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Changes in muscle coordination and power output during sprint cycling
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Steven J. O’Bryan a , Nicholas A.T. Brown b , Franc¸ois Billaut a,c , David M. Rouffet a,b,∗ a b c
Institute of Sport, Exercise and Active Living (ISEAL), Victoria University, PO Box 14428, Melbourne, VIC 8001, Australia Department of Biomechanics and Performance Analysis, Australian Institute of Sport, PO Box 176, Belconnen, ACT 2616, Australia Institut national du sport du Québec, 1000, avenue Émile-Journault – bureau 1.72, Montréal, Qc H2M 2E7, Canada
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Power deficit is accompanied by significant alterations in muscle coordination. Bi-articular RF and GAS muscles are most significantly affected. Co-activation between GAS and proximal muscles dramatically reduced. Co-activation analysis supports previous biomechanical models. Coordination affected by central/peripheral fatigue or change in movement strategy.
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Article history: Received 17 September 2013 Received in revised form 27 March 2014 Accepted 13 May 2014 Available online xxx
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Keywords: EMG Muscle activation Bi-articular muscles Fatigue Co-activation Power transfer
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1. Introduction
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This study investigated the changes in muscle coordination associated to power output decrease during a 30-s isokinetic (120 rpm) cycling sprint. Modifications in EMG amplitude and onset/offset were investigated from eight muscles [gluteus maximus (EMGGMAX ), vastus lateralis and medialis obliquus (EMGVAS ), medial and lateral gastrocnemius (EMGGAS ), rectus femoris (EMGRF ), biceps femoris and semitendinosus (EMGHAM )]. Changes in co-activation of four muscle pairs (CAIGMAX/GAS , CAIVAS/GAS , CAIVAS/HAM and CAIGMAX/RF ) were also calculated. Substantial power reduction (60 ± 6%) was accompanied by a decrease in EMG amplitude for all muscles other than HAM, with the greatest deficit identified for EMGRF (31 ± 16%) and EMGGAS (20 ± 14%). GASonset , HAMonset and GMAXonset shifted later in the pedalling cycle and the EMG offsets of all muscles (except GASoffset ) shifted earlier as the sprint progressed (P < 0.05). At the end of the sprint, CAIVAS/GAS and CAIGMAX/GAS were reduced by 48 ± 10% and 43 ± 12%, respectively. Our results show that substantial power reduction during fatiguing sprint cycling is accompanied by marked reductions in the EMG activity of bi-articular GAS and RF and co-activation level between GAS and main power producer muscles (GMAX and VAS). The observed changes in RF and GAS EMG activity are likely to result in a redistribution of the joint powers and alterations in the orientation of the pedal forces. © 2014 Published by Elsevier Ireland Ltd.
High performance during sprinting events (running, cycling) is strongly determined by the ability to produce and maintain maximal levels of muscular power. However, the ability of the central nervous system (CNS) to optimally coordinate the activation of the different muscles is also very important as it determines how
∗ Corresponding author at: Institute of Sport, Exercise and Active Living (ISEAL), Victoria University, PO Box 14428, Melbourne, VIC 8001, Australia. Tel.: +61 3 9919 4384. E-mail address: [email protected] (D.M. Rouffet).
the muscular forces are distributed across the joints and how the external force is orientated. If power production during sprint performances has been well documented [6,8,17], muscle coordination has received less attention, particularly during fatiguing sprints. Previous studies have provided detailed analyses of muscle coordination during fatigue-free sprint cycling, through the investigation of muscle activation patterns during the pedal cycle [5,20]. Surface EMG (EMG) studies of fatigue-free sprint cycling show that gastrocnemius (GAS) and quadriceps muscles [vasti (VAS) and rectus femoris (RF)] are maximally activated, while some discrepancies have been reported regarding activation level of the hamstrings (HAM) and gluteus maximus (GMAX) muscles [5,20]. Considering the high activation level of most lower-limb muscles during
http://dx.doi.org/10.1016/j.neulet.2014.05.023 0304-3940/© 2014 Published by Elsevier Ireland Ltd.
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fatigue-free sprint cycling, neuromuscular fatigue (central and peripheral) is likely to occur during prolonged periods of sprint cycling (i.e. 30-s) [12], which may manifest as changes in muscular EMG activity (amplitude and/or timing). During a maximal 30-s cycling sprint, EMG activity of the quadriceps has been shown to decrease by ∼8% [4] or remain unaltered [9,13,19], whereas GAS muscles have shown a decrease of up to 15% [9]. A manipulation to the timing of activation for biceps femoris (BF) muscles during fatiguing sprint cycling has also been shown [2]. Unfortunately, none of these studies [2,4,9,13,19] analyzed changes in EMG activity using the recommendations made by recent extensive reviews [3,12]. Consequently, it seems difficult to describe the link between changes in muscle coordination with power deficit during fatiguing sprint cycling from this previous data. Martin and Brown [16] demonstrated that the power produced at the three lower-limb joints decreases at different rates during a maximal 30-s isokinetic (120 rpm) cycle sprint. In reference to biomechanical models of pedalling [25,27], it is possible that alterations in joint power [16] could be further understood by investigating changes in muscle co-activation. Van Ingen Schenau [25] explains that co-activation between GMAX/RF and VAS/HAM is essential to transfer muscular forces across the hip and knee joints and to optimize the orientation of the pedal forces. A decrease in coactivation between VAS/HAM has been suggested during fatiguing cycling sprints [2,10]. However, Zajac et al. [27] further suggests that co-activation between the ankle plantar flexors and proximal muscles (GMAX and VAS) is a key factor for optimizing power transfer across the ankle joint to the crank during cycling. Interestingly, Martin and Brown [16] observed the largest reduction in joint power at the ankle level over the course of a fatiguing cycling sprint (63%). However, no EMG studies have investigated changes in coactivation between the ankle plantar flexors and proximal muscles during fatiguing sprint cycling. The aim of the present study was to investigate changes in the EMG activity (amplitude and onsets/offsets) of the lower-limb muscles and associated modifications in muscle co-activations during a fatiguing 30-s cycling sprint for which detailed biomechanical data has been reported [16]. Changes in the EMG activity of five major lower-limb muscle groups were investigated by using gold standard methods for EMG normalization [3,20], calculation of EMG profiles [5,12] and quantification of co-activations [15]. Extending on the biomechanical findings of Martin and Brown [16], it was hypothesized that marked changes in the EMG activity of the ankle plantar flexor muscles (amplitude and timing) and/or coactivation of this muscle with proximal muscles would occur during the course of a fatiguing 30-s cycle sprint.
2. Materials and methods Ten active males volunteered to participate in this study (age 24 ± 3 years; body mass 83.7 ± 9.7 kg). Six were amateur team sport players (Australian Rules football, basketball and netball), three participated in individual sports (swimming, tennis and sprint athletics) and one was undertaking regular resistance training, with an overall training load of 5.3 ± 1.7 h/week. Written informed consent was obtained from each participant and all testing was approved by Victoria University’s Human Research Ethics Committee. Exercise was conducted on an electronically braked cycle ergometer (Excalibur Sport; Lode® , The Netherlands) which sampled power output at 5 Hz. Crank length equalled 175 mm and pedal straps were utilized to fasten feet into the pedals. Participants remained seated with hand position in the dropped portion of the handlebars during the sprint. A familiarization session took place no earlier than 48 h prior to testing. Following a warm-up [5-min cycling at 1 W/kg and 80
revolutions per minute (rpm)], each participant completed a practice 5-s sprint followed by 5 min of passive rest. For the 30-s sprint, participants were required to overcome the inertia of the flywheel and reach a cadence close to 120 rpm within 5 s to start time. Participants were stopped from pedalling and instructed to place the right crank angle at 45◦ before receiving a verbal 5-s countdown. For the sprint, the ergometer was set in isokinetic mode and cadence fixed at 120 rpm [16]. Power output was calculated over each pedalling cycle and normalized in reference to the peak power achieved during the sprint (PPEAK ). EMG signals were recorded from eight muscles of the left lower-limb [gluteus maximus (EMGGMAX ), rectus femoris (EMGRF ), vastus lateralis (VASLAT ), vastus medialis obliquus (VASMED ), semitendinosus (ST), biceps femoris long head (BF), gastrocnemius medialis (GASMED ) and gastrocnemius lateralis (GASLAT )]. Muscles from the same functional group were averaged to produce EMGGAS (GASLAT + GASMED ), EMGVAS (VASLAT + VASMED ) and EMGHAM (ST + BF). Dual surface electrodes of 10 mm diameter and inter-electrode distance of 20 mm (Noraxon dual electrodes, Noraxon USA Inc., Scottsdale, AZ) were used to record the EMG signals, with electrode location defined following SENIAM’s recommendations [11]. The reference electrode was placed over the superior aspect of the medial sacral crest. Prior to electrode application, skin was shaved, lightly abraded and cleaned with an alcohol swab to reduce skin impedance. Tubular netting was worn to limit movement artefacts. All signals were recorded continuously at 1500 Hz via a wireless receiver (Telemyo 2400 GT, Noraxon Inc., USA) connected to a notebook. A reed switch attached to the ergometer frame was aligned with a magnet attached to the left crank in order to identify 0/100% (TDC) of the left pedalling cycle from +3 V pulse recorded in a channel of the EMG system. EMG signals were recorded and processed using Noraxon software (MyoResearch XP version 1.07.41). Raw EMG signals were pre-amplified, band pass filtered (10–500 Hz) and full wave rectified. Following full wave rectification, the EMG signals were root mean squared with a 100 ms moving rectangular window to create a linear envelope. Each linear envelope was synchronized with the TDC sensor and time normalized to 100 points (100% of pedalling cycle, TDC-TDC) to create EMG activity profiles, which were then normalized in reference to the individual maximum value obtained during the sprint [5,12,20]. From each of the EMG profiles (i.e. 60), we calculated the average EMG amplitude and the EMG onset/offset of activation via determining a threshold of three standard deviations above the minimal EMG value [21]. Following this, one average EMG profile for each 6-s interval was constructed for each muscle group. Co-activation values were calculated from the normalized EMG activity profiles using the Co-activation Index (CAI) employed by Lewek et al. [15]. Based on the biomechanical models of cycling, changes in CAIs were calculated for VAS/HAM (CAIVAS/HAM ) and GMAX/RF (CAIGMAX/RF ) [25] as well as VAS/GAS (CAIVAS/GAS ) and GMAX/GAS (CAIGMAX/GAS ) [27]. Power output, EMG amplitude, onset/offset and CAIs was recorded for each pedalling cycle before average values were calculated for each variable over five even time intervals of 6 s duration (equivalent of 20% total sprint duration and 12 consecutive pedalling cycles). All data was analyzed using SPSS software (version 21, SPSS Inc., Chicago, IL). A two-way repeated measures ANOVA (muscle/CAI*time) with LSD post hoc comparisons was performed to evaluate differences between EMG (amplitude and onset/offset) and CAIs over each 6-s time interval of the sprint. Changes over time for mean power, individual EMG and CAIs were investigated via one-way repeated measures ANOVA. The significance level for all statistical tests was set at P < 0.05 and all data in text is reported as mean ± standard deviation.
Please cite this article in press as: S.J. O’Bryan, et al., Changes in muscle coordination and power output during sprint cycling, Neurosci. Lett. (2014), http://dx.doi.org/10.1016/j.neulet.2014.05.023
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Fig. 1. Power output measured per pedalling cycle (% PPEAK ) throughout the duration of the sprint. Mean ± SD is also displayed for each time interval. *Significantly different from the initial time interval (P < 0.05). # Significantly different from the previous time interval (P < 0.05)
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3. Results PPEAK during the initial interval was 1043 ± 185 W (12.6 ± 2.5 W/kg). Absolute mean power for the five time intervals was as follows: 833 ± 213; 672 ± 118; 547 ± 91; 437 ± 79 and 335 ± 73 W representing relative reductions of 19 ± 9; 34 ± 8; 47 ± 7 and 60 ± 6% (P < 0.05) from the initial time interval (Fig. 1). Mean EMG amplitude was affected by time, with a general decrease occurring during the third time interval (i.e. 12–18 s) (P < 0.05). Mean EMG amplitude also varied between the muscles (P < 0.05) with EMGGAS displaying the highest mean amplitude (30 ± 1%) and EMGGMAX the lowest (24 ± 1%) over the full duration of the sprint. A combined effect of muscle and time was also observed for mean EMG amplitude (P < 0.05). All muscles other than EMGHAM displayed a significant decrease in EMG amplitude over time (P < 0.05), with EMGRF , EMGGAS and EMGVAS decreasing from the third time interval (P < 0.05) and EMGGMAX decreasing during the final interval (P < 0.05). At the end of the sprint, EMGRF (31 ± 16%) and EMGGAS (20 ± 14%) showed the greatest relative decrease in mean EMG amplitude. EMG onsets were affected by time and tended to occur later in the pedal cycle as the sprint progressed (P < 0.05). A combined effect of muscle and time was also displayed for EMG onsets (P < 0.05). GASonset occurred at significantly later periods of the pedal cycle during each time interval, whereas HAMonset and GMAXonset started to deviate from the initial interval during the second half of the sprint (P < 0.05). Over time, VASonset and RFonset were unaffected (P > 0.05) (Fig. 2). A global effect of time was also identified for EMG offsets, which tended to occur at earlier periods of the pedalling cycle as the sprint progressed. RFoffset occurred earlier than the initial 6 s during each time interval (P < 0.05). VASoffset deviated from the initial interval during the second half of the sprint, whereas HAMoffset and GMAXoffset both occurred earlier during the final interval only (P < 0.05). GASoffset did not fluctuate from the initial 6-s throughout the sprint (P > 0.05). Changes in the EMG profiles and average amplitude over the duration of the sprint are displayed in Fig. 2.
The general level of co-activation decreased over time (P < 0.05). A significant difference between all CAIs (P < 0.05) showed the lowest mean level of co-activation for CAIVAS/GAS (16 ± 1%) and the highest for CAIVAS/HAM (24 ± 2%). A combined effect for muscle pairs and time was also shown (P < 0.05). CAIVAS/GAS and CAIGMAX/GAS decreased over each time interval and displayed a relative decrease from the initial interval of 48 ± 10% and 43 ± 12% at the end of the sprint, respectively (P < 0.05) (Fig. 3). CAIGMAX/RF was lower than the initial interval during the second half of the sprint with an overall relative decrease of 38 ± 19%, while CAIVAS/HAM decreased during the final interval and displayed a relative decrease of 17 ± 21% (P < 0.05).
4. Discussion Our analysis started by verifying that individual EMG profiles and derived EMG values obtained during the first interval (0–6 s) were in line with that reported during fatigue-free sprint cycling [5,20], which provided us with a valid reference to investigate the effects of fatigue on muscle coordination during the sprint. Following this, we showed that fatigue during a 30-s isokinetic (120 rpm) sprint is associated with uneven changes in the EMG of individual muscles and the level of co-activation between different muscle pairs. The most pronounced changes consisted of a reduction in EMGGAS and EMGRF amplitude, which was associated with alterations in the occurrence of the EMG bursts during the pedalling cycle. These changes during the sprint resulted in a considerable decrease in co-activation between GAS and proximal power producing muscles (GMAX and VAS). The relative reduction in mean power of 60% was in line with that observed by Martin and Brown [16] during the same fatiguing cycling sprint. However, the reduction in mean power was greater than that displayed during a 30-s Wingate test (WAT) [4,9,13,19]. This difference in relative power decrease presumably occurred due to the completion of additional pedal revolutions (∼13) [26] which would have increased the level of fatigue [24]. Interestingly, this
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Fig. 2. EMG profiles of each muscle for all time intervals (left column), average EMG amplitude (middle column) and activation onsets/offsets (right column) for each completed pedal cycle. Mean ± SD is also displayed for each time interval of the sprint. Individual muscles are displayed on separate rows. *Significantly different from the initial time interval (P < 0.05). # Significantly different from the previous time interval (P < 0.05).
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Fig. 3. Co-activation profiles for each muscle pair (left column) and average CAI for each pedal cycle (right column). Mean ± SD is also displayed for each time interval of the sprint. Each CAI pair is displayed on separate rows. *Significantly different from the initial time interval (P < 0.05). # Significantly different from the previous time interval (P < 0.05)
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difference coincided with larger decreases in EMG amplitude of all lower-limb muscles when compared to previous WAT studies [4,9,13,19], suggesting that the magnitude of power reduction may be associated with a greater EMG decrease in the lower-limb muscles. The uneven decrease in EMG across the lower-limb muscles is in line with the biomechanical findings from Martin and Brown [16] who showed different rates of joint power reduction during the same type of fatiguing sprint. Such a decrease in EMG activity during a maximal exercise may reflect the occurrence of fatigue, with a central or peripheral origin [7]. However, where Martin and Brown [16] showed decrements in joint power of up to ∼60%, our
EMG decreases were much lower, suggesting that power decrease during a 30-s isokinetic cycle sprint could be largely explained by peripheral fatigue [1]. For example, we identified no alteration in EMGHAM amplitude, whereas Martin and Brown [16] displayed a 47% decrease in knee flexion power. Furthermore, we displayed a 20% decrease in EMGGAS amplitude compared to the 63% decrease in ankle joint power observed by Martin and Brown [16]. It has been shown that GAS muscles transfer a large proportion (>50%) of the power produced by the proximal mono-articular muscles (GMAX and VAS) to the crank during maximal cycling, whereas the demand placed on RF for power transfer is much less [18,27]. However, the
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muscle fibre composition of RF (higher % type II muscle fibres) [14] makes this muscle more susceptible to fatigue development than GAS during maximal exercise [23], which could explain the greater decrease in EMG amplitude. In light of Martin and Brown findings [16], the large reduction in EMGRF amplitude is likely to decrease knee extension power and generate negative hip joint power (during the upstroke phase) over the course of the fatiguing cycling sprint. If muscle fatigue can explain the alteration in EMG activity, a fatigue-independent adjustment could also explain the EMG decrease. For example, in reference to biomechanical models [27], the decrease in EMGGAS amplitude may occur to adjust to a reduced power production from GMAX and VAS. This hypothesis cannot be excluded as our results showed a significant reduction in EMGGMAX and EMGVAS amplitude, which is in line with the reduction of the hip knee extension powers observed during fatiguing sprint cycling [16]. Furthermore, the decrease in EMGGAS amplitude could be aimed at reducing the range of motion (ROM) of the ankle joint and simplifying the complexity of the pedalling movement during the course of the fatiguing sprint [16]. If this reduction in ankle joint ROM occurred in the present study, this would decrease GAS shortening velocity and further reduce the EMG activity of these muscles [22]. Finally, the general observation across all lower-limb muscles of a later EMG onset and earlier EMG offset suggests that the CNS may increase the time for muscular relaxation in an attempt to limit fatigue development. According to the biomechanical models of cycling [25,27], the large reductions in co-activation between the bi-articular GAS and RF with the proximal GMAX and VAS, would have substantially decreased the amount of power transferred across the joint to the crank. However, it is difficult to determine the exact mechanisms leading to these reductions. For example, during the second interval of the sprint (6–12 s), co-activation between GAS and proximal muscles reduced through a manipulation to GASonset only. This suggests that a change in the coordination of a bi-articular muscle may influence the level of co-activation with a mono-articular muscle and affect joint power distribution and power production. In addition to transferring power generated by VAS and GMAX across the joints, the bi-articular RF and GAS also optimize the orientation of the external force applied to the pedal around the transition phases [25,27]. Therefore, the observed reduction in the EMGRF and EMGGAS during the fatiguing sprint may result in a reduction of the horizontal components of the force applied to the pedal around top (oriented forward) and bottom (oriented backward) dead centres, respectively. Such alterations can potentially decrease the magnitude of the tangential component of the force applied to the pedal and reduce the amount of power transmitted to the crank.
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Our results clearly show that EMG activity and muscular coactivation decreases at different rates between the lower-limb muscles during a fatiguing cycling sprint. In light of previous biomechanical findings and models, the changes in the EMG activity of the bi-articular muscles observed in this study may result from localized muscle fatigue or changes in the pedalling movement control strategy. Future research combining EMG and biomechanical measurements is warranted to extend our understanding of the respective roles played by fatigue and motor control in the
changes of muscle coordination, forces applied to the pedals and power transmitted to the crank during fatiguing sprint cycling. Acknowledgements The authors would like to sincerely thank the reviewers of the manuscript for their constructive criticism and valuable comments. References [1] B. Bigland-Ritchie, J.J. Woods, Changes in muscle contractile properties and neural control during human muscular fatigue, Muscle Nerve 7 (9) (1984) 691–699. [2] F. Billaut, F.A. Basset, G. Falgairette, Muscle coordination changes during intermittent cycling sprints, Neurosci. Lett. 380 (3) (2005) 265–269. [3] A. Burden, How should we normalize electromyograms obtained from healthy participants? What we have learned from over 25 years of research, J. Electromyogr. Kinesiol. 20 (6) (2010) 1023–1035. [4] H. Chtourou, et al., Diurnal variation in Wingate-test performance and associ- Q2 ated electromyographic parameters, Chronobiol. Int. 28 (8) (2011) 706–713. [5] S. Dorel, et al., Adjustment of muscle coordination during an all-out sprint cycling task, Med. Sci. Sports Exerc. 44 (11) (2012) 2154–2164. [6] S. Dorel, et al., Torque and power-velocity relationships in cycling: relevance to track sprint performance in world-class cyclists, Int. J. Sports Med. 26 (9) (2005) 739–746. [7] D. Farina, R. Merletti, R.M. Enoka, The extraction of neural strategies from the surface EMG, J. Appl. Physiol. 96 (4) (2004) 1486–1495. [8] A.S. Gardner, et al., Velocity-specific fatigue: quantifying fatigue during variable velocity cycling, Med. Sci. Sports Exerc. 41 (4) (2009) 904. [9] F. Greer, J. Morales, M. Coles, Wingate performance and surface EMG frequency variables are not affected by caffeine ingestion, Appl. Physiol. Nutr. Metab. 31 (5) (2006) 597–603. [10] C.A. Hautier, et al., Influence of fatigue on EMG/force ratio and cocontraction in cycling, Med. Sci. Sports Exerc. 32 (4) (2000) 839–843. [11] H.J. Hermens, et al., European Recommendations for Surface Electromyography, Roessingh Research and Development, 1999. [12] F. Hug, S. Dorel, Electromyographic analysis of pedaling: a review, J. Electromyogr. Kinesiol. 19 (2) (2009) 182–198. [13] A.M. Hunter, et al., Effects of supramaximal exercise on the electromyographic signal, Br. J. Sports Med. 37 (4) (2003) 296–299. [14] M.A. Johnson, et al., Data on the distribution of fibre types in thirty-six human muscles. An autopsy study, J. Neurol. Sci. 18 (1) (1973) 111–129. [15] M.D. Lewek, K.S. Rudolph, L. Snyder-Mackler, Control of frontal plane knee laxity during gait in patients with medial compartment knee osteoarthritis, Osteoarthr. Cartil. 12 (9) (2004) 745–751. [16] J.C. Martin, N.A. Brown, Joint-specific power production and fatigue during maximal cycling, J. Biomech. 42 (4) (2009) 474–479. [17] J.-B. Morin, et al., Mechanical determinants of 100-m sprint running performance, Eur. J. Appl. Physiol. 112 (11) (2012) 3921–3930. [18] C.C. Raasch, et al., Muscle coordination of maximum-speed pedaling, J. Biomech. 30 (6) (1997) 595–602. [19] S.R. Rana, Effect of the Wingate test on mechanomyography and electromyography, J. Strength Cond. Res. 20 (2) (2006) 292–297. [20] D.M. Rouffet, C.A. Hautier, EMG normalization to study muscle activation in cycling, J. Electromyogr. Kinesiol. 18 (5) (2008) 866–878. [21] D.M. Rouffet, et al., Timing of muscle activation of the lower limbs can be modulated to maintain a constant pedaling cadence, J. Electromyogr. Kinesiol. 19 (6) (2009) 1100–1107. [22] D.J. Sanderson, et al., Gastrocnemius and soleus muscle length: velocity, and EMG responses to changes in pedalling cadence, J. Electromyogr. Kinesiol. 16 (6) (2006) 642–649. [23] S. Schiaffino, C. Reggiani, Fiber types in mammalian skeletal muscles, Physiol. Rev. 91 (4) (2011) 1447–1531. [24] A. Tomas, E.Z. Ross, J.C. Martin, Fatigue during maximal sprint cycling: unique role of cumulative contraction cycles, Med. Sci. Sports Exerc. 42 (7) (2010) 1364–1369. [25] G.J. Van Ingen Schenau, From rotation to translation: constraints on multi-joint movements and the unique action of bi-articular muscles, Hum. Mov. Sci. 8 (4) (1989) 301–337. [26] C. Williams, J. Doust, A. Hammond, Power output and VO2 responses during 30 s maximal isokinetic cycle sprints at different cadences in comparison to the Wingate test, Isokin. Exerc. Sci. 14 (4) (2006) 327–333. [27] F.E. Zajac, R.R. Neptune, S.A. Kautz, Biomechanics and muscle coordination of human walking. Part I: introduction to concepts, power transfer, dynamics and simulations, Gait Posture 16 (3) (2002) 215–232.
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Changes in muscle coordination and power output during sprint cycling
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Steven J. O’Bryan a , Nicholas A.T. Brown b , Franc¸ois Billaut a,c , David M. Rouffet a,b,∗ a b c
Institute of Sport, Exercise and Active Living (ISEAL), Victoria University, PO Box 14428, Melbourne, VIC 8001, Australia Department of Biomechanics and Performance Analysis, Australian Institute of Sport, PO Box 176, Belconnen, ACT 2616, Australia Institut national du sport du Québec, 1000, avenue Émile-Journault – bureau 1.72, Montréal, Qc H2M 2E7, Canada
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h i g h l i g h t s • • • • •
Power deficit is accompanied by significant alterations in muscle coordination. Bi-articular RF and GAS muscles are most significantly affected. Co-activation between GAS and proximal muscles dramatically reduced. Co-activation analysis supports previous biomechanical models. Coordination affected by central/peripheral fatigue or change in movement strategy.
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Article history: Received 17 September 2013 Received in revised form 27 March 2014 Accepted 13 May 2014 Available online xxx
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Keywords: EMG Muscle activation Bi-articular muscles Fatigue Co-activation Power transfer
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1. Introduction
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This study investigated the changes in muscle coordination associated to power output decrease during a 30-s isokinetic (120 rpm) cycling sprint. Modifications in EMG amplitude and onset/offset were investigated from eight muscles [gluteus maximus (EMGGMAX ), vastus lateralis and medialis obliquus (EMGVAS ), medial and lateral gastrocnemius (EMGGAS ), rectus femoris (EMGRF ), biceps femoris and semitendinosus (EMGHAM )]. Changes in co-activation of four muscle pairs (CAIGMAX/GAS , CAIVAS/GAS , CAIVAS/HAM and CAIGMAX/RF ) were also calculated. Substantial power reduction (60 ± 6%) was accompanied by a decrease in EMG amplitude for all muscles other than HAM, with the greatest deficit identified for EMGRF (31 ± 16%) and EMGGAS (20 ± 14%). GASonset , HAMonset and GMAXonset shifted later in the pedalling cycle and the EMG offsets of all muscles (except GASoffset ) shifted earlier as the sprint progressed (P < 0.05). At the end of the sprint, CAIVAS/GAS and CAIGMAX/GAS were reduced by 48 ± 10% and 43 ± 12%, respectively. Our results show that substantial power reduction during fatiguing sprint cycling is accompanied by marked reductions in the EMG activity of bi-articular GAS and RF and co-activation level between GAS and main power producer muscles (GMAX and VAS). The observed changes in RF and GAS EMG activity are likely to result in a redistribution of the joint powers and alterations in the orientation of the pedal forces. © 2014 Published by Elsevier Ireland Ltd.
High performance during sprinting events (running, cycling) is strongly determined by the ability to produce and maintain maximal levels of muscular power. However, the ability of the central nervous system (CNS) to optimally coordinate the activation of the different muscles is also very important as it determines how
∗ Corresponding author at: Institute of Sport, Exercise and Active Living (ISEAL), Victoria University, PO Box 14428, Melbourne, VIC 8001, Australia. Tel.: +61 3 9919 4384. E-mail address: [email protected] (D.M. Rouffet).
the muscular forces are distributed across the joints and how the external force is orientated. If power production during sprint performances has been well documented [6,8,17], muscle coordination has received less attention, particularly during fatiguing sprints. Previous studies have provided detailed analyses of muscle coordination during fatigue-free sprint cycling, through the investigation of muscle activation patterns during the pedal cycle [5,20]. Surface EMG (EMG) studies of fatigue-free sprint cycling show that gastrocnemius (GAS) and quadriceps muscles [vasti (VAS) and rectus femoris (RF)] are maximally activated, while some discrepancies have been reported regarding activation level of the hamstrings (HAM) and gluteus maximus (GMAX) muscles [5,20]. Considering the high activation level of most lower-limb muscles during
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fatigue-free sprint cycling, neuromuscular fatigue (central and peripheral) is likely to occur during prolonged periods of sprint cycling (i.e. 30-s) [12], which may manifest as changes in muscular EMG activity (amplitude and/or timing). During a maximal 30-s cycling sprint, EMG activity of the quadriceps has been shown to decrease by ∼8% [4] or remain unaltered [9,13,19], whereas GAS muscles have shown a decrease of up to 15% [9]. A manipulation to the timing of activation for biceps femoris (BF) muscles during fatiguing sprint cycling has also been shown [2]. Unfortunately, none of these studies [2,4,9,13,19] analyzed changes in EMG activity using the recommendations made by recent extensive reviews [3,12]. Consequently, it seems difficult to describe the link between changes in muscle coordination with power deficit during fatiguing sprint cycling from this previous data. Martin and Brown [16] demonstrated that the power produced at the three lower-limb joints decreases at different rates during a maximal 30-s isokinetic (120 rpm) cycle sprint. In reference to biomechanical models of pedalling [25,27], it is possible that alterations in joint power [16] could be further understood by investigating changes in muscle co-activation. Van Ingen Schenau [25] explains that co-activation between GMAX/RF and VAS/HAM is essential to transfer muscular forces across the hip and knee joints and to optimize the orientation of the pedal forces. A decrease in coactivation between VAS/HAM has been suggested during fatiguing cycling sprints [2,10]. However, Zajac et al. [27] further suggests that co-activation between the ankle plantar flexors and proximal muscles (GMAX and VAS) is a key factor for optimizing power transfer across the ankle joint to the crank during cycling. Interestingly, Martin and Brown [16] observed the largest reduction in joint power at the ankle level over the course of a fatiguing cycling sprint (63%). However, no EMG studies have investigated changes in coactivation between the ankle plantar flexors and proximal muscles during fatiguing sprint cycling. The aim of the present study was to investigate changes in the EMG activity (amplitude and onsets/offsets) of the lower-limb muscles and associated modifications in muscle co-activations during a fatiguing 30-s cycling sprint for which detailed biomechanical data has been reported [16]. Changes in the EMG activity of five major lower-limb muscle groups were investigated by using gold standard methods for EMG normalization [3,20], calculation of EMG profiles [5,12] and quantification of co-activations [15]. Extending on the biomechanical findings of Martin and Brown [16], it was hypothesized that marked changes in the EMG activity of the ankle plantar flexor muscles (amplitude and timing) and/or coactivation of this muscle with proximal muscles would occur during the course of a fatiguing 30-s cycle sprint.
2. Materials and methods Ten active males volunteered to participate in this study (age 24 ± 3 years; body mass 83.7 ± 9.7 kg). Six were amateur team sport players (Australian Rules football, basketball and netball), three participated in individual sports (swimming, tennis and sprint athletics) and one was undertaking regular resistance training, with an overall training load of 5.3 ± 1.7 h/week. Written informed consent was obtained from each participant and all testing was approved by Victoria University’s Human Research Ethics Committee. Exercise was conducted on an electronically braked cycle ergometer (Excalibur Sport; Lode® , The Netherlands) which sampled power output at 5 Hz. Crank length equalled 175 mm and pedal straps were utilized to fasten feet into the pedals. Participants remained seated with hand position in the dropped portion of the handlebars during the sprint. A familiarization session took place no earlier than 48 h prior to testing. Following a warm-up [5-min cycling at 1 W/kg and 80
revolutions per minute (rpm)], each participant completed a practice 5-s sprint followed by 5 min of passive rest. For the 30-s sprint, participants were required to overcome the inertia of the flywheel and reach a cadence close to 120 rpm within 5 s to start time. Participants were stopped from pedalling and instructed to place the right crank angle at 45◦ before receiving a verbal 5-s countdown. For the sprint, the ergometer was set in isokinetic mode and cadence fixed at 120 rpm [16]. Power output was calculated over each pedalling cycle and normalized in reference to the peak power achieved during the sprint (PPEAK ). EMG signals were recorded from eight muscles of the left lower-limb [gluteus maximus (EMGGMAX ), rectus femoris (EMGRF ), vastus lateralis (VASLAT ), vastus medialis obliquus (VASMED ), semitendinosus (ST), biceps femoris long head (BF), gastrocnemius medialis (GASMED ) and gastrocnemius lateralis (GASLAT )]. Muscles from the same functional group were averaged to produce EMGGAS (GASLAT + GASMED ), EMGVAS (VASLAT + VASMED ) and EMGHAM (ST + BF). Dual surface electrodes of 10 mm diameter and inter-electrode distance of 20 mm (Noraxon dual electrodes, Noraxon USA Inc., Scottsdale, AZ) were used to record the EMG signals, with electrode location defined following SENIAM’s recommendations [11]. The reference electrode was placed over the superior aspect of the medial sacral crest. Prior to electrode application, skin was shaved, lightly abraded and cleaned with an alcohol swab to reduce skin impedance. Tubular netting was worn to limit movement artefacts. All signals were recorded continuously at 1500 Hz via a wireless receiver (Telemyo 2400 GT, Noraxon Inc., USA) connected to a notebook. A reed switch attached to the ergometer frame was aligned with a magnet attached to the left crank in order to identify 0/100% (TDC) of the left pedalling cycle from +3 V pulse recorded in a channel of the EMG system. EMG signals were recorded and processed using Noraxon software (MyoResearch XP version 1.07.41). Raw EMG signals were pre-amplified, band pass filtered (10–500 Hz) and full wave rectified. Following full wave rectification, the EMG signals were root mean squared with a 100 ms moving rectangular window to create a linear envelope. Each linear envelope was synchronized with the TDC sensor and time normalized to 100 points (100% of pedalling cycle, TDC-TDC) to create EMG activity profiles, which were then normalized in reference to the individual maximum value obtained during the sprint [5,12,20]. From each of the EMG profiles (i.e. 60), we calculated the average EMG amplitude and the EMG onset/offset of activation via determining a threshold of three standard deviations above the minimal EMG value [21]. Following this, one average EMG profile for each 6-s interval was constructed for each muscle group. Co-activation values were calculated from the normalized EMG activity profiles using the Co-activation Index (CAI) employed by Lewek et al. [15]. Based on the biomechanical models of cycling, changes in CAIs were calculated for VAS/HAM (CAIVAS/HAM ) and GMAX/RF (CAIGMAX/RF ) [25] as well as VAS/GAS (CAIVAS/GAS ) and GMAX/GAS (CAIGMAX/GAS ) [27]. Power output, EMG amplitude, onset/offset and CAIs was recorded for each pedalling cycle before average values were calculated for each variable over five even time intervals of 6 s duration (equivalent of 20% total sprint duration and 12 consecutive pedalling cycles). All data was analyzed using SPSS software (version 21, SPSS Inc., Chicago, IL). A two-way repeated measures ANOVA (muscle/CAI*time) with LSD post hoc comparisons was performed to evaluate differences between EMG (amplitude and onset/offset) and CAIs over each 6-s time interval of the sprint. Changes over time for mean power, individual EMG and CAIs were investigated via one-way repeated measures ANOVA. The significance level for all statistical tests was set at P < 0.05 and all data in text is reported as mean ± standard deviation.
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Fig. 1. Power output measured per pedalling cycle (% PPEAK ) throughout the duration of the sprint. Mean ± SD is also displayed for each time interval. *Significantly different from the initial time interval (P < 0.05). # Significantly different from the previous time interval (P < 0.05)
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3. Results PPEAK during the initial interval was 1043 ± 185 W (12.6 ± 2.5 W/kg). Absolute mean power for the five time intervals was as follows: 833 ± 213; 672 ± 118; 547 ± 91; 437 ± 79 and 335 ± 73 W representing relative reductions of 19 ± 9; 34 ± 8; 47 ± 7 and 60 ± 6% (P < 0.05) from the initial time interval (Fig. 1). Mean EMG amplitude was affected by time, with a general decrease occurring during the third time interval (i.e. 12–18 s) (P < 0.05). Mean EMG amplitude also varied between the muscles (P < 0.05) with EMGGAS displaying the highest mean amplitude (30 ± 1%) and EMGGMAX the lowest (24 ± 1%) over the full duration of the sprint. A combined effect of muscle and time was also observed for mean EMG amplitude (P < 0.05). All muscles other than EMGHAM displayed a significant decrease in EMG amplitude over time (P < 0.05), with EMGRF , EMGGAS and EMGVAS decreasing from the third time interval (P < 0.05) and EMGGMAX decreasing during the final interval (P < 0.05). At the end of the sprint, EMGRF (31 ± 16%) and EMGGAS (20 ± 14%) showed the greatest relative decrease in mean EMG amplitude. EMG onsets were affected by time and tended to occur later in the pedal cycle as the sprint progressed (P < 0.05). A combined effect of muscle and time was also displayed for EMG onsets (P < 0.05). GASonset occurred at significantly later periods of the pedal cycle during each time interval, whereas HAMonset and GMAXonset started to deviate from the initial interval during the second half of the sprint (P < 0.05). Over time, VASonset and RFonset were unaffected (P > 0.05) (Fig. 2). A global effect of time was also identified for EMG offsets, which tended to occur at earlier periods of the pedalling cycle as the sprint progressed. RFoffset occurred earlier than the initial 6 s during each time interval (P < 0.05). VASoffset deviated from the initial interval during the second half of the sprint, whereas HAMoffset and GMAXoffset both occurred earlier during the final interval only (P < 0.05). GASoffset did not fluctuate from the initial 6-s throughout the sprint (P > 0.05). Changes in the EMG profiles and average amplitude over the duration of the sprint are displayed in Fig. 2.
The general level of co-activation decreased over time (P < 0.05). A significant difference between all CAIs (P < 0.05) showed the lowest mean level of co-activation for CAIVAS/GAS (16 ± 1%) and the highest for CAIVAS/HAM (24 ± 2%). A combined effect for muscle pairs and time was also shown (P < 0.05). CAIVAS/GAS and CAIGMAX/GAS decreased over each time interval and displayed a relative decrease from the initial interval of 48 ± 10% and 43 ± 12% at the end of the sprint, respectively (P < 0.05) (Fig. 3). CAIGMAX/RF was lower than the initial interval during the second half of the sprint with an overall relative decrease of 38 ± 19%, while CAIVAS/HAM decreased during the final interval and displayed a relative decrease of 17 ± 21% (P < 0.05).
4. Discussion Our analysis started by verifying that individual EMG profiles and derived EMG values obtained during the first interval (0–6 s) were in line with that reported during fatigue-free sprint cycling [5,20], which provided us with a valid reference to investigate the effects of fatigue on muscle coordination during the sprint. Following this, we showed that fatigue during a 30-s isokinetic (120 rpm) sprint is associated with uneven changes in the EMG of individual muscles and the level of co-activation between different muscle pairs. The most pronounced changes consisted of a reduction in EMGGAS and EMGRF amplitude, which was associated with alterations in the occurrence of the EMG bursts during the pedalling cycle. These changes during the sprint resulted in a considerable decrease in co-activation between GAS and proximal power producing muscles (GMAX and VAS). The relative reduction in mean power of 60% was in line with that observed by Martin and Brown [16] during the same fatiguing cycling sprint. However, the reduction in mean power was greater than that displayed during a 30-s Wingate test (WAT) [4,9,13,19]. This difference in relative power decrease presumably occurred due to the completion of additional pedal revolutions (∼13) [26] which would have increased the level of fatigue [24]. Interestingly, this
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Fig. 2. EMG profiles of each muscle for all time intervals (left column), average EMG amplitude (middle column) and activation onsets/offsets (right column) for each completed pedal cycle. Mean ± SD is also displayed for each time interval of the sprint. Individual muscles are displayed on separate rows. *Significantly different from the initial time interval (P < 0.05). # Significantly different from the previous time interval (P < 0.05).
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Fig. 3. Co-activation profiles for each muscle pair (left column) and average CAI for each pedal cycle (right column). Mean ± SD is also displayed for each time interval of the sprint. Each CAI pair is displayed on separate rows. *Significantly different from the initial time interval (P < 0.05). # Significantly different from the previous time interval (P < 0.05)
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difference coincided with larger decreases in EMG amplitude of all lower-limb muscles when compared to previous WAT studies [4,9,13,19], suggesting that the magnitude of power reduction may be associated with a greater EMG decrease in the lower-limb muscles. The uneven decrease in EMG across the lower-limb muscles is in line with the biomechanical findings from Martin and Brown [16] who showed different rates of joint power reduction during the same type of fatiguing sprint. Such a decrease in EMG activity during a maximal exercise may reflect the occurrence of fatigue, with a central or peripheral origin [7]. However, where Martin and Brown [16] showed decrements in joint power of up to ∼60%, our
EMG decreases were much lower, suggesting that power decrease during a 30-s isokinetic cycle sprint could be largely explained by peripheral fatigue [1]. For example, we identified no alteration in EMGHAM amplitude, whereas Martin and Brown [16] displayed a 47% decrease in knee flexion power. Furthermore, we displayed a 20% decrease in EMGGAS amplitude compared to the 63% decrease in ankle joint power observed by Martin and Brown [16]. It has been shown that GAS muscles transfer a large proportion (>50%) of the power produced by the proximal mono-articular muscles (GMAX and VAS) to the crank during maximal cycling, whereas the demand placed on RF for power transfer is much less [18,27]. However, the
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muscle fibre composition of RF (higher % type II muscle fibres) [14] makes this muscle more susceptible to fatigue development than GAS during maximal exercise [23], which could explain the greater decrease in EMG amplitude. In light of Martin and Brown findings [16], the large reduction in EMGRF amplitude is likely to decrease knee extension power and generate negative hip joint power (during the upstroke phase) over the course of the fatiguing cycling sprint. If muscle fatigue can explain the alteration in EMG activity, a fatigue-independent adjustment could also explain the EMG decrease. For example, in reference to biomechanical models [27], the decrease in EMGGAS amplitude may occur to adjust to a reduced power production from GMAX and VAS. This hypothesis cannot be excluded as our results showed a significant reduction in EMGGMAX and EMGVAS amplitude, which is in line with the reduction of the hip knee extension powers observed during fatiguing sprint cycling [16]. Furthermore, the decrease in EMGGAS amplitude could be aimed at reducing the range of motion (ROM) of the ankle joint and simplifying the complexity of the pedalling movement during the course of the fatiguing sprint [16]. If this reduction in ankle joint ROM occurred in the present study, this would decrease GAS shortening velocity and further reduce the EMG activity of these muscles [22]. Finally, the general observation across all lower-limb muscles of a later EMG onset and earlier EMG offset suggests that the CNS may increase the time for muscular relaxation in an attempt to limit fatigue development. According to the biomechanical models of cycling [25,27], the large reductions in co-activation between the bi-articular GAS and RF with the proximal GMAX and VAS, would have substantially decreased the amount of power transferred across the joint to the crank. However, it is difficult to determine the exact mechanisms leading to these reductions. For example, during the second interval of the sprint (6–12 s), co-activation between GAS and proximal muscles reduced through a manipulation to GASonset only. This suggests that a change in the coordination of a bi-articular muscle may influence the level of co-activation with a mono-articular muscle and affect joint power distribution and power production. In addition to transferring power generated by VAS and GMAX across the joints, the bi-articular RF and GAS also optimize the orientation of the external force applied to the pedal around the transition phases [25,27]. Therefore, the observed reduction in the EMGRF and EMGGAS during the fatiguing sprint may result in a reduction of the horizontal components of the force applied to the pedal around top (oriented forward) and bottom (oriented backward) dead centres, respectively. Such alterations can potentially decrease the magnitude of the tangential component of the force applied to the pedal and reduce the amount of power transmitted to the crank.
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Our results clearly show that EMG activity and muscular coactivation decreases at different rates between the lower-limb muscles during a fatiguing cycling sprint. In light of previous biomechanical findings and models, the changes in the EMG activity of the bi-articular muscles observed in this study may result from localized muscle fatigue or changes in the pedalling movement control strategy. Future research combining EMG and biomechanical measurements is warranted to extend our understanding of the respective roles played by fatigue and motor control in the
changes of muscle coordination, forces applied to the pedals and power transmitted to the crank during fatiguing sprint cycling. Acknowledgements The authors would like to sincerely thank the reviewers of the manuscript for their constructive criticism and valuable comments. References [1] B. Bigland-Ritchie, J.J. Woods, Changes in muscle contractile properties and neural control during human muscular fatigue, Muscle Nerve 7 (9) (1984) 691–699. [2] F. Billaut, F.A. Basset, G. Falgairette, Muscle coordination changes during intermittent cycling sprints, Neurosci. Lett. 380 (3) (2005) 265–269. [3] A. Burden, How should we normalize electromyograms obtained from healthy participants? What we have learned from over 25 years of research, J. Electromyogr. Kinesiol. 20 (6) (2010) 1023–1035. [4] H. Chtourou, et al., Diurnal variation in Wingate-test performance and associ- Q2 ated electromyographic parameters, Chronobiol. Int. 28 (8) (2011) 706–713. [5] S. Dorel, et al., Adjustment of muscle coordination during an all-out sprint cycling task, Med. Sci. Sports Exerc. 44 (11) (2012) 2154–2164. [6] S. Dorel, et al., Torque and power-velocity relationships in cycling: relevance to track sprint performance in world-class cyclists, Int. J. Sports Med. 26 (9) (2005) 739–746. [7] D. Farina, R. Merletti, R.M. Enoka, The extraction of neural strategies from the surface EMG, J. Appl. Physiol. 96 (4) (2004) 1486–1495. [8] A.S. Gardner, et al., Velocity-specific fatigue: quantifying fatigue during variable velocity cycling, Med. Sci. Sports Exerc. 41 (4) (2009) 904. [9] F. Greer, J. Morales, M. Coles, Wingate performance and surface EMG frequency variables are not affected by caffeine ingestion, Appl. Physiol. Nutr. Metab. 31 (5) (2006) 597–603. [10] C.A. Hautier, et al., Influence of fatigue on EMG/force ratio and cocontraction in cycling, Med. Sci. Sports Exerc. 32 (4) (2000) 839–843. [11] H.J. Hermens, et al., European Recommendations for Surface Electromyography, Roessingh Research and Development, 1999. [12] F. Hug, S. Dorel, Electromyographic analysis of pedaling: a review, J. Electromyogr. Kinesiol. 19 (2) (2009) 182–198. [13] A.M. Hunter, et al., Effects of supramaximal exercise on the electromyographic signal, Br. J. Sports Med. 37 (4) (2003) 296–299. [14] M.A. Johnson, et al., Data on the distribution of fibre types in thirty-six human muscles. An autopsy study, J. Neurol. Sci. 18 (1) (1973) 111–129. [15] M.D. Lewek, K.S. Rudolph, L. Snyder-Mackler, Control of frontal plane knee laxity during gait in patients with medial compartment knee osteoarthritis, Osteoarthr. Cartil. 12 (9) (2004) 745–751. [16] J.C. Martin, N.A. Brown, Joint-specific power production and fatigue during maximal cycling, J. Biomech. 42 (4) (2009) 474–479. [17] J.-B. Morin, et al., Mechanical determinants of 100-m sprint running performance, Eur. J. Appl. Physiol. 112 (11) (2012) 3921–3930. [18] C.C. Raasch, et al., Muscle coordination of maximum-speed pedaling, J. Biomech. 30 (6) (1997) 595–602. [19] S.R. Rana, Effect of the Wingate test on mechanomyography and electromyography, J. Strength Cond. Res. 20 (2) (2006) 292–297. [20] D.M. Rouffet, C.A. Hautier, EMG normalization to study muscle activation in cycling, J. Electromyogr. Kinesiol. 18 (5) (2008) 866–878. [21] D.M. Rouffet, et al., Timing of muscle activation of the lower limbs can be modulated to maintain a constant pedaling cadence, J. Electromyogr. Kinesiol. 19 (6) (2009) 1100–1107. [22] D.J. Sanderson, et al., Gastrocnemius and soleus muscle length: velocity, and EMG responses to changes in pedalling cadence, J. Electromyogr. Kinesiol. 16 (6) (2006) 642–649. [23] S. Schiaffino, C. Reggiani, Fiber types in mammalian skeletal muscles, Physiol. Rev. 91 (4) (2011) 1447–1531. [24] A. Tomas, E.Z. Ross, J.C. Martin, Fatigue during maximal sprint cycling: unique role of cumulative contraction cycles, Med. Sci. Sports Exerc. 42 (7) (2010) 1364–1369. [25] G.J. Van Ingen Schenau, From rotation to translation: constraints on multi-joint movements and the unique action of bi-articular muscles, Hum. Mov. Sci. 8 (4) (1989) 301–337. [26] C. Williams, J. Doust, A. Hammond, Power output and VO2 responses during 30 s maximal isokinetic cycle sprints at different cadences in comparison to the Wingate test, Isokin. Exerc. Sci. 14 (4) (2006) 327–333. [27] F.E. Zajac, R.R. Neptune, S.A. Kautz, Biomechanics and muscle coordination of human walking. Part I: introduction to concepts, power transfer, dynamics and simulations, Gait Posture 16 (3) (2002) 215–232.
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