm-up) indicating that the systematic error coming from the measuring device, the electrodes and probe re-placement, or the pre-measurement state of the muscle was overall low. Information about the long-term stability of TMG parameters is essential when intervention studies are undertaken in order to be able to distinguish between measurement error and real change brought about by the treatment. This is particularly relevant for TMG since the accurate re-placement of electrodes and probe can be an issue (Tous-Fajardo et al., 2010). Two previous studies have examined reliability of the same set of five TMG parameters (Tc, Ts, Tr, Td, Dm). Tous-Fajardo et al. (2010) assessed the intra- and inter-rater reliability whilst Šimunicˇ (2012) assessed the inter-day reliability over three consecutive
days. Interestingly, in both investigations Tc and Ts presented the lowest level and Tr the highest level of CV, and these findings have been confirmed in the present study. When looking at measurements taken over different days, the overall level of reliability in the study by Šimunicˇ (2012), with ICCs constantly higher than 0.87 and CVs below 10%, is much higher than in the present study. This difference in reliability measurement could mainly be attributed to the different research design, with measurements taken 1-day vs. 4-week apart, respectively. Based on the results of this study it appears that 4 weeks of time greatly reduces the consistencies between measurements, and this finding has implications in the determination of the clinically or practically important difference and the smallest worthwhile change in prospective investigations. Other factors, such as muscles examined (quadriceps vs. gastrocnemius) and subject preparation, could account for the difference in reliability between the two studies. When considering subject preparation, unlike the present study, Šimunicˇ (2012) had the participants resting supine in bed for an hour prior to measurement. Whilst this may be good practice to allow redistribution of fluids (Berg et al., 1993), this procedure may be impractical for athletes who notoriously have limited time to devote to sport testing. In other research circumstances, such as when the effect of fatigue on mechanical and contractile properties of skeletal muscle has been investigated (e.g. García-Manso et al., 2011b), the research design does not allow for any supine resting prior to measurement, therefore the protocol adopted in the present study is deemed more appropriate. Tc and Dm are the most commonly reported parameters when TMG is performed. The level of absolute (i.e. CV) and relative (i.e. ICC) reliability for either parameters did not match, with Tc presenting a good to excellent level of CV (9.4–3.8%) but poor to excellent level of ICC (0.62–0.92) and Dm showing an acceptable to questionable level of CV (8.0–14.8%) and good to excellent level of ICC (0.86–0.95). It is well known however that the two reliability indexes convey different information. CV measures the consistency of measurements within participants on different occasions, whereas ICC measures the extent to which participants maintain the same rank within the group (Atkinson and Nevill, 1998). The latter is also affected by the heterogeneity of the sample, with more heterogeneous results within the group displaying higher ICCs when all other conditions are equal (Atkinson and Nevill, 1998). Indeed, this observation could at least partially explain the apparently contradicting results within the present study. A similar difference between absolute and relative reliability is exhibited by the Ts and even more by the Td parameter, with the latter showing a good level of CV but poor ICCs. As supported by similar outcomes in other investigations (Šimunicˇ, 2012; Tous-Fajardo et al., 2010) Tr showed overall insufficient reliability (CV: 27.8–32.7%; ICC: 0.67–0.82). Thus based on the results of this study it is advised not to use this parameter when medium/long term intervention studies are carried out. Notably, for all parameters the overall level of reliability tended to increase across the four measurements, i.e. the TMG reliability is
Table 1 Coefficient of variation and intraclass correlation coefficient of the five tensiomyographic parameters analysed. CV (95% CI)
Tc Ts Tr Td Dm
ICC (95% CI)
M1
M2
M3
M4
M1
9.4 (6.3–12.5) 6.8 (3.7–9.9) 30.3 (18.2–42.4) 9.2 (5.2–12.9) 14.8 (10.4–19.3)
9.1 (6.4–11.8) 8.2 (5.0–11.3) 32.7 (18.4–47.0) 8.2 (4.2–12.3) 11.1 (7.0–15.1)
8.1 (5.4–10.8) 5.5 (3.7–7.3) 27.8 (14.5–41.1) 7.8 (3.7–11.9) 10.1 (5.0–15.2)
3.8 (2.3–5.3) 5.3 (3.1–7.6) 29.4 (19.2–39.6) 7.0 (3.2–10.8) 8.0 (5.0–11.0)
0.62 0.78 0.79 0.60 0.86
M2 (0.27–0.83) (0.54–0.91) (0.55–0.91) (0.24–0.82) (0.68–0.94)
0.63 0.71 0.67 0.56 0.91
M3 (0.28–0.83) (0.41–0.87) (0.35–0.85) (0.18–0.80) (0.79–0.96)
0.62 0.84 0.82 0.62 0.92
M4 (0.26–0.82) (0.65–0.93) (0.60–0.92) (0.27–0.83) (0.82–0.97)
0.92 0.86 0.79 0.62 0.95
CV = coefficient of variation; CI = confidence intervals; ICC = intraclass correlation coefficient; M1, M2, . . . = time point when the measurement was taken. Tc = Contraction time (ms); Ts = Sustain time (ms); Tr = half-relaxation time (ms); Td = delay time (ms); Dm = muscle displacement (mm).
(0.82–0.97) (0.70–0.94) (0.56–0.91) (0.26–0.82) (0.87–0.98)
562
M. Ditroilo et al. / Journal of Electromyography and Kinesiology 23 (2013) 558–563
Table 2 Standard error of measurement and minimum detectable change of the five tensiomyographic parameters analysed. SEM
Tc Ts Tr Td Dm
MDC
%MDC
M1
M2
M3
M4
M1
M2
M3
M4
M1
M2
M3
M4
1.36 7.00 16.03 1.34 0.30
1.36 9.01 19.07 1.52 0.26
1.18 5.83 12.88 1.27 0.21
0.61 5.59 11.73 1.16 0.19
3.77 19.41 44.44 3.72 0.84
3.77 24.96 52.86 4.21 0.72
3.28 16.16 35.70 3.53 0.58
1.68 15.49 32.50 3.20 0.51
15.79 11.84 62.95 16.41 22.07
14.95 14.26 70.11 19.05 18.19
13.70 10.27 59.33 17.15 17.13
7.33 9.49 44.12 14.98 15.05
SEM = standard error of measurement; MDC = minimum detectable change; M1, M2, . . . = time point when the measurement was taken. Tc = Contraction time (ms); Ts = Sustain time (ms); Tr = half-relaxation time (ms); Td = delay time (ms); Dm = muscle displacement (mm).
higher when the muscle is measured post-MVC or after the fatigue protocol. Although not easy to explain, it has to be considered that prior to the first measurement conditions were predominantly uncontrolled, with the exception that participants had been asked to refrain from strenuous exercise and to drink 500 ml of water 2 h before the testing session. The subsequent protocol administration, which lasted approximately 30 min, had progressively more controlled conditions, hence the improved reliability. Also, it is likely that prior to inducing fatigue the potentiation of the muscle became progressively amplified which could improve the homogeneity of the TMG response; this is considered to be appropriate methodological practice on resting muscle to ensure that muscle has achieved maximal potentiation prior to inducing any intervention (Lee and Binder-Macleod, 2000). Furthermore, the measurement taken after the fatigue protocol happened 8–10 min after the participant was resting in a prone position, which has allowed some fluid shifts to occur (Berg et al., 1993) and potentially more standardised muscle conditions. The MDC establishes the magnitude of change that represents ‘true’ change beyond measurement error and is provided in this study for each parameter measured, across the four measurements. It is useful to define MDC because it helps to interpret the effectiveness of the intervention undertaken and can assist the researcher or sport practitioner in structuring a training/recovery plan. Taken together, the results of this study suggest that for Tc, Ts, Td and Dm in most conditions changes of more than 20% are necessary to detect a real change. It is interesting to compare the overall level of long-term stability of the TMG to that of more traditional neuromuscular parameters. Clark et al. (2007) measured the neuromuscular function of plantar-flexors in seventeen young individuals before and after a 4-week control period. MVC and rate of force development, evoked muscle force and rate of force development and relaxation, electromyography, H-reflex excitability, and several more measures exhibited a CV ranging from 4.2% to 19.9% and an ICC ranging from 0.97 to 0.53. It appears that long-term stability of TMG does not differ from that of more established neuromuscular parameters. There are limitations associated with this study and technique. First, with respect to the protocol of data collection, in order to limit the effects of post-activation in the GM muscle (Pääsuke et al., 2007) the TMG measurements were taken 3 min after the administration of the fatigue protocol. Although low frequency fatigue lasts longer (Metzger and Fitts, 1987), a TMG measurement taken just after the fatigue protocol could have better characterised the induced fatigue. Second, identification of the motor point through EMG would have ensured maximal contraction of the muscle belly from the stimulation and potentially improved the reliability. However, it is important to note that TMG is intended as a field based measure; therefore such additional procedures would add a substantial amount of time and equipment making it impractical for its proposed purpose. Finally, one limitation of the TMG technique has to do with muscle displacement dynamics with respect to the low stimulus used. As mentioned in Section 2, TMG resembles mechanomyography. A study by Orizio et al. (1999) using the
latter technique has identified some potential factors that can affect the geometrical change of the stimulated muscle at low vs. high stimulation frequencies. Importantly, they demonstrated that there is relatively large muscle displacement at the low frequencies which generates low force production with the opposite outcomes at the high frequencies. Therefore, the former condition could be more relatively affected by different arrangement of the contractile elements and fibre lengths, and different behaviour of the sarcomeres and aponeurosis along the active muscle (Orizio et al., 1999). Consequently, these factors may also have affected the radial displacement of the muscle as detected by TMG. 5. Conclusions When assessing the long-term stability of five TMG parameters Tc, Ts and Td exhibited an overall good level of absolute reliability and poor to excellent level of relative reliability. On the other hand, relative reliability was good to excellent for Dm, whereas its level of absolute reliability was questionable. Tr yielded overall insufficient reliability. The MDC provided will allow to distinguish between ‘‘true’’ change and measurement error when intervention studies are undertaken. This study examined one single muscle – GM – further research could investigate long-term stability of TMG parameters measured on different muscles. 6. Conflict of interest The authors declare that they have no conflict of interest. Acknowledgements Funding for the study was provided by UK Sport, The University of Stirling, and the Sportscotland Institute of Sport. References Akataki K, Mita K, Watakabe M, Itoh K. Mechanomyogram and force relationship during voluntary isometric ramp contractions of the biceps brachii muscle. Eur J Appl Physiol 2001;84:19–25. Allen DG, Lamb GD, Westerblad H. Skeletal muscle fatigue: cellular mechanisms. Physiol Rev 2008;88:287–332. Atkinson G, Nevill AM. Statistical methods for assessing measurement error (reliability) in variables relevant to sports medicine. Sports med 1998;26:217–38. Berg HE, Tedner B, Tesch PA. Changes in lower limb muscle cross-sectional area and tissue fluid volume after transition from standing to supine. Acta Physiol Scand 1993;148:379–85. Carrasco L, Sañudo B, de Hoyo M, Pradas F, Da Silva ME. Effectiveness of lowfrequency vibration recovery method on blood lactate removal, muscle contractile properties and on time to exhaustion during cycling at VO(2max) power output. Eur J Appl Physiol 2011;111:2271–9. Clark BC, Cook SB, Ploutz-Snyder LL. Reliability of techniques to assess human neuromuscular function in vivo. J Electromyogr Kinesiol 2007;17:90–101. Dahmane R, Djordjevic S, Šimunicˇ B, Valencˇicˇ V. Spatial fiber type distribution in normal human muscle Histochemical and tensiomyographical evaluation. J Biomech 2005;38:2451–9. Dahmane R, Valencˇicˇ V, Knez N, Erzˇen I. Evaluation of the ability to make noninvasive estimation of muscle contractile properties on the basis of the muscle belly response. Med Biol Eng Comput 2001;39:51–5.
M. Ditroilo et al. / Journal of Electromyography and Kinesiology 23 (2013) 558–563 Ditroilo M, Hunter AM, Haslam S, De Vito G. The effectiveness of two novel techniques in establishing the mechanical and contractile responses of biceps femoris. Physiol Meas 2011;32:1315–26. García-Manso JM, Rodríguez-Matoso D, Rodríguez-Ruiz D, Sarmiento S, de Saa Y, Calderón J. Effect of cold-water immersion on skeletal muscle contractile properties in soccer players. Am J Phys Med Rehabil 2011;90:356–63. García-Manso JM, Rodríguez-Matoso D, Sarmiento S, de Saa Y, Vaamonde D, Rodríguez-Ruiz D, et al. Effect of high-load and high-volume resistance exercise on the tensiomyographic twitch response of biceps brachii. J Electromyogr Kinesiol 2012. García-Manso JM, Rodríguez-Ruiz D, Rodríguez-Matoso D, de Saa Y, Sarmiento S, Quiroga M. Assessment of muscle fatigue after an ultra-endurance triathlon using tensiomyography (TMG). J Sports Sci 2011;29:619–25. Hunter AM, Galloway SD, Smith IJ, Tallent J, Ditroilo M, Fairweather MM, et al. Assessment of eccentric exercise-induced muscle damage of the elbow flexors by tensiomyography. J Electromyogr Kinesiol 2012;22:334–41. Krizaj D, Šimunicˇ B, Zagar T. Short-term repeatability of parameters extracted from radial displacement of muscle belly. J Electromyogr Kinesiol 2008;18:645–51. Lee SC, Binder-Macleod SA. Effects of activation frequency on dynamic performance of human fresh and fatigued muscles. J Appl Physiol 2000;88:2166–75. Metzger JM, Fitts RH. Fatigue from high- and low-frequency muscle stimulation: contractile and biochemical alterations. J Appl Physiol 1987;62:2075–82. Orizio C, Baratta RV, Zhou BH, Solomonow M, Veicsteinas A. Force and surface mechanomyogram relationship in cat gastrocnemius. J Electromyogr Kinesiol 1999;9:131–40. Pääsuke M, Saapar L, Ereline J, Gapeyeva H, Requena B, Oöpik V. Postactivation potentiation of knee extensor muscles in power- and endurance-trained, and untrained women. Eur J Appl Physiol 2007;101:577–85. Pišot R, Narici MV, Šimunicˇ B, De Boer M, Seynnes O, Jurdana M, et al. Whole muscle contractile parameters and thickness loss during 35-day bed rest. Eur J Appl Physiol 2008;104:409–14. Rey E, Lago-Peñas C, Lago-Ballesteros J, Casáis L. The effect of recovery strategies on contractile properties using tensiomyography and perceived muscle soreness in professional soccer players. J Strength Cond Res 2011. 10.1519/ JSC.0b013e3182470d33. Šimunicˇ B. Between-day reliability of a method for non-invasive estimation of muscle composition. J Electromyogr Kinesiol 2012. 10.1016/ j.jelekin.2012.04.003. Šimunicˇ B, Degens H, Rittweger J, Narici M, Mekjavic´ IB, Pišot R. Noninvasive estimation of myosin heavy chain composition in human skeletal muscle. Med Sci Sports Exerc 2011;43:1619–25. Tous-Fajardo J, Moras G, Rodríguez-Jiménez S, Usach R, Doutres DM, Maffiuletti NA. Inter-rater reliability of muscle contractile property measurements using noninvasive tensiomyography. J Electromyogr Kinesiol 2010;20:761–6. Valencˇicˇ V, Knez N. Measuring of skeletal muscles’ dynamic properties. Artif Organs 1997;21:240–2. Webber SC, Porter MM. Reliability of ankle isometric, isotonic, and isokinetic strength and power testing in older women. Phys Ther 2010;90:1165–75. Weir JP. Quantifying test-retest reliability using the intraclass correlation coefficient and the SEM. J Strength Cond Res 2005;19:231–40.
Massimiliano Ditroilo is a lecturer in Sport and Exercise Biomechanics at University of Hull (UK). He received his PhD in Health and Performance Science from University College Dublin (Ireland) in 2012 conducting research on ‘mechanical properties of muscletendon unit and relationships with sport performance and ageing’. Other research interests include age-related decline of muscle function.
563
Iain J. Smith is a consultant in the fitness industry in Glasgow. He received his M.Phil. from University of Stirling examining the effect of a 12-week strength training and concurrent endurance cycling programme on neuromuscular activity.
Malcolm M. Fairweather is Head of Science and Innovation at sportscotland’s Institute of Sport. He received his Ph.D. in Motor Behaviour from Louisiana State University in 1994, with a research focus in applied Motor Learning and Skill Acquisition areas. His current work remit includes investigating high performance sport and coaching questions. Malcolm has explored the application of Tensiomiography measures within high performance sport environments and in partnership with Stirling University/Dr Angus Hunter over a 6 year period. This work has included both basic and applied research questions.
Angus M. Hunter is a Senior Lecturer in Exercise Physiology at University of Stirling, Scotland, UK. He received his Doctoral degree from University of Cape Town, in the Physiology of Exercise examining various manipulations on neural fatigue. His current research interests include neuromuscular control and adaptation for both high performance sport and clinical patient mobility.
Contents lists available at SciVerse ScienceDirect
Journal of Electromyography and Kinesiology journal homepage: www.elsevier.com/locate/jelekin
Long-term stability of tensiomyography measured under different muscle conditions Massimiliano Ditroilo c,⇑, Iain J. Smith a, Malcolm M. Fairweather b, Angus M. Hunter a a
Health and Exercise Sciences Research Group, University of Stirling, Scotland, United Kingdom Sportscotland Institute of Sport, Stirling, Scotland, United Kingdom c Department of Sport, Health & Exercise Science, Faculty of Science, University of Hull, England, United Kingdom b
a r t i c l e
i n f o
Article history: Received 19 July 2012 Received in revised form 17 January 2013 Accepted 17 January 2013
Keywords: Reliability Minimum detectable change Muscle contractile properties
a b s t r a c t Tensiomyography (TMG) is a technique utilised to measure mechanical and contractile properties of skeletal muscle. Aim of this study was to assess long-term stability of TMG across a variety of muscle conditions. Gastrocnemius Medialis of 21 healthy males was measured using TMG in rested conditions, after a warm-up, after a maximal voluntary contraction and after a fatigue protocol. Participants were re-tested on a second occasion 4 weeks apart. Among the parameters examined, Contraction Time, Sustain Time and Delay time exhibited a good level of absolute reliability (CV = 3.8–9.4%) and poor to excellent level of relative reliability (ICC = 0.56–0.92). On the other hand, relative reliability was good to excellent for muscle Displacement (ICC = 0.86–0.96), whereas its level of absolute reliability was questionable (CV = 8.0–14.8%). Minimum detectable change was less than 20% in most conditions for the aforementioned parameters. Half-relaxation Time yielded overall insufficient reliability. In general, the level of reliability tended to increase after the maximal voluntary contraction and the fatigue protocol were administered, probably because of more controlled conditions preceding the measurement. Information about the long-term stability of TMG across different muscle conditions is essential when intervention studies are undertaken with an exercising population, particularly athletes. Ó 2013 Elsevier Ltd. All rights reserved.
1. Introduction Numerous techniques are available to study muscle function either in the laboratory or in the field setting. Tensiomyography (TMG) has been developed over the last 15 years as a non-invasive technique which makes use of a portable device to assess skeletal muscle mechanical and contractile properties in response to electrical stimuli (Dahmane et al., 2005, 2001; Pišot et al., 2008). This response produces spatial and temporal parameters of the radial displacement of muscle belly (Valencˇicˇ and Knez, 1997). TMG has been used to: (1) predict the proportion of myosin heavy chain I (Dahmane et al., 2005; Šimunicˇ et al., 2011); (2) monitor the change in passive tension as a result of a change in muscle length (Ditroilo et al., 2011); (3) detect muscle damage following eccentric exercise (Hunter et al., 2012); (4) monitor muscle alterations following bed rest (Pišot et al., 2008); and (5) assess the effect of recovery strategies (García-Manso et al., 2011a; Rey et al., 2011).
⇑ Corresponding author. Address: Department of Sport, Health & Exercise Science, Faculty of Science, Don Building, Room 001A, University of Hull, Hull HU6 7RX, England, United Kingdom. Tel.: +44 (0)1482 463859; fax: +44 (0)1482 463855. E-mail address: [email protected] (M. Ditroilo). 1050-6411/$ - see front matter Ó 2013 Elsevier Ltd. All rights reserved. http://dx.doi.org/10.1016/j.jelekin.2013.01.014
Therefore, it would appear that TMG is an attractive tool for practitioners and researchers seeking to establish muscle status across a variety of conditions. However, in order to ascertain whether a change in TMG is meaningful or simply measurement error it is important to accurately determine reliability. Previous studies have shown good to excellent inter-rater reliability (Tous-Fajardo et al., 2010) and acceptable to good intra-day reliability (Carrasco et al., 2011; Krizaj et al., 2008) of TMG. Interday reliability has been measured over three consecutive days for vastus lateralis, vastus medial and biceps femoris with good to excellent levels of reliability (Šimunicˇ, 2012). However, when intervention studies are undertaken, the evaluation of the longterm stability of specific variables is critical (Clark et al., 2007). Another important factor within TMG measurement is the capability to reliably measure mechanical and contractile properties of muscles across a number of muscle conditions, e.g., at rest, after warm-up, after a maximal voluntary contraction (MVC) and in fatigued conditions. This versatility across different measurement conditions is particularly relevant for the assessment of an exercising population, especially athletes. Muscle fatigue in particular is a widely investigated topic and in two recent studies TMG successfully detected alterations in the rectus femoris and biceps femoris muscles (García-Manso et al., 2011b) and in the biceps brachii muscle (García-Manso et al., 2012) as a result of fatigue induced
M. Ditroilo et al. / Journal of Electromyography and Kinesiology 23 (2013) 558–563
by an ultra-endurance triathlon and by resistance exercise, respectively. Yet, no information about long term inter-day reliability of the TMG parameters was documented. Accordingly, the aim of this study was to assess the long-term stability of mechanical and contractile properties of gastrocnemius medialis as measured with TMG in rested, exercised and fatigued muscle conditions. Gastrocnemius is one of the propulsive muscles fundamental to different types of human locomotion (e.g. walking, running and cycling) and is clearly measurable by TMG. The results of this reliability study could therefore assist a range of researchers and sport practitioners in tracking meaningful muscle changes as a result of training and recovery. 2. Methods 2.1. Participants Twenty-one healthy males with a mean (±SD) age, height, and mass of 21.3 ± 3.4 years, 182.0 ± 6.1 cm, 79.5 ± 10.0 kg, volunteered and gave their informed consent to participate in this study. The study was performed according to the Declaration of Helsinki and was approved by the local research ethics committee. 2.2. Experimental design Mechanical and contractile properties of the right Gastrocnemius Medialis (GM) were measured using TMG (BMC Ltd., Ljubljana). Participants were also required to undertake a warm-up, a MVC of the right plantar flexors and a protocol to fatigue the GM. As illustrated in Fig. 1, measurements were taken at a number of time points in the following order: TMG (measurement 1, M1), warm-up, TMG (M2), MVC, TMG (M3), fatigue intervention, TMG (M4). TMG measurements were recorded straight after skin marking and electrodes placement at rest (i.e. within 2 min), whereas to limit the effects of post-activation potentiation in the GM muscle (Pääsuke et al., 2007) measurement was taken 3 min after the warm-up, the performance of MVC and the fatigue intervention, which was considered to be sufficient period for the circulating Ca2+ to be transported back into the sarcoplasmic recticulum (Pääsuke et al., 2007). To assess inter-day reliability of the TMG parameters, the testing session was also repeated within 4 weeks’ time. This period was chosen to evaluate the long-term stability of the measured variables, in keeping with context of intervention studies (Clark et al., 2007). To ensure standardised conditions, participants were instructed to refrain from strenuous physical activity 24 h prior to their scheduled lab visit (always at the same time of day) and to ensure a constant hydration status they drank 500 ml of water 2 h before the start of testing.
559
2.4. TMG protocol Measurements were performed in a prone position on a padded bench with a foam pad placed just above the ankle which supported around five degrees of knee flexion (Fig. 2a). A digital displacement transducer (TMG–BMC Ltd., Ljubljana) was then placed perpendicular to the muscle belly of the right GM with a controlled initial pressure of 1.5 10 2 N/mm2. This measuring position was selected by visually and manually pulsating the GM to determine the thickest part of the muscle and then later, if needed, it was slightly adjusted to obtain the highest mechanical response with the least amount of co-activation when externally stimulated; this was typically identified by a second peak in the TMG response curve. Once chosen, this position was marked with a permanent maker pen to ensure the sensor was placed in the exact same position on subsequent measurements. The centre point of the two stimulating electrodes (5 cm2) (Axelgaard, USA) was located approximately half way from the position of the sensor (5 cm) to the start of the respective GM proximal distal tendons. After each measurement these electrodes were left in place and unplugged to avoid any possible changes in muscle response via alterations in surface electrodes distance (Tous-Fajardo et al., 2010). A single 1 ms wide stimulation pulse was delivered, which applied an initial current amplitude of 20 mA. This amplitude was progressively increased by 10 mA increments until maximal response was obtained. In order to minimise the effects of fatigue and potentiation, rest periods of 10 s were given between each mA increments. Typical maximal responses were of a stimulation amplitude between 40 and 70 mA and only the output data for that particular stimulation intensity were used for analysis. As previously documented (Šimunicˇ et al., 2011; Ditroilo et al., 2011), this stimulus is likely to evoke a low torque response, in the order of 10% of MVC. Nonetheless, the high sensitivity of the digital displacement transducer can detect muscle displacement in response to voluntary contractions up to about 68% of MVC (Pišot et al., 2008) and this is consistent with mechanomyography (Akataki et al., 2001), a similar but more established technique of analysis of muscle properties. From each maximal twitch response, five output parameters were extracted and analysed (Tous-Fajardo et al., 2010) (Fig. 2b): Displacement (Dm), the extent of maximal radial deformation (millimetre) of the muscle belly during contraction; Delay time (Td), the time taken from onset of the electrical stimulus to 10% of maximal radial displacement (millisecond); Contraction time (Tc), the time (millisecond) between 10% and 90% of maximal displacement; Sustain time (Ts), the time (millisecond) between 50% of maximal displacement during the contraction phase and 50% of maximal displacement during the relaxation phase, half relaxation time (Tr), the time (millisecond) taken to fall from 90% to 50% of maximal displacement during the relaxation phase.
2.3. Warm-up Participants warmed up by cycling at low intensity (75 W) on an electromagnetically braked cycle ergometer (Lode Ergometer, Netherlands) at a cadence between 80 and 90 rpm for a period of 5 min.
2.5. Maximal voluntary contraction (MVC) protocol Plantar flexor isometric MVC was performed in an isokinetic dynamometer (Kin-Com, Chattanooga Group Inc., USA) with the
Fig. 1. Overview of the testing protocol. TMG = tensiomyography; MVC = maximal isometric voluntary contraction;
560
M. Ditroilo et al. / Journal of Electromyography and Kinesiology 23 (2013) 558–563
Fig. 2. (a) Tensiomyography set-up with the displacement sensor and electrodes placed on gastrocnemius medialis. (b) Typical displacement/time signal recorded as a result of an electrical stimulation. Dm = maximal displacement (mm); Td = delay time (ms); Tc = contraction time (ms); Tr = relaxation time (ms); Ts = sustain time (ms).
participant having their right foot fastened securely into the plantar flexion attachment. The lever arm was lifted to an exact horizontal position using a magnetic spirit level and a 90° ankle angle to the tibia was ensured for each subject. The dynamometer position was set to ensure that the subject’s right leg was straight to maximise the involvement of the gastrocnemius muscles (and minimising soleus involvement) during plantar flexion. Participants were also held in place using two securely fastened shoulder straps and a lap belt. Following two sub-maximal warm-up sets, participants each performed a 5-s MVC of the right plantar flexors. Three trials of the MVC were completed with 60 s recovery between attempts. Participants were verbally motivated to ensure the greatest possible effort for the duration of all attempts.
2.6. Fatigue protocol The fatigue intervention consisted of a 5 min intermittent electrical stimulation of the right GM to evoke fatigue. The stimulation protocol involved continuous repeats of 15 electrical pulses (10 Hz) for a period of 1.5 s with a 1 s gap between the pulses. Participants were asked to endure the maximum current they could to ensure fatigue (110 mA). This protocol was chosen to induce low frequency fatigue which will necessitate greater recovery than high frequency fatigue (Metzger and Fitts, 1987). Furthermore, as motor unit discharge rate rarely exceeds 30 Hz during voluntary contraction the frequency we have chosen can be considered to
be more functionally relevant than using substantially higher frequencies (Allen et al., 2008).
2.7. Statistical analysis Inter-day reliability of TMG was assessed at the time points M1, M2, M3, M4 using indexes of relative and absolute reliability. Intraclass correlation coefficient (ICC) and coefficient of variation (CV) were calculated along with their 95% confidence intervals. The CV is defined as (s/mean) 100, where s is the standard deviation and mean is the mean of the change scores of the measure (Atkinson and Nevill, 1998). The ICC is defined as (V v)/V, where V is the between-subject variance averaged over the two trials analysed, and v is the within-subject square of the standard error of measurement averaged across the subjects (Weir, 2005). The standard error of measurement (SEM), defined as S (1-ICC)1/2, where S is the standard deviation of the scores from all subjects, was also calculated together with the minimum detectable change (MDC), i.e., the minimum meaningful change in a variable over time, defined as 1.96 21/2 SEM (Weir, 2005). The minimum detectable change is also expressed as a percentage: (MDC/mean of all observations) 100 (Webber and Porter, 2010). Systematic bias between the two measurements at each time point was analysed using a paired t-test (Atkinson and Nevill, 1998). Reference to a study by Tous-Fajardo et al. (2010) was applied to interpret the CV values with an analytical goal set at 10% whereas ICC was examined in conjunction with
561
M. Ditroilo et al. / Journal of Electromyography and Kinesiology 23 (2013) 558–563
CV without setting a priori criteria since it has been argued that there is no consensus in its interpretation (Weir, 2005). 3. Results CV and ICC, along with their 95% confidence intervals are reported in Table 1 for the five TMG parameters. Generally, there is an improvement in reliability when moving from M1 to M4, which is evident from the decrease in CV and the increase in ICC. Tc, Ts and Td exhibited an acceptable to good level of reliability, although the ICC is quite low for Tc and Td. Dm showed a moderate to good level of reliability with excellent ICCs. The level of reliability for the Tr parameter is insufficient with CVs around 30% and questionable levels of ICCs. Systematic bias was only detected for Dm at M1 (3.4 vs. 3.9 mm, p < 0.05) and at M2 (3.6 vs. 4.0 mm, p < 0.01) time points. Table 2 shows the SEM, MDC and %MDC for the aforementioned parameters. Similarly to the other reliability indexes, SEM decreased across the four time points of measurement. Likewise, the smallest MDC and %MDC were at time point M4. The %MDC are in the order of 15–20% for Tc, Ts, Td and Dm parameters with values as low as 9.49% and 7.33% at time point M4 for Ts and Tc, respectively. Tr displayed %MDC ranging from 44.12% to 70.11%. 4. Discussion TMG is a technique that utilises a portable device to record radial muscle belly displacement as a result of an electrical stimulus. Once it is set-up a measure can be obtained in a few seconds, therefore it is ideal to be used in a field setting and across a variety of applications as demonstrated by the growing body of literature on TMG. The aim of this study was to assess the long-term stability of a number of TMG parameters under four muscle conditions: at rest, after warm-up, after a MVC and in fatigued condition. Although CVs and ICCs yielded somehow inconsistent results, overall the parameters with the highest level of inter-day reliability are three contractile properties of the GM, namely Tc, Ts and Td. Moreover, for all parameters there was a trend towards an increase in reliability after the muscle had performed MVC and had undergone a fatigue protocol. Only Dm showed bias at two measurement points (at rest and after warm-up) indicating that the systematic error coming from the measuring device, the electrodes and probe re-placement, or the pre-measurement state of the muscle was overall low. Information about the long-term stability of TMG parameters is essential when intervention studies are undertaken in order to be able to distinguish between measurement error and real change brought about by the treatment. This is particularly relevant for TMG since the accurate re-placement of electrodes and probe can be an issue (Tous-Fajardo et al., 2010). Two previous studies have examined reliability of the same set of five TMG parameters (Tc, Ts, Tr, Td, Dm). Tous-Fajardo et al. (2010) assessed the intra- and inter-rater reliability whilst Šimunicˇ (2012) assessed the inter-day reliability over three consecutive
days. Interestingly, in both investigations Tc and Ts presented the lowest level and Tr the highest level of CV, and these findings have been confirmed in the present study. When looking at measurements taken over different days, the overall level of reliability in the study by Šimunicˇ (2012), with ICCs constantly higher than 0.87 and CVs below 10%, is much higher than in the present study. This difference in reliability measurement could mainly be attributed to the different research design, with measurements taken 1-day vs. 4-week apart, respectively. Based on the results of this study it appears that 4 weeks of time greatly reduces the consistencies between measurements, and this finding has implications in the determination of the clinically or practically important difference and the smallest worthwhile change in prospective investigations. Other factors, such as muscles examined (quadriceps vs. gastrocnemius) and subject preparation, could account for the difference in reliability between the two studies. When considering subject preparation, unlike the present study, Šimunicˇ (2012) had the participants resting supine in bed for an hour prior to measurement. Whilst this may be good practice to allow redistribution of fluids (Berg et al., 1993), this procedure may be impractical for athletes who notoriously have limited time to devote to sport testing. In other research circumstances, such as when the effect of fatigue on mechanical and contractile properties of skeletal muscle has been investigated (e.g. García-Manso et al., 2011b), the research design does not allow for any supine resting prior to measurement, therefore the protocol adopted in the present study is deemed more appropriate. Tc and Dm are the most commonly reported parameters when TMG is performed. The level of absolute (i.e. CV) and relative (i.e. ICC) reliability for either parameters did not match, with Tc presenting a good to excellent level of CV (9.4–3.8%) but poor to excellent level of ICC (0.62–0.92) and Dm showing an acceptable to questionable level of CV (8.0–14.8%) and good to excellent level of ICC (0.86–0.95). It is well known however that the two reliability indexes convey different information. CV measures the consistency of measurements within participants on different occasions, whereas ICC measures the extent to which participants maintain the same rank within the group (Atkinson and Nevill, 1998). The latter is also affected by the heterogeneity of the sample, with more heterogeneous results within the group displaying higher ICCs when all other conditions are equal (Atkinson and Nevill, 1998). Indeed, this observation could at least partially explain the apparently contradicting results within the present study. A similar difference between absolute and relative reliability is exhibited by the Ts and even more by the Td parameter, with the latter showing a good level of CV but poor ICCs. As supported by similar outcomes in other investigations (Šimunicˇ, 2012; Tous-Fajardo et al., 2010) Tr showed overall insufficient reliability (CV: 27.8–32.7%; ICC: 0.67–0.82). Thus based on the results of this study it is advised not to use this parameter when medium/long term intervention studies are carried out. Notably, for all parameters the overall level of reliability tended to increase across the four measurements, i.e. the TMG reliability is
Table 1 Coefficient of variation and intraclass correlation coefficient of the five tensiomyographic parameters analysed. CV (95% CI)
Tc Ts Tr Td Dm
ICC (95% CI)
M1
M2
M3
M4
M1
9.4 (6.3–12.5) 6.8 (3.7–9.9) 30.3 (18.2–42.4) 9.2 (5.2–12.9) 14.8 (10.4–19.3)
9.1 (6.4–11.8) 8.2 (5.0–11.3) 32.7 (18.4–47.0) 8.2 (4.2–12.3) 11.1 (7.0–15.1)
8.1 (5.4–10.8) 5.5 (3.7–7.3) 27.8 (14.5–41.1) 7.8 (3.7–11.9) 10.1 (5.0–15.2)
3.8 (2.3–5.3) 5.3 (3.1–7.6) 29.4 (19.2–39.6) 7.0 (3.2–10.8) 8.0 (5.0–11.0)
0.62 0.78 0.79 0.60 0.86
M2 (0.27–0.83) (0.54–0.91) (0.55–0.91) (0.24–0.82) (0.68–0.94)
0.63 0.71 0.67 0.56 0.91
M3 (0.28–0.83) (0.41–0.87) (0.35–0.85) (0.18–0.80) (0.79–0.96)
0.62 0.84 0.82 0.62 0.92
M4 (0.26–0.82) (0.65–0.93) (0.60–0.92) (0.27–0.83) (0.82–0.97)
0.92 0.86 0.79 0.62 0.95
CV = coefficient of variation; CI = confidence intervals; ICC = intraclass correlation coefficient; M1, M2, . . . = time point when the measurement was taken. Tc = Contraction time (ms); Ts = Sustain time (ms); Tr = half-relaxation time (ms); Td = delay time (ms); Dm = muscle displacement (mm).
(0.82–0.97) (0.70–0.94) (0.56–0.91) (0.26–0.82) (0.87–0.98)
562
M. Ditroilo et al. / Journal of Electromyography and Kinesiology 23 (2013) 558–563
Table 2 Standard error of measurement and minimum detectable change of the five tensiomyographic parameters analysed. SEM
Tc Ts Tr Td Dm
MDC
%MDC
M1
M2
M3
M4
M1
M2
M3
M4
M1
M2
M3
M4
1.36 7.00 16.03 1.34 0.30
1.36 9.01 19.07 1.52 0.26
1.18 5.83 12.88 1.27 0.21
0.61 5.59 11.73 1.16 0.19
3.77 19.41 44.44 3.72 0.84
3.77 24.96 52.86 4.21 0.72
3.28 16.16 35.70 3.53 0.58
1.68 15.49 32.50 3.20 0.51
15.79 11.84 62.95 16.41 22.07
14.95 14.26 70.11 19.05 18.19
13.70 10.27 59.33 17.15 17.13
7.33 9.49 44.12 14.98 15.05
SEM = standard error of measurement; MDC = minimum detectable change; M1, M2, . . . = time point when the measurement was taken. Tc = Contraction time (ms); Ts = Sustain time (ms); Tr = half-relaxation time (ms); Td = delay time (ms); Dm = muscle displacement (mm).
higher when the muscle is measured post-MVC or after the fatigue protocol. Although not easy to explain, it has to be considered that prior to the first measurement conditions were predominantly uncontrolled, with the exception that participants had been asked to refrain from strenuous exercise and to drink 500 ml of water 2 h before the testing session. The subsequent protocol administration, which lasted approximately 30 min, had progressively more controlled conditions, hence the improved reliability. Also, it is likely that prior to inducing fatigue the potentiation of the muscle became progressively amplified which could improve the homogeneity of the TMG response; this is considered to be appropriate methodological practice on resting muscle to ensure that muscle has achieved maximal potentiation prior to inducing any intervention (Lee and Binder-Macleod, 2000). Furthermore, the measurement taken after the fatigue protocol happened 8–10 min after the participant was resting in a prone position, which has allowed some fluid shifts to occur (Berg et al., 1993) and potentially more standardised muscle conditions. The MDC establishes the magnitude of change that represents ‘true’ change beyond measurement error and is provided in this study for each parameter measured, across the four measurements. It is useful to define MDC because it helps to interpret the effectiveness of the intervention undertaken and can assist the researcher or sport practitioner in structuring a training/recovery plan. Taken together, the results of this study suggest that for Tc, Ts, Td and Dm in most conditions changes of more than 20% are necessary to detect a real change. It is interesting to compare the overall level of long-term stability of the TMG to that of more traditional neuromuscular parameters. Clark et al. (2007) measured the neuromuscular function of plantar-flexors in seventeen young individuals before and after a 4-week control period. MVC and rate of force development, evoked muscle force and rate of force development and relaxation, electromyography, H-reflex excitability, and several more measures exhibited a CV ranging from 4.2% to 19.9% and an ICC ranging from 0.97 to 0.53. It appears that long-term stability of TMG does not differ from that of more established neuromuscular parameters. There are limitations associated with this study and technique. First, with respect to the protocol of data collection, in order to limit the effects of post-activation in the GM muscle (Pääsuke et al., 2007) the TMG measurements were taken 3 min after the administration of the fatigue protocol. Although low frequency fatigue lasts longer (Metzger and Fitts, 1987), a TMG measurement taken just after the fatigue protocol could have better characterised the induced fatigue. Second, identification of the motor point through EMG would have ensured maximal contraction of the muscle belly from the stimulation and potentially improved the reliability. However, it is important to note that TMG is intended as a field based measure; therefore such additional procedures would add a substantial amount of time and equipment making it impractical for its proposed purpose. Finally, one limitation of the TMG technique has to do with muscle displacement dynamics with respect to the low stimulus used. As mentioned in Section 2, TMG resembles mechanomyography. A study by Orizio et al. (1999) using the
latter technique has identified some potential factors that can affect the geometrical change of the stimulated muscle at low vs. high stimulation frequencies. Importantly, they demonstrated that there is relatively large muscle displacement at the low frequencies which generates low force production with the opposite outcomes at the high frequencies. Therefore, the former condition could be more relatively affected by different arrangement of the contractile elements and fibre lengths, and different behaviour of the sarcomeres and aponeurosis along the active muscle (Orizio et al., 1999). Consequently, these factors may also have affected the radial displacement of the muscle as detected by TMG. 5. Conclusions When assessing the long-term stability of five TMG parameters Tc, Ts and Td exhibited an overall good level of absolute reliability and poor to excellent level of relative reliability. On the other hand, relative reliability was good to excellent for Dm, whereas its level of absolute reliability was questionable. Tr yielded overall insufficient reliability. The MDC provided will allow to distinguish between ‘‘true’’ change and measurement error when intervention studies are undertaken. This study examined one single muscle – GM – further research could investigate long-term stability of TMG parameters measured on different muscles. 6. Conflict of interest The authors declare that they have no conflict of interest. Acknowledgements Funding for the study was provided by UK Sport, The University of Stirling, and the Sportscotland Institute of Sport. References Akataki K, Mita K, Watakabe M, Itoh K. Mechanomyogram and force relationship during voluntary isometric ramp contractions of the biceps brachii muscle. Eur J Appl Physiol 2001;84:19–25. Allen DG, Lamb GD, Westerblad H. Skeletal muscle fatigue: cellular mechanisms. Physiol Rev 2008;88:287–332. Atkinson G, Nevill AM. Statistical methods for assessing measurement error (reliability) in variables relevant to sports medicine. Sports med 1998;26:217–38. Berg HE, Tedner B, Tesch PA. Changes in lower limb muscle cross-sectional area and tissue fluid volume after transition from standing to supine. Acta Physiol Scand 1993;148:379–85. Carrasco L, Sañudo B, de Hoyo M, Pradas F, Da Silva ME. Effectiveness of lowfrequency vibration recovery method on blood lactate removal, muscle contractile properties and on time to exhaustion during cycling at VO(2max) power output. Eur J Appl Physiol 2011;111:2271–9. Clark BC, Cook SB, Ploutz-Snyder LL. Reliability of techniques to assess human neuromuscular function in vivo. J Electromyogr Kinesiol 2007;17:90–101. Dahmane R, Djordjevic S, Šimunicˇ B, Valencˇicˇ V. Spatial fiber type distribution in normal human muscle Histochemical and tensiomyographical evaluation. J Biomech 2005;38:2451–9. Dahmane R, Valencˇicˇ V, Knez N, Erzˇen I. Evaluation of the ability to make noninvasive estimation of muscle contractile properties on the basis of the muscle belly response. Med Biol Eng Comput 2001;39:51–5.
M. Ditroilo et al. / Journal of Electromyography and Kinesiology 23 (2013) 558–563 Ditroilo M, Hunter AM, Haslam S, De Vito G. The effectiveness of two novel techniques in establishing the mechanical and contractile responses of biceps femoris. Physiol Meas 2011;32:1315–26. García-Manso JM, Rodríguez-Matoso D, Rodríguez-Ruiz D, Sarmiento S, de Saa Y, Calderón J. Effect of cold-water immersion on skeletal muscle contractile properties in soccer players. Am J Phys Med Rehabil 2011;90:356–63. García-Manso JM, Rodríguez-Matoso D, Sarmiento S, de Saa Y, Vaamonde D, Rodríguez-Ruiz D, et al. Effect of high-load and high-volume resistance exercise on the tensiomyographic twitch response of biceps brachii. J Electromyogr Kinesiol 2012. García-Manso JM, Rodríguez-Ruiz D, Rodríguez-Matoso D, de Saa Y, Sarmiento S, Quiroga M. Assessment of muscle fatigue after an ultra-endurance triathlon using tensiomyography (TMG). J Sports Sci 2011;29:619–25. Hunter AM, Galloway SD, Smith IJ, Tallent J, Ditroilo M, Fairweather MM, et al. Assessment of eccentric exercise-induced muscle damage of the elbow flexors by tensiomyography. J Electromyogr Kinesiol 2012;22:334–41. Krizaj D, Šimunicˇ B, Zagar T. Short-term repeatability of parameters extracted from radial displacement of muscle belly. J Electromyogr Kinesiol 2008;18:645–51. Lee SC, Binder-Macleod SA. Effects of activation frequency on dynamic performance of human fresh and fatigued muscles. J Appl Physiol 2000;88:2166–75. Metzger JM, Fitts RH. Fatigue from high- and low-frequency muscle stimulation: contractile and biochemical alterations. J Appl Physiol 1987;62:2075–82. Orizio C, Baratta RV, Zhou BH, Solomonow M, Veicsteinas A. Force and surface mechanomyogram relationship in cat gastrocnemius. J Electromyogr Kinesiol 1999;9:131–40. Pääsuke M, Saapar L, Ereline J, Gapeyeva H, Requena B, Oöpik V. Postactivation potentiation of knee extensor muscles in power- and endurance-trained, and untrained women. Eur J Appl Physiol 2007;101:577–85. Pišot R, Narici MV, Šimunicˇ B, De Boer M, Seynnes O, Jurdana M, et al. Whole muscle contractile parameters and thickness loss during 35-day bed rest. Eur J Appl Physiol 2008;104:409–14. Rey E, Lago-Peñas C, Lago-Ballesteros J, Casáis L. The effect of recovery strategies on contractile properties using tensiomyography and perceived muscle soreness in professional soccer players. J Strength Cond Res 2011. 10.1519/ JSC.0b013e3182470d33. Šimunicˇ B. Between-day reliability of a method for non-invasive estimation of muscle composition. J Electromyogr Kinesiol 2012. 10.1016/ j.jelekin.2012.04.003. Šimunicˇ B, Degens H, Rittweger J, Narici M, Mekjavic´ IB, Pišot R. Noninvasive estimation of myosin heavy chain composition in human skeletal muscle. Med Sci Sports Exerc 2011;43:1619–25. Tous-Fajardo J, Moras G, Rodríguez-Jiménez S, Usach R, Doutres DM, Maffiuletti NA. Inter-rater reliability of muscle contractile property measurements using noninvasive tensiomyography. J Electromyogr Kinesiol 2010;20:761–6. Valencˇicˇ V, Knez N. Measuring of skeletal muscles’ dynamic properties. Artif Organs 1997;21:240–2. Webber SC, Porter MM. Reliability of ankle isometric, isotonic, and isokinetic strength and power testing in older women. Phys Ther 2010;90:1165–75. Weir JP. Quantifying test-retest reliability using the intraclass correlation coefficient and the SEM. J Strength Cond Res 2005;19:231–40.
Massimiliano Ditroilo is a lecturer in Sport and Exercise Biomechanics at University of Hull (UK). He received his PhD in Health and Performance Science from University College Dublin (Ireland) in 2012 conducting research on ‘mechanical properties of muscletendon unit and relationships with sport performance and ageing’. Other research interests include age-related decline of muscle function.
563
Iain J. Smith is a consultant in the fitness industry in Glasgow. He received his M.Phil. from University of Stirling examining the effect of a 12-week strength training and concurrent endurance cycling programme on neuromuscular activity.
Malcolm M. Fairweather is Head of Science and Innovation at sportscotland’s Institute of Sport. He received his Ph.D. in Motor Behaviour from Louisiana State University in 1994, with a research focus in applied Motor Learning and Skill Acquisition areas. His current work remit includes investigating high performance sport and coaching questions. Malcolm has explored the application of Tensiomiography measures within high performance sport environments and in partnership with Stirling University/Dr Angus Hunter over a 6 year period. This work has included both basic and applied research questions.
Angus M. Hunter is a Senior Lecturer in Exercise Physiology at University of Stirling, Scotland, UK. He received his Doctoral degree from University of Cape Town, in the Physiology of Exercise examining various manipulations on neural fatigue. His current research interests include neuromuscular control and adaptation for both high performance sport and clinical patient mobility.