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Surface Electromyographic Activities of Upper Body Muscles during Highintensity Cycle Ergometry ab
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Marie Clare McCormick , Hugh Watson , Alan Simpson , Lon Kilgore & Julien S Baker
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Institute of Clinical Exercise and Health Science, Exercise Science Research Laboratory, School of Science, Faculty of Science and Technology, University of the West of Scotland, Hamilton ML3 OJB, UK b
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Division of Sport and Exercise Sciences, School of Social & Health Sciences, University of Abertay, Bell Street, Dundee DD1 1HG, UK c
Institute of Clinical Exercise and Health Science, Exercise Science Research Laboratory, School of Science, Faculty of Science and Technology, University of the West of Scotland, Hamilton, Scotland, ML3 OJB, UK Published online: 21 Mar 2014.
To cite this article: Marie Clare McCormick, Hugh Watson, Alan Simpson, Lon Kilgore & Julien S Baker (2014) Surface Electromyographic Activities of Upper Body Muscles during High-intensity Cycle Ergometry, Research in Sports Medicine: An International Journal, 22:2, 124-135, DOI: 10.1080/15438627.2014.881817 To link to this article: http://dx.doi.org/10.1080/15438627.2014.881817
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Research in Sports Medicine, 22:124–135, 2014 Copyright © Taylor & Francis Group, LLC ISSN: 1543-8627 print/1543-8635 online DOI: 10.1080/15438627.2014.881817
Surface Electromyographic Activities of Upper Body Muscles during High-intensity Cycle Ergometry
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MARIE CLARE MCCORMICK Institute of Clinical Exercise and Health Science, Exercise Science Research Laboratory, School of Science, Faculty of Science and Technology, University of the West of Scotland, Hamilton ML3 OJB, UK; and Division of Sport and Exercise Sciences, School of Social & Health Sciences, University of Abertay, Bell Street, Dundee DD1 1HG, UK
HUGH WATSON, ALAN SIMPSON, LON KILGORE, and JULIEN S BAKER Institute of Clinical Exercise and Health Science, Exercise Science Research Laboratory, School of Science, Faculty of Science and Technology, University of the West of Scotland, Hamilton, Scotland, ML3 OJB, UK.
The aim of this study was to investigate upper body muscle activity during a 30 s Wingate test. Eighteen physically active participants performed a Wingate test while muscle activity was recorded from the brachioradialis (BR), biceps brachii (BB), triceps brachii (TB) and upper trapezius (UT). Measurements were obtained at rest, during a function maximal contraction (FMC) and during the 30 s Wingate test, whilst participants were positioned in a seated position on the cycle ergometer. All muscles were significantly active for the duration of the test. When normalized as a %FMC no differences in activity were found between muscles. Across the 30 s, power output was found to significantly decrease, whereas no changes were found in upper body muscle activity. All muscles investigated were active during the Wingate test and therefore
Received 11 February 2013; accepted 19 August 2013. No sources of funding were used to assist in the preparation of this study. The authors are grateful to the participants for their involvement in this study. All of the authors have no conflicts of interest. Address Corresponding to Marie Clare McCormick, Institute of Clinical Exercise and Health Science, Exercise Science Research Laboratory, School of Science, Faculty of Science and Technology, University of the West of Scotland, Hamilton ML3 OJB, UK. Email: marieclare. [email protected] 124
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confirmed previous findings that the upper body significantly contributes to power profiles obtained during high intensity cycle ergometry in addition to its role in stabilizing the body. KEYWORDS anaerobic power, cycle ergometry, electromyography
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INTRODUCTION High intensity cycle ergometry is widely used to assess indices of muscular performance during maximal exercise (Baker, Gal, Davies, Bailey, & Morgan, 2001). Recently the potential contribution of the upper extremities and trunk muscles to cycling has been recognized (Gregor & Concomi, 2000) with research suggesting that, via the handlebar grip, there is a contribution to power production from the upper body (Baker & Davies, 2009; Baker et al., 2001, 2002). Surface electromyography (sEMG) data suggests that during high intensity cycle ergometry with a normal handlebar grip, the amplitude of the sEMG signal of the forearm musculature is similar, if not greater than, the signal amplitude during a 100% maximum voluntary contraction (MVC) (Baker et al., 2001). It has been suggested that articulation with the handlebar allows the upper body to isometrically stabilize body position and pull the body downward to help overcome the high resistive loads during cycle ergometry so providing a counterbalancing force for the lower limbs (Baker, Thomas & Davies, 2009) and that the hand, arm, shoulder and abdomen form a muscular sling that rhythmically moves back and forth in supporting the trunk and pelvis during cycling (Schmidt, 1994). Furthermore, research supports the use of a firm handgrip to help maintain body position relative to the ergometer, thus ensuring that the forces generated when forcefully extending the hips and legs are efficiently directed at rotation of the pedals (Baker & Davies, 2009). It is known that the lower body muscles primarily involved in power production are the vastus lateralis and vastus medialis (Blake, Champoux, & Wakeling, 2012). However, as little attention has been given to the effect of the upper body musculature on high intensity cycle ergometer performance, it is currently unknown which muscles or muscle groups of the upper body contribute most to the task. During high intensity cycle ergometry the brachioradialis (BR) acts as a pronator/supinator and elbow flexor that likely assists with maintaining grip position. The biceps brachii (BB) flexes the elbow while the triceps brachii (TB) acts to hold the elbow in extension and adducts the shoulder in normal cycling posture. The upper segment of the trapezius (UT) elevates the scapulae, assists in isometrically holding the scapulae and stabilizes the glenohumeral and acromioclavicular joints – both important in maintaining body position on a bike (Martini, 2006). Based on the roles of these superficial muscles, the present study used sEMG to describe the activity of the BR, BB, TB and UT during a 30 s Wingate test. It was
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hypothesized that sEMG would reveal significantly upper body activation, which would not be directly related to power output during the 30 s test.
METHODOLOGY
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Participants Eighteen healthy, physically active individuals who were not trained cyclists (nine male 24.1 ± 3.3 yrs; 178.7 ± 7.1 cm; 74.2 ± 12.3 kg and nine female 25.3 ± 5.6 yrs; 167.1 ± 7.9 cm; 61.5 ± 7.1 kg) volunteered to participate in the study. Body mass and stature were measured prior to testing and recorded to the nearest 0.1 kg and 0.1 cm respectively. All participants completed an informed consent form and medical history questionnaire and all methods used were approved by the university ethical committee. Any individuals with a history of cardiovascular/cardiorespiratory illness were excluded from the study. Prior to experimental testing, all participants were familiarized with high intensity cycle ergometry testing and the baseline isometric contractions. Participants were instructed to maintain their normal diet during the days leading up to and on the days of testing. To avoid dehydration they were asked to refrain from vigorous exercise and avoid the consumption of caffeine and alcohol during the 24 hours preceding the testing date. Food was not consumed during testing and water was available ad libitum.
Surface Electromyography Muscle activity was recorded via sEMG from the BR, BB, TB and UT on the right-hand side of the body (Gonzalez-Izal et al., 2010). Prior to electrode placement, skin was shaved, lightly abraded and cleaned with alcohol. Pregelled (Ag-AgCl) bipolar surface electrodes (Blue Sensor, Ambu, Ballerup, DK) were placed over the belly of each muscle with a distance of 25 mm between the electrodes’ centres. The grounding electrode was placed over the left ulnar styloid process and the skin marked with a permanent marker following the familiarization session, to ensure electrodes were placed in the same position in the subsequent testing session. sEMG signals were pre-amplified (×1000) (Neurolog remote AC preamplifier, NL824, Digitimer Ltd, Hertfordshire, UK), filtered (10–500 Hz) (Neurolog filter, NL125, Digitimer Ltd, Hertfordshire, UK), converted from analogue to digital signal (Power 1401, Cambridge Electronic Design, Cambridge, UK) and sampled at a rate of 2000 Hz.
sEMG Baseline Measurements During the first testing session, baseline muscle activity of the BB, BR, TB and UT was recorded from participants at rest. All measurements were obtained
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while participants were seated on the cycle ergometer with a standard overhand grip on the handlebar, identical to body position during the cycle ergometer test. To allow EMG data to be normalized, muscle activity was also recorded during a functional maximal contraction (FMC) using joint angles specific to the activity for all four muscles. Each isometric FMC lasted 2–3 s with a rest interval of 60 s between the three trials. The highest output served as the reference maximal contraction. The FMCs were recorded with participants positioned in a seated position with no leg movement. The FMC of the BR was obtained through a maximal handgrip on the handlebar. To execute FMC of the BB and TB, participants pulled and pushed, maximally upon the handlebars. UT FMC was accomplished by an isometric shoulder shrug against an isometric and antagonistic latissimus dorsi co-contraction, balancing shoulder elevation and depression. EMG activity during the FMCs served as reference standards to assess relative activity of the musculature during cycle ergometry. Muscle activity during the 30 s Wingate test was normalized by calculating it as a percentage of FMCs.
Cycle Ergometer Protocol During the second testing session, participants completed one 30 s Wingate test, while sEMG recorded muscle activity from the BR, BB, TB and UT. A Monark 894E Peak cycle ergometer (Monark, Vansbro, SWE) was used for all experimental testing. The cycle ergometer was connected to a PC to allow for data capture via the Monark anaerobic test software (version 2.24.2). Saddle height was adjusted for each participant, ensuring the knee remained slightly flexed at the completion of the power stroke (approximately 170–175° at extension). Toe clips were used to ensure that the participants’ feet were held firmly in place and in contact with the pedals throughout the tests. All participants completed a standardized warm up protocol, pedalling for 3 minutes at 60 rpm with a 2 kg flywheel resistance. During the Wingate protocol participants were instructed to remain seated in the saddle for the duration of the test and maintain a standard overhand handlebar grip. They were given a rolling start of approximately 5 s to generate an unloaded acceleration of pedal cadence to 60 rpm. At 60 rpm the weight basket automatically dropped and participants pedalled with maximum effort for a period of 30 s against a fixed resistive load of 75 grams per kilogram total body mass (7.5% of body mass) (Bar-Or, 1987). Verbal encouragement was given equitably to each participant in all testing.
Data Processing All sEMG data were processed using WinEDR V3.1.9 (Dr John Dempster, University of Strathclyde, Glasgow, UK). Root mean square (RMS) values were calculated by the following formula; T = 1 s
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Z RMS ¼ ½jmðt Þj ¼ 1=T
tþT
1=2 m ðt Þdt 2
(1)
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The calculated RMS values were used to describe signal amplitude as an estimate of muscle activity at rest, during isometric FMCs and during the Wingate tests. Data are presented as RMS (±SD).
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Statistical Analysis Statistically analysis was performed using Statistical Package for Social Sciences (SPSS) software (Version 18) (IBM, Armonk, NY, USA). Normality of data distribution was tested by a Shapiro-Wilk’s test. Between-group differences were calculated using a repeated measures analysis of variance (ANOVA). Multiple comparisons on paired data were made using a paired t-test or Wilcoxon test. A paired t-test was used to identify differences in muscle activity at rest and during a FMC. Data collected during the Wingate test were non-parametric, therefore a Wilcoxon test was used to identify differences in muscle activity at rest and during a Wingate test and muscle activity during a FMC and during a Wingate test. A related-samples Friedman’s Two-Way ANOVA with subsequent pairwise comparisons was used to assess any changes in muscle activity over the 30 s Wingate test. A repeated measure ANOVA with subsequent Bonferonni post-hoc analysis was used to determine changes in power output over the duration of the test. Relationships between upper body limb activity (RMS) and power output were assessed using Spearman’s correlation coefficient. Statistical significance was set a priori at P < 0.05. All data is presented as mean ±SD.
RESULTS No differences were found between groups with regards to muscle activity, therefore male and female data was subsequently analysed as one group.
Processed sEMG Muscle activity in all four muscles, represented by sEMG amplitude (RMS), during the FMCs and Wingate test was significantly greater than muscle activity recorded at rest on the cycle ergometer (P < 0.001; P < 0.05 respectively). Muscle activity during the FMCs was significantly greater than muscle activity during the 30 s Wingate test, this was similar for all muscles (P < 0.05) (Table 1).
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TABLE 1 Muscle activity, represented by sEMG amplitude (RMS) at rest, during a FMC (functional maximal contraction) and average muscle activity recorded at 5 s intervals during the Wingate test. Values are group mean RMS (±SD) Rest BR BB TB UT
0.07 0.09 0.09 0.02
± ± ± ±
0.08a 0.09a 0.04a 0.01a
FMC 1.34 1.02 0.65 0.53
± ± ± ±
0.71b 0.62b 0.35b 0.37b
0–5 s 0.46 0.23 0.35 0.21
± ± ± ±
0.27 0.12 0.23 0.13
5–10 s 0.38 0.22 0.32 0.27
± ± ± ±
0.16 0.10 0.21 0.20
10–15 s 0.49 0.23 0.31 0.26
± ± ± ±
0.35 0.11 0.20 0.15
15–20 s 0.46 0.22 0.34 0.22
± ± ± ±
0.32 0.15 0.26 0.12
20–25 s 0.45 0.23 0.36 0.21
± ± ± ±
0.31 0.14 0.26 0.13
25–30 s 0.31 0.15 0.36 0.16
± ± ± ±
0.19 0.06 0.24 0.11
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a Resting values significantly lower than values recorded during FMC and at all time intervals during the 30 sWingate test; bMVE significantly greater than muscle activity recorded during 30sWingate test (P < 0.05).
Normalized values for sEMG amplitude, using a 1 s window, were obtained at sequential 5 s intervals during the Wingate test. There were no significant changes in signal amplitude over the duration of the test for the BR (P = 0.413), BB (P = 0.256), TB (P = 0.855). However, signal amplitude did change over time in the UT (P = 0.01) with muscle activity being significantly greatly at 10–15 s than at 25–30 s (Figure 1). Between-muscle differences were assessed using normalized values and only the TB was relatively more active compared with the BB at each time point (%FMC) (P < 0.05). There were no other differences between muscles (P > 0.05).
FIGURE 1 Muscle activity displayed as a percentage of the functional maximal contraction (FMC) at sequential 5 s interval across the 30 s Wingate test. No significant differences were found across the 30 s period (P > 0.05).
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Power Output Power output (W/kg) was averaged at 5 s intervals. No significant differences were found between power output at 0–5 s (8.86 ± 2.01 W/kg) and 5–10 s (8.89 ± 1.61 W/kg) (P = 1.00) and no differences between power output at 0–5 and 10–15 s (P = 0.068). Power output at 0–5 s and 5–10 s was significantly higher than at 15–20 s; 20–25 s and 25–30 s (7.79 ± 1.17; 6.97 ± 1.01; 6.27 ± 0.81; 5.70 ± 0.83 W/kg respectively) (P < 0.01). At 5–10 s power output was also significantly greater than at 10–15 s (P < 0.01). Each subsequent sequential power output from 10–15 s to 25–30 s was significantly lower than the preceding time interval (p < 0.05), highlighting the progressive decline in power output over the 30 s Wingate test. There was no correlation between upper body muscle activity and power output across the 30 s Wingate test (p > 0.05).
Raw sEMG The raw sEMG signal obtained from a selected participant during the Wingate test demonstrates very regular and sequential bursts of activity for the duration of the test. Generally, BR and BB activation was followed immediately by TB activation, as highlighted in Figure 2. It also highlights the clear regular bursts of muscle activation representing the cyclic pulling and pushing actions upon the handlebars.
5.0 2.5 BR 0.0 –2.5 –5.0 5.0 2.5 BB 0.0 –2.5 –5.0 5.0 2.5 TB 0.0 –2.5 –5.0 5.0 2.5 UT 0.0 –2.5 –5.0
FIGURE 2 Section of the sEMG signal of a participant recorded during a 30 s Wingate test. Dashed lines highlight the co-contraction of the BR and BB, immediately followed by TB activation. BR, brachioradialis; BB, biceps brachii, TB, triceps brachii; UT, upper trapezius.
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DISCUSSION The principle aim of this investigation was to explore upper body muscle activity during high intensity cycle ergometry using sEMG. Baker and colleagues (2001, 2002, 2009) previously established a relationship between power output and handlebar grip suggesting that the upper body musculature significantly contributes to power output during high intensity cycle ergometry. While handlebar grip has been examined, identification of the muscles of the upper body contributing to the lower body power transfer has only been speculated. The muscles investigated in the present study were the BR, BB, TB and UT. All four muscles investigated were found to be significantly more active during cycling compared to resting values obtained while seated on the cycle ergometer (p < 0.05) but less active than during a FMC (p < 0.01). This therefore confirms the previous suggestion that during the Wingate test, the upper body muscles are contributing to power output but also that they are not contracting maximally. The amplitude of the EMG signal, reported as RMS of the EMG, was used within the present investigation to describe muscular activity (Jobson, Hopker, Arkesteijn, & Passfield, 2012). Signal amplitude has been used as an estimate of muscle activity as both the force exerted by the muscle and the amplitude of the EMG signal have been reported to depend on the number of recruited motor units (MU) and the firing rate of each active MU (Vollestad, 1997). An increase in the amplitude of the sEMG signal is often observed during repetitive or sustained submaximal contractions (Vollestad, 1997) and has been attributed to both the recruitment of additional MUs to compensate for the decrease in contraction force and to an increase in the MU firing rate and/or synchronization of MU recruitment (Dimitrova & Dimitrov, 2002). Numerous authors have reported findings in agreement with this and have demonstrated an increase in amplitude during both sustained and dynamic sub-maximal isometric contractions (Arendt-Nielsen & Mills, 1988; Lloyd, 1971; Macdonald, Farina, & Marcora, 2008; Masuda, Masuda, Sadoyama, Inaki, & Katsuta, 1999; Moritani, Nagata, & Muro, 1982; Potvin & Bent, 1997). More recently, Fukuda et al. (2010) demonstrated a positive linear relationship between contraction force and RMS of the sEMG signal, further highlighting the association between force production and amplitude. However, in the present study there were no changes in signal amplitude over the 30 s test, measured at 5 s intervals, for any of the four muscles investigated (P > 0.05). This reflects the sub-maximal intermittent nature of the upper body contractions and therefore suggests that there is no increase in muscle force as the sprint progresses. The lack of changes in muscle force production in the upper body may be related to the oscillatory nature of cycling, which implies that agonist and antagonist muscles are able to share the workload, with no requirements to recruit additional MUs to maintain the contraction force. Furthermore, with the muscles being intermittently active,
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hyperaemia will be able to provide the muscles with sufficient oxygen to maintain aerobic energy metabolism and therefore prevent possible energy depletion and/or metabolite accumulation (Jobson et al., 2012). Similar to the findings of the present study, Hunter and colleagues (2003) found no change in signal amplitude in the lower limbs during a similar protocol. They suggested this may be a result of insufficient afferent command from type III and IV receptors to the central nervous system, reducing central drive and a resulting change in EMG amplitude. Although unlikely to be a valid explanation for the results of the present study, it highlights the variability of sEMG analysis. The results therefore suggest acceptance of the null hypothesis as upper body muscle contraction did not change over the duration of the sprint despite a significant decline in power output (W/kg), which is indicative of a decrease in overall cycling performance. The submaximal nature of the upper body contractions, as demonstrated in the sEMG data, confirm the previous suggestion that the primary function of the upper body is to stabilize body position and provide a counterbalancing force for the lower limbs. However, in real-world cycling performance, there may be a greater activation of the upper body musculature, in particular in a standing position, where the upper body and trunk muscles are supporting additional weight due to the loss of saddle support, in order to control balance and to swing both the body and bicycle side to side (Duc, Bertucci, Pernin, & Grappe, 2008). The large inter-participant variability in the present study (a common finding in sEMG analysis), indicated by large standard deviations throughout the data, make it difficult to determine an objective quantitative relationship between upper body activity and high intensity cycle ergometry performance (Figure 1). This variability is further increased due to the nature of cycling where muscle activity and co-ordination can differ considerably between individuals (Blake, Champoux, & Wakeling, 2012), particularly as the individuals within this study were not trained cyclists. However, as an exploratory investigation, visual inspection of the raw EMG data may provide the most pertinent insight into muscle activity. Raw EMG recording contains important information and therefore can be used as a first understanding of neuromuscular control during exercise (So, Ng & Ng, 2005). The raw EMG signal (Figure 2) recorded during the present study demonstrates a linkage to the oscillatory nature of cycling. The bursts of activity are representative of the alternate pushing and pulling motions upon the handlebars (Baker et al., 2001) and may also provide some valuable information relating to the working phase of the muscle with respect to the three crank phases as described by So et al., (2005), as the downstroke (propulsive), the upstroke (recovery) and the pulling phase where the foot is pushed forward at top dead centre. Observations of participants during the cycle ergometer test revealed that in general the bursts of activity observed on the EMG trace in the TB occur during the upstroke of the leg (due to elbow
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extension) and the bursts of activity in the BR and BB generally occur at the same time during the downstroke of the leg (due to elbow flexion) (Figure 2). No clear pattern emerged from the UT data and this may be due to its role as a tonic muscle that is associated with stabilization during exercise. This warrants further investigation combining sEMG and biomechanical analysis. Every effort was made to control for the limiting factors commonly associated with the outcomes of sEMG analysis (De Luca, 1997). The effect of subcutaneous tissue layers acting as low pass filters, so influencing signal conduction (Pincivero, Green, Mark & Campy, 2000) is one factor. Minor electrode displacement causing sEMG to be recorded from different muscle locations can also affect the signal due to the heterogeneity of muscle fibres (Rainoldi, Melchiorri & Caruso, 2004), alongside muscle crosstalk producing electrical activity that artifactually registers on the sEMG thus amplifying the recorded muscle’s activity. This may be a particular problem in the BR due its close proximity to several other small forearm muscles (Kong, Hallbeck & Jung, 2010).
CONCLUSION It is clear that all muscles investigated were active during the 30 s Wingate test and therefore have a considerable role in optimal high intensity cycling performance. Therefore, when using high-intensity cycle ergometry as a test of muscular performance it is important that investigators consider the potential influences of the upper body to the power outputs achieved, through both the handlebar grip and position of the trunk. Handlebar grip should therefore be standardized in any experimental procedures. Further investigation is necessary to fully quantify the contribution of the upper body relative to power output and to evaluate the relative contributions of both the abdominal and back musculature. In terms of real world cycling performance cyclists and their coaches should not underestimate the importance of establishing a strength base in the upper body to support cycling performance both in training and competition. The upper body is likely to be particularly influential during sustained uphill climbs where there is a continued high resistance that cannot be overcome.
REFERENCES Arendt-Nielsen, L., & Mills, K. R. (1988). Muscle fibre conduction velocity, mean power frequency, mean EMG voltage and force during submaximal fatiguing contractions of human quadriceps. European Journal of Applied Physiology and Occupational Physiology, 58, 20–25. Baker, J. S., & Davies, B. (2009a). Additional considerations and recommendations for the quantification of hand-grip strength in the measurement of leg power during high intensity cycle ergometry. Research in Sports Medicine, 17, 145–155.
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Baker, J. S., Brown, E., Hill, G., Philips, G., & Davies, B. (2002). Handgrip contribution to lactate production and leg power during high intensity exercise. Medicine and Science in Sport and Exercise, 34(6), 1037–1040. Baker, J. S., Gal, J., Davies, B., Bailey, D., & Morgan, R. (2001). Power output of legs during high intensity cycle ergometry: Influence of hand grip. Journal of Sports Science, 4(1), 10–18. Baker, J. S., Thomas, N. E., & Davies, B. (2009). Physiological, biomechanical and mechanical issues relating to force selection during high intensity cycle ergometer performance. Journal of Exercise Science & Fitness, 7(2), s51–s60. Bar-Or, O. (1987). The Wingate anaerobic test. An update on methodology, reliability and validity. Sports Medicine, 4, 381–394. Blake, A. M., Champoux, Y., & Wakeling, J. M. (2012). Muscle coordination patterns for efficient cycling. Medicine and Science in Sport and Exercise, 44(5), 926–938. De Luca, C, J. (1997). The use of surface electromyography in biomechanics. Journal of Applied Biomechanics, 13, 135–163. Dimitrova, N. A., & Dimitrov, G. V. (2002). Amplitude-related characteristics of motor unit and M-wave potentials during fatigue. A simulation study using literature data on intracellular potential changes found in vitro. Journal of Electromyography and Kinesiology, 12(5), 339–349. Duc, S., Bertucci, W., Pernin, J. N., & Grappe, F. (2008). Muscular activity during uphill cycling: effect of slope, posture, hand grip position and constrained bicycle lateral sways. Journal of Electromyography and Kinesiology, 18(1), 116–127. Fukuda, T. Y., Echeimberg, J. O., Pompeu, J. E., Lucareli, P. R. G., Garbelotti, S., Gimenes, R. O., & Apolinário, A. (2010). Root mean square value of the electromyographic signal in the isometric torque of the quadriceps. Hamstrings and brachial biceps muscles in female subjects. Journal of Applied. Research, 10(1), 32–39. González-Izal, M., Malanda, A., Navarro-Amézqueta, I., Gorostiaga, E. M., Mallor, F., Ibañez, J., & Izquierdo, M. (2010). EMG spectral indices and muscle power fatigue during dynamic contractions. Journal of Electromyography and Kinesiology, 20(2), 233–240. Gregor, R. J., & Concomi, F. (2000). Road Cycling. Oxford: Blackwell Science. Hunter, A. M., Gibson, A. S. C., Lambert, M. I., Nobbs, L., & Noakes, T. D. (2003). Effects of supramaximal exercise on the electromyographic signal. British Journal of Sports Medicine, 37(4), 296–299. Jobson, S. A., Hopker, J., Arkesteijn, M., & Passfield, L. (2012). Inter- and intra-session reliability of muscle activity patterns during cycling. Journal of Electromyography and Kinesiology, http://dx.doi.org/10.1016/j.jelekin.2012.08.013 Kong, Y. K., Hallbeck, M. S., & Jung, M. C. (2010). Crosstalk effect on surface electromyogram of the forearm flexors during a static grip task Journal of Electromyography Kinesiology, 20(6), 1223–1229. Lloyd, A. J. (1971). Surface electromyography during sustained isometric contraction. Journal of Applied Physiology, 30, 713–719. Macdonald, J. H., Farina, D., & Marcora, S. M. (2008). Response of electromyographic variables during incremental and fatiguing cycling. Medicine and Science in Sports and Exercise, 40(2), 335–344.
Downloaded by [George Washington University] at 11:40 23 February 2015
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Martini, F. H. (2006). Fundamentals of Anatomy and Physiology (7th ed.) San Francisco: Pearson Education. Masuda, K., Masuda, T., Sadoyama, T., Inaki, M., & Katsuta, S. (1999). Changes in surface EMG parameters during static and dynamic fatiguing contractions. Journal of Electromyography and Kinesiology, 9(1), 39–46. Moritani, T., Nagata, A., & Muro, M. (1982). Electromyographic manifestations of muscular fatigue. Medicine and Sciemce in Sports and Exercise, 14(3), 198–202. Pincivero, D. M., Green, R. C., Mark, J. D., & Campy, R. M. (2000). Gender and muscle differences in EMG amplitude and median frequency, and variability during maximal voluntary contractions of the quadriceps femoris. Journal of Electromyography and Kinesiology, 10(3), 189–196. Potvin, J. R., & Bent, L. R. (1997). A validation of techniques using surface EMG signals from dynamic contractions to quantify muscle fatigue during repetitive tasks. Journal of Electromyography and Kinesiology, 7(2), 131–139. Rainoldi, A., Melchiorri, G., & Caruso, I. (2004). A method for positioning electrodes during surface EMG recordings in lower limb muscles. Journal of Neuroscience Methods, 134(1), 37–43. Schmidt, A. (1994). Handbook of Competitive Cycling: Training, Keep Fit, Tactics. Oxford: Meyer & Meyer. So, R. C. H., Ng, J. K. F., & Ng, G. Y. F. (2005). Muscle recruitment in cycling: a review. Physical Therapy in Sport, 6, 89–96. Vollestad, N. K. (1997). Measurement of human muscle fatigue. Journal of Neuroscience Methods, 74, 219–227.
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Surface Electromyographic Activities of Upper Body Muscles during Highintensity Cycle Ergometry ab
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Marie Clare McCormick , Hugh Watson , Alan Simpson , Lon Kilgore & Julien S Baker
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a
Institute of Clinical Exercise and Health Science, Exercise Science Research Laboratory, School of Science, Faculty of Science and Technology, University of the West of Scotland, Hamilton ML3 OJB, UK b
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Division of Sport and Exercise Sciences, School of Social & Health Sciences, University of Abertay, Bell Street, Dundee DD1 1HG, UK c
Institute of Clinical Exercise and Health Science, Exercise Science Research Laboratory, School of Science, Faculty of Science and Technology, University of the West of Scotland, Hamilton, Scotland, ML3 OJB, UK Published online: 21 Mar 2014.
To cite this article: Marie Clare McCormick, Hugh Watson, Alan Simpson, Lon Kilgore & Julien S Baker (2014) Surface Electromyographic Activities of Upper Body Muscles during High-intensity Cycle Ergometry, Research in Sports Medicine: An International Journal, 22:2, 124-135, DOI: 10.1080/15438627.2014.881817 To link to this article: http://dx.doi.org/10.1080/15438627.2014.881817
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Research in Sports Medicine, 22:124–135, 2014 Copyright © Taylor & Francis Group, LLC ISSN: 1543-8627 print/1543-8635 online DOI: 10.1080/15438627.2014.881817
Surface Electromyographic Activities of Upper Body Muscles during High-intensity Cycle Ergometry
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MARIE CLARE MCCORMICK Institute of Clinical Exercise and Health Science, Exercise Science Research Laboratory, School of Science, Faculty of Science and Technology, University of the West of Scotland, Hamilton ML3 OJB, UK; and Division of Sport and Exercise Sciences, School of Social & Health Sciences, University of Abertay, Bell Street, Dundee DD1 1HG, UK
HUGH WATSON, ALAN SIMPSON, LON KILGORE, and JULIEN S BAKER Institute of Clinical Exercise and Health Science, Exercise Science Research Laboratory, School of Science, Faculty of Science and Technology, University of the West of Scotland, Hamilton, Scotland, ML3 OJB, UK.
The aim of this study was to investigate upper body muscle activity during a 30 s Wingate test. Eighteen physically active participants performed a Wingate test while muscle activity was recorded from the brachioradialis (BR), biceps brachii (BB), triceps brachii (TB) and upper trapezius (UT). Measurements were obtained at rest, during a function maximal contraction (FMC) and during the 30 s Wingate test, whilst participants were positioned in a seated position on the cycle ergometer. All muscles were significantly active for the duration of the test. When normalized as a %FMC no differences in activity were found between muscles. Across the 30 s, power output was found to significantly decrease, whereas no changes were found in upper body muscle activity. All muscles investigated were active during the Wingate test and therefore
Received 11 February 2013; accepted 19 August 2013. No sources of funding were used to assist in the preparation of this study. The authors are grateful to the participants for their involvement in this study. All of the authors have no conflicts of interest. Address Corresponding to Marie Clare McCormick, Institute of Clinical Exercise and Health Science, Exercise Science Research Laboratory, School of Science, Faculty of Science and Technology, University of the West of Scotland, Hamilton ML3 OJB, UK. Email: marieclare. [email protected] 124
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confirmed previous findings that the upper body significantly contributes to power profiles obtained during high intensity cycle ergometry in addition to its role in stabilizing the body. KEYWORDS anaerobic power, cycle ergometry, electromyography
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INTRODUCTION High intensity cycle ergometry is widely used to assess indices of muscular performance during maximal exercise (Baker, Gal, Davies, Bailey, & Morgan, 2001). Recently the potential contribution of the upper extremities and trunk muscles to cycling has been recognized (Gregor & Concomi, 2000) with research suggesting that, via the handlebar grip, there is a contribution to power production from the upper body (Baker & Davies, 2009; Baker et al., 2001, 2002). Surface electromyography (sEMG) data suggests that during high intensity cycle ergometry with a normal handlebar grip, the amplitude of the sEMG signal of the forearm musculature is similar, if not greater than, the signal amplitude during a 100% maximum voluntary contraction (MVC) (Baker et al., 2001). It has been suggested that articulation with the handlebar allows the upper body to isometrically stabilize body position and pull the body downward to help overcome the high resistive loads during cycle ergometry so providing a counterbalancing force for the lower limbs (Baker, Thomas & Davies, 2009) and that the hand, arm, shoulder and abdomen form a muscular sling that rhythmically moves back and forth in supporting the trunk and pelvis during cycling (Schmidt, 1994). Furthermore, research supports the use of a firm handgrip to help maintain body position relative to the ergometer, thus ensuring that the forces generated when forcefully extending the hips and legs are efficiently directed at rotation of the pedals (Baker & Davies, 2009). It is known that the lower body muscles primarily involved in power production are the vastus lateralis and vastus medialis (Blake, Champoux, & Wakeling, 2012). However, as little attention has been given to the effect of the upper body musculature on high intensity cycle ergometer performance, it is currently unknown which muscles or muscle groups of the upper body contribute most to the task. During high intensity cycle ergometry the brachioradialis (BR) acts as a pronator/supinator and elbow flexor that likely assists with maintaining grip position. The biceps brachii (BB) flexes the elbow while the triceps brachii (TB) acts to hold the elbow in extension and adducts the shoulder in normal cycling posture. The upper segment of the trapezius (UT) elevates the scapulae, assists in isometrically holding the scapulae and stabilizes the glenohumeral and acromioclavicular joints – both important in maintaining body position on a bike (Martini, 2006). Based on the roles of these superficial muscles, the present study used sEMG to describe the activity of the BR, BB, TB and UT during a 30 s Wingate test. It was
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hypothesized that sEMG would reveal significantly upper body activation, which would not be directly related to power output during the 30 s test.
METHODOLOGY
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Participants Eighteen healthy, physically active individuals who were not trained cyclists (nine male 24.1 ± 3.3 yrs; 178.7 ± 7.1 cm; 74.2 ± 12.3 kg and nine female 25.3 ± 5.6 yrs; 167.1 ± 7.9 cm; 61.5 ± 7.1 kg) volunteered to participate in the study. Body mass and stature were measured prior to testing and recorded to the nearest 0.1 kg and 0.1 cm respectively. All participants completed an informed consent form and medical history questionnaire and all methods used were approved by the university ethical committee. Any individuals with a history of cardiovascular/cardiorespiratory illness were excluded from the study. Prior to experimental testing, all participants were familiarized with high intensity cycle ergometry testing and the baseline isometric contractions. Participants were instructed to maintain their normal diet during the days leading up to and on the days of testing. To avoid dehydration they were asked to refrain from vigorous exercise and avoid the consumption of caffeine and alcohol during the 24 hours preceding the testing date. Food was not consumed during testing and water was available ad libitum.
Surface Electromyography Muscle activity was recorded via sEMG from the BR, BB, TB and UT on the right-hand side of the body (Gonzalez-Izal et al., 2010). Prior to electrode placement, skin was shaved, lightly abraded and cleaned with alcohol. Pregelled (Ag-AgCl) bipolar surface electrodes (Blue Sensor, Ambu, Ballerup, DK) were placed over the belly of each muscle with a distance of 25 mm between the electrodes’ centres. The grounding electrode was placed over the left ulnar styloid process and the skin marked with a permanent marker following the familiarization session, to ensure electrodes were placed in the same position in the subsequent testing session. sEMG signals were pre-amplified (×1000) (Neurolog remote AC preamplifier, NL824, Digitimer Ltd, Hertfordshire, UK), filtered (10–500 Hz) (Neurolog filter, NL125, Digitimer Ltd, Hertfordshire, UK), converted from analogue to digital signal (Power 1401, Cambridge Electronic Design, Cambridge, UK) and sampled at a rate of 2000 Hz.
sEMG Baseline Measurements During the first testing session, baseline muscle activity of the BB, BR, TB and UT was recorded from participants at rest. All measurements were obtained
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while participants were seated on the cycle ergometer with a standard overhand grip on the handlebar, identical to body position during the cycle ergometer test. To allow EMG data to be normalized, muscle activity was also recorded during a functional maximal contraction (FMC) using joint angles specific to the activity for all four muscles. Each isometric FMC lasted 2–3 s with a rest interval of 60 s between the three trials. The highest output served as the reference maximal contraction. The FMCs were recorded with participants positioned in a seated position with no leg movement. The FMC of the BR was obtained through a maximal handgrip on the handlebar. To execute FMC of the BB and TB, participants pulled and pushed, maximally upon the handlebars. UT FMC was accomplished by an isometric shoulder shrug against an isometric and antagonistic latissimus dorsi co-contraction, balancing shoulder elevation and depression. EMG activity during the FMCs served as reference standards to assess relative activity of the musculature during cycle ergometry. Muscle activity during the 30 s Wingate test was normalized by calculating it as a percentage of FMCs.
Cycle Ergometer Protocol During the second testing session, participants completed one 30 s Wingate test, while sEMG recorded muscle activity from the BR, BB, TB and UT. A Monark 894E Peak cycle ergometer (Monark, Vansbro, SWE) was used for all experimental testing. The cycle ergometer was connected to a PC to allow for data capture via the Monark anaerobic test software (version 2.24.2). Saddle height was adjusted for each participant, ensuring the knee remained slightly flexed at the completion of the power stroke (approximately 170–175° at extension). Toe clips were used to ensure that the participants’ feet were held firmly in place and in contact with the pedals throughout the tests. All participants completed a standardized warm up protocol, pedalling for 3 minutes at 60 rpm with a 2 kg flywheel resistance. During the Wingate protocol participants were instructed to remain seated in the saddle for the duration of the test and maintain a standard overhand handlebar grip. They were given a rolling start of approximately 5 s to generate an unloaded acceleration of pedal cadence to 60 rpm. At 60 rpm the weight basket automatically dropped and participants pedalled with maximum effort for a period of 30 s against a fixed resistive load of 75 grams per kilogram total body mass (7.5% of body mass) (Bar-Or, 1987). Verbal encouragement was given equitably to each participant in all testing.
Data Processing All sEMG data were processed using WinEDR V3.1.9 (Dr John Dempster, University of Strathclyde, Glasgow, UK). Root mean square (RMS) values were calculated by the following formula; T = 1 s
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Z RMS ¼ ½jmðt Þj ¼ 1=T
tþT
1=2 m ðt Þdt 2
(1)
t
The calculated RMS values were used to describe signal amplitude as an estimate of muscle activity at rest, during isometric FMCs and during the Wingate tests. Data are presented as RMS (±SD).
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Statistical Analysis Statistically analysis was performed using Statistical Package for Social Sciences (SPSS) software (Version 18) (IBM, Armonk, NY, USA). Normality of data distribution was tested by a Shapiro-Wilk’s test. Between-group differences were calculated using a repeated measures analysis of variance (ANOVA). Multiple comparisons on paired data were made using a paired t-test or Wilcoxon test. A paired t-test was used to identify differences in muscle activity at rest and during a FMC. Data collected during the Wingate test were non-parametric, therefore a Wilcoxon test was used to identify differences in muscle activity at rest and during a Wingate test and muscle activity during a FMC and during a Wingate test. A related-samples Friedman’s Two-Way ANOVA with subsequent pairwise comparisons was used to assess any changes in muscle activity over the 30 s Wingate test. A repeated measure ANOVA with subsequent Bonferonni post-hoc analysis was used to determine changes in power output over the duration of the test. Relationships between upper body limb activity (RMS) and power output were assessed using Spearman’s correlation coefficient. Statistical significance was set a priori at P < 0.05. All data is presented as mean ±SD.
RESULTS No differences were found between groups with regards to muscle activity, therefore male and female data was subsequently analysed as one group.
Processed sEMG Muscle activity in all four muscles, represented by sEMG amplitude (RMS), during the FMCs and Wingate test was significantly greater than muscle activity recorded at rest on the cycle ergometer (P < 0.001; P < 0.05 respectively). Muscle activity during the FMCs was significantly greater than muscle activity during the 30 s Wingate test, this was similar for all muscles (P < 0.05) (Table 1).
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TABLE 1 Muscle activity, represented by sEMG amplitude (RMS) at rest, during a FMC (functional maximal contraction) and average muscle activity recorded at 5 s intervals during the Wingate test. Values are group mean RMS (±SD) Rest BR BB TB UT
0.07 0.09 0.09 0.02
± ± ± ±
0.08a 0.09a 0.04a 0.01a
FMC 1.34 1.02 0.65 0.53
± ± ± ±
0.71b 0.62b 0.35b 0.37b
0–5 s 0.46 0.23 0.35 0.21
± ± ± ±
0.27 0.12 0.23 0.13
5–10 s 0.38 0.22 0.32 0.27
± ± ± ±
0.16 0.10 0.21 0.20
10–15 s 0.49 0.23 0.31 0.26
± ± ± ±
0.35 0.11 0.20 0.15
15–20 s 0.46 0.22 0.34 0.22
± ± ± ±
0.32 0.15 0.26 0.12
20–25 s 0.45 0.23 0.36 0.21
± ± ± ±
0.31 0.14 0.26 0.13
25–30 s 0.31 0.15 0.36 0.16
± ± ± ±
0.19 0.06 0.24 0.11
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a Resting values significantly lower than values recorded during FMC and at all time intervals during the 30 sWingate test; bMVE significantly greater than muscle activity recorded during 30sWingate test (P < 0.05).
Normalized values for sEMG amplitude, using a 1 s window, were obtained at sequential 5 s intervals during the Wingate test. There were no significant changes in signal amplitude over the duration of the test for the BR (P = 0.413), BB (P = 0.256), TB (P = 0.855). However, signal amplitude did change over time in the UT (P = 0.01) with muscle activity being significantly greatly at 10–15 s than at 25–30 s (Figure 1). Between-muscle differences were assessed using normalized values and only the TB was relatively more active compared with the BB at each time point (%FMC) (P < 0.05). There were no other differences between muscles (P > 0.05).
FIGURE 1 Muscle activity displayed as a percentage of the functional maximal contraction (FMC) at sequential 5 s interval across the 30 s Wingate test. No significant differences were found across the 30 s period (P > 0.05).
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Power Output Power output (W/kg) was averaged at 5 s intervals. No significant differences were found between power output at 0–5 s (8.86 ± 2.01 W/kg) and 5–10 s (8.89 ± 1.61 W/kg) (P = 1.00) and no differences between power output at 0–5 and 10–15 s (P = 0.068). Power output at 0–5 s and 5–10 s was significantly higher than at 15–20 s; 20–25 s and 25–30 s (7.79 ± 1.17; 6.97 ± 1.01; 6.27 ± 0.81; 5.70 ± 0.83 W/kg respectively) (P < 0.01). At 5–10 s power output was also significantly greater than at 10–15 s (P < 0.01). Each subsequent sequential power output from 10–15 s to 25–30 s was significantly lower than the preceding time interval (p < 0.05), highlighting the progressive decline in power output over the 30 s Wingate test. There was no correlation between upper body muscle activity and power output across the 30 s Wingate test (p > 0.05).
Raw sEMG The raw sEMG signal obtained from a selected participant during the Wingate test demonstrates very regular and sequential bursts of activity for the duration of the test. Generally, BR and BB activation was followed immediately by TB activation, as highlighted in Figure 2. It also highlights the clear regular bursts of muscle activation representing the cyclic pulling and pushing actions upon the handlebars.
5.0 2.5 BR 0.0 –2.5 –5.0 5.0 2.5 BB 0.0 –2.5 –5.0 5.0 2.5 TB 0.0 –2.5 –5.0 5.0 2.5 UT 0.0 –2.5 –5.0
FIGURE 2 Section of the sEMG signal of a participant recorded during a 30 s Wingate test. Dashed lines highlight the co-contraction of the BR and BB, immediately followed by TB activation. BR, brachioradialis; BB, biceps brachii, TB, triceps brachii; UT, upper trapezius.
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DISCUSSION The principle aim of this investigation was to explore upper body muscle activity during high intensity cycle ergometry using sEMG. Baker and colleagues (2001, 2002, 2009) previously established a relationship between power output and handlebar grip suggesting that the upper body musculature significantly contributes to power output during high intensity cycle ergometry. While handlebar grip has been examined, identification of the muscles of the upper body contributing to the lower body power transfer has only been speculated. The muscles investigated in the present study were the BR, BB, TB and UT. All four muscles investigated were found to be significantly more active during cycling compared to resting values obtained while seated on the cycle ergometer (p < 0.05) but less active than during a FMC (p < 0.01). This therefore confirms the previous suggestion that during the Wingate test, the upper body muscles are contributing to power output but also that they are not contracting maximally. The amplitude of the EMG signal, reported as RMS of the EMG, was used within the present investigation to describe muscular activity (Jobson, Hopker, Arkesteijn, & Passfield, 2012). Signal amplitude has been used as an estimate of muscle activity as both the force exerted by the muscle and the amplitude of the EMG signal have been reported to depend on the number of recruited motor units (MU) and the firing rate of each active MU (Vollestad, 1997). An increase in the amplitude of the sEMG signal is often observed during repetitive or sustained submaximal contractions (Vollestad, 1997) and has been attributed to both the recruitment of additional MUs to compensate for the decrease in contraction force and to an increase in the MU firing rate and/or synchronization of MU recruitment (Dimitrova & Dimitrov, 2002). Numerous authors have reported findings in agreement with this and have demonstrated an increase in amplitude during both sustained and dynamic sub-maximal isometric contractions (Arendt-Nielsen & Mills, 1988; Lloyd, 1971; Macdonald, Farina, & Marcora, 2008; Masuda, Masuda, Sadoyama, Inaki, & Katsuta, 1999; Moritani, Nagata, & Muro, 1982; Potvin & Bent, 1997). More recently, Fukuda et al. (2010) demonstrated a positive linear relationship between contraction force and RMS of the sEMG signal, further highlighting the association between force production and amplitude. However, in the present study there were no changes in signal amplitude over the 30 s test, measured at 5 s intervals, for any of the four muscles investigated (P > 0.05). This reflects the sub-maximal intermittent nature of the upper body contractions and therefore suggests that there is no increase in muscle force as the sprint progresses. The lack of changes in muscle force production in the upper body may be related to the oscillatory nature of cycling, which implies that agonist and antagonist muscles are able to share the workload, with no requirements to recruit additional MUs to maintain the contraction force. Furthermore, with the muscles being intermittently active,
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hyperaemia will be able to provide the muscles with sufficient oxygen to maintain aerobic energy metabolism and therefore prevent possible energy depletion and/or metabolite accumulation (Jobson et al., 2012). Similar to the findings of the present study, Hunter and colleagues (2003) found no change in signal amplitude in the lower limbs during a similar protocol. They suggested this may be a result of insufficient afferent command from type III and IV receptors to the central nervous system, reducing central drive and a resulting change in EMG amplitude. Although unlikely to be a valid explanation for the results of the present study, it highlights the variability of sEMG analysis. The results therefore suggest acceptance of the null hypothesis as upper body muscle contraction did not change over the duration of the sprint despite a significant decline in power output (W/kg), which is indicative of a decrease in overall cycling performance. The submaximal nature of the upper body contractions, as demonstrated in the sEMG data, confirm the previous suggestion that the primary function of the upper body is to stabilize body position and provide a counterbalancing force for the lower limbs. However, in real-world cycling performance, there may be a greater activation of the upper body musculature, in particular in a standing position, where the upper body and trunk muscles are supporting additional weight due to the loss of saddle support, in order to control balance and to swing both the body and bicycle side to side (Duc, Bertucci, Pernin, & Grappe, 2008). The large inter-participant variability in the present study (a common finding in sEMG analysis), indicated by large standard deviations throughout the data, make it difficult to determine an objective quantitative relationship between upper body activity and high intensity cycle ergometry performance (Figure 1). This variability is further increased due to the nature of cycling where muscle activity and co-ordination can differ considerably between individuals (Blake, Champoux, & Wakeling, 2012), particularly as the individuals within this study were not trained cyclists. However, as an exploratory investigation, visual inspection of the raw EMG data may provide the most pertinent insight into muscle activity. Raw EMG recording contains important information and therefore can be used as a first understanding of neuromuscular control during exercise (So, Ng & Ng, 2005). The raw EMG signal (Figure 2) recorded during the present study demonstrates a linkage to the oscillatory nature of cycling. The bursts of activity are representative of the alternate pushing and pulling motions upon the handlebars (Baker et al., 2001) and may also provide some valuable information relating to the working phase of the muscle with respect to the three crank phases as described by So et al., (2005), as the downstroke (propulsive), the upstroke (recovery) and the pulling phase where the foot is pushed forward at top dead centre. Observations of participants during the cycle ergometer test revealed that in general the bursts of activity observed on the EMG trace in the TB occur during the upstroke of the leg (due to elbow
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extension) and the bursts of activity in the BR and BB generally occur at the same time during the downstroke of the leg (due to elbow flexion) (Figure 2). No clear pattern emerged from the UT data and this may be due to its role as a tonic muscle that is associated with stabilization during exercise. This warrants further investigation combining sEMG and biomechanical analysis. Every effort was made to control for the limiting factors commonly associated with the outcomes of sEMG analysis (De Luca, 1997). The effect of subcutaneous tissue layers acting as low pass filters, so influencing signal conduction (Pincivero, Green, Mark & Campy, 2000) is one factor. Minor electrode displacement causing sEMG to be recorded from different muscle locations can also affect the signal due to the heterogeneity of muscle fibres (Rainoldi, Melchiorri & Caruso, 2004), alongside muscle crosstalk producing electrical activity that artifactually registers on the sEMG thus amplifying the recorded muscle’s activity. This may be a particular problem in the BR due its close proximity to several other small forearm muscles (Kong, Hallbeck & Jung, 2010).
CONCLUSION It is clear that all muscles investigated were active during the 30 s Wingate test and therefore have a considerable role in optimal high intensity cycling performance. Therefore, when using high-intensity cycle ergometry as a test of muscular performance it is important that investigators consider the potential influences of the upper body to the power outputs achieved, through both the handlebar grip and position of the trunk. Handlebar grip should therefore be standardized in any experimental procedures. Further investigation is necessary to fully quantify the contribution of the upper body relative to power output and to evaluate the relative contributions of both the abdominal and back musculature. In terms of real world cycling performance cyclists and their coaches should not underestimate the importance of establishing a strength base in the upper body to support cycling performance both in training and competition. The upper body is likely to be particularly influential during sustained uphill climbs where there is a continued high resistance that cannot be overcome.
REFERENCES Arendt-Nielsen, L., & Mills, K. R. (1988). Muscle fibre conduction velocity, mean power frequency, mean EMG voltage and force during submaximal fatiguing contractions of human quadriceps. European Journal of Applied Physiology and Occupational Physiology, 58, 20–25. Baker, J. S., & Davies, B. (2009a). Additional considerations and recommendations for the quantification of hand-grip strength in the measurement of leg power during high intensity cycle ergometry. Research in Sports Medicine, 17, 145–155.
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Baker, J. S., Brown, E., Hill, G., Philips, G., & Davies, B. (2002). Handgrip contribution to lactate production and leg power during high intensity exercise. Medicine and Science in Sport and Exercise, 34(6), 1037–1040. Baker, J. S., Gal, J., Davies, B., Bailey, D., & Morgan, R. (2001). Power output of legs during high intensity cycle ergometry: Influence of hand grip. Journal of Sports Science, 4(1), 10–18. Baker, J. S., Thomas, N. E., & Davies, B. (2009). Physiological, biomechanical and mechanical issues relating to force selection during high intensity cycle ergometer performance. Journal of Exercise Science & Fitness, 7(2), s51–s60. Bar-Or, O. (1987). The Wingate anaerobic test. An update on methodology, reliability and validity. Sports Medicine, 4, 381–394. Blake, A. M., Champoux, Y., & Wakeling, J. M. (2012). Muscle coordination patterns for efficient cycling. Medicine and Science in Sport and Exercise, 44(5), 926–938. De Luca, C, J. (1997). The use of surface electromyography in biomechanics. Journal of Applied Biomechanics, 13, 135–163. Dimitrova, N. A., & Dimitrov, G. V. (2002). Amplitude-related characteristics of motor unit and M-wave potentials during fatigue. A simulation study using literature data on intracellular potential changes found in vitro. Journal of Electromyography and Kinesiology, 12(5), 339–349. Duc, S., Bertucci, W., Pernin, J. N., & Grappe, F. (2008). Muscular activity during uphill cycling: effect of slope, posture, hand grip position and constrained bicycle lateral sways. Journal of Electromyography and Kinesiology, 18(1), 116–127. Fukuda, T. Y., Echeimberg, J. O., Pompeu, J. E., Lucareli, P. R. G., Garbelotti, S., Gimenes, R. O., & Apolinário, A. (2010). Root mean square value of the electromyographic signal in the isometric torque of the quadriceps. Hamstrings and brachial biceps muscles in female subjects. Journal of Applied. Research, 10(1), 32–39. González-Izal, M., Malanda, A., Navarro-Amézqueta, I., Gorostiaga, E. M., Mallor, F., Ibañez, J., & Izquierdo, M. (2010). EMG spectral indices and muscle power fatigue during dynamic contractions. Journal of Electromyography and Kinesiology, 20(2), 233–240. Gregor, R. J., & Concomi, F. (2000). Road Cycling. Oxford: Blackwell Science. Hunter, A. M., Gibson, A. S. C., Lambert, M. I., Nobbs, L., & Noakes, T. D. (2003). Effects of supramaximal exercise on the electromyographic signal. British Journal of Sports Medicine, 37(4), 296–299. Jobson, S. A., Hopker, J., Arkesteijn, M., & Passfield, L. (2012). Inter- and intra-session reliability of muscle activity patterns during cycling. Journal of Electromyography and Kinesiology, http://dx.doi.org/10.1016/j.jelekin.2012.08.013 Kong, Y. K., Hallbeck, M. S., & Jung, M. C. (2010). Crosstalk effect on surface electromyogram of the forearm flexors during a static grip task Journal of Electromyography Kinesiology, 20(6), 1223–1229. Lloyd, A. J. (1971). Surface electromyography during sustained isometric contraction. Journal of Applied Physiology, 30, 713–719. Macdonald, J. H., Farina, D., & Marcora, S. M. (2008). Response of electromyographic variables during incremental and fatiguing cycling. Medicine and Science in Sports and Exercise, 40(2), 335–344.
Downloaded by [George Washington University] at 11:40 23 February 2015
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Martini, F. H. (2006). Fundamentals of Anatomy and Physiology (7th ed.) San Francisco: Pearson Education. Masuda, K., Masuda, T., Sadoyama, T., Inaki, M., & Katsuta, S. (1999). Changes in surface EMG parameters during static and dynamic fatiguing contractions. Journal of Electromyography and Kinesiology, 9(1), 39–46. Moritani, T., Nagata, A., & Muro, M. (1982). Electromyographic manifestations of muscular fatigue. Medicine and Sciemce in Sports and Exercise, 14(3), 198–202. Pincivero, D. M., Green, R. C., Mark, J. D., & Campy, R. M. (2000). Gender and muscle differences in EMG amplitude and median frequency, and variability during maximal voluntary contractions of the quadriceps femoris. Journal of Electromyography and Kinesiology, 10(3), 189–196. Potvin, J. R., & Bent, L. R. (1997). A validation of techniques using surface EMG signals from dynamic contractions to quantify muscle fatigue during repetitive tasks. Journal of Electromyography and Kinesiology, 7(2), 131–139. Rainoldi, A., Melchiorri, G., & Caruso, I. (2004). A method for positioning electrodes during surface EMG recordings in lower limb muscles. Journal of Neuroscience Methods, 134(1), 37–43. Schmidt, A. (1994). Handbook of Competitive Cycling: Training, Keep Fit, Tactics. Oxford: Meyer & Meyer. So, R. C. H., Ng, J. K. F., & Ng, G. Y. F. (2005). Muscle recruitment in cycling: a review. Physical Therapy in Sport, 6, 89–96. Vollestad, N. K. (1997). Measurement of human muscle fatigue. Journal of Neuroscience Methods, 74, 219–227.
