Electromyographic analysis of pedaling: a review

Influence of musculo-tendinous stiffness of the plantar ankle flexor muscles upon maximal power output on a cycle ergometre

The importance of maximal voluntary torque (T (MVC)), maximal rate of torque development (MRTD) and musculo-tendinous stiffness of the triceps surae for maximal power output on a cycle ergometre (Pmax) was studied in 21 healthy subjects by studying the relationships between maximal cycling power related to body mass (Pmax BM(-1)) with T (MVC), MRTD and different indices of musculo-tendinous stiffness of the ankle flexor. Pmax BM(-1) was calculated from the data of an all-out force-velocity test on a Monark cycle ergometre. T (MVC) and MRTD were measured on a specific ankle ergometre. Musculo-tendinous stiffness was estimated by means of quick releases at 20, 40, 60 and 80% T (MVC) on the same ankle ergometre. Pmax BM(-1) was significantly and positively correlated with MRTD related to body mass but the positive correlation between Pmax BM(-1) and T (MVC) did not reach the significance level (0.05). Pmax BM(-1) was significantly and positively correlated with the estimation of stiffness at 40% T (MVC) (S(0.4)), but not with stiffness at 20, 60 and 80% T (MVC). The results of the present study suggest that maximal power output during cycling is significantly correlated with the level of musculo-tendinous stiffness which corresponds to torque range around peak torque at optimal pedal rate. However, the low coefficient of determination (r2 = 0.203) between Pmax BM(-1) and S (0.4) BM(-1) suggested that Pmax BM(-1) largely depended on other factors than the musculo-tendinous stiffness of the only plantar flexors.

Muscle coordination during an outdoor cycling time trial

INTRODUCTION/PURPOSE

Muscle activity in cycling has primarily been studied in the laboratory; however, conclusions are limited by the ability to recreate realistic environmental conditions. The purpose of this study was to determine muscle coordination patterns in an outdoor time trial and investigate their relationships to power output (PO), total muscle activity (Itot), overall mechanical efficiency (ηO), cadence, and gradient.

METHODS

Surface EMG, gradient, and cycling parameters were measured while cycling 18.8 km outdoors. A principal component analysis was used to establish coordination patterns that were compared with Itot, ηO, PO, cadence, and gradient.

RESULTS

PO was positively correlated with Itot, and high PO was associated with elevated rectus femoris and vastus lateralis activity and synchronization of muscles crossing the same joint. PO and cadence demonstrated positive and negative relationships, respectively, with gradient. Relationships between muscle coordination, PO, ηO, Itot, and gradient showed that muscle coordination, PO, and ηO fluctuate during an outdoor time trial as a result of pacing and gradient. A trade-off existed between ηO and PO, and ηO was dependent on muscle activation around the top and bottom of the pedal cycle and activity in more than the knee extensor muscles. Fluctuations in muscle activity due to the changing PO, from pacing and terrain, seemed to mitigate fatigue indices seen in indoor cycling studies.

CONCLUSIONS

This study provides evidence that muscle activity is dependent on the terrain aspects of the cycle course as muscle coordination changes with the altered locomotor demands. The coordination patterns significantly covaried with PO, Itot, ηO, cadence, and gradient, which highlights the importance of recording these parameters under field conditions and/or careful reproduction of outdoor environments in indoor studies.

Diurnal variation in Wingate-test performance and associated electromyographic parameters

The present study was designed to evaluate time-of-day effects on electromyographic (EMG) activity changes during a short-term intense cycling exercise. In a randomized order, 22 male subjects were asked to perform a 30-s Wingate test against a constant braking load of 0.087 kg·kg(-1) body mass during two experimental sessions, which were set up either at 07:00 or 17:00 h. During the test, peak power (P(peak)), mean power (P(mean)), fatigue index (FI; % of decrease in power output throughout the 30 s), and evolution of power output (5-s span) throughout the exercise were analyzed. Surface EMG activity was recorded in both the vastus lateralis and vastus medialis muscles throughout the test and analyzed over a 5-s span. The root mean square (RMS) and mean power frequency (MPF) of EMG were calculated. Neuromuscular efficiency (NME) was estimated from the ratio of power to RMS. Resting core temperature, P(peak), P(mean), and FI were significantly higher (p < .05) in the evening than morning test (e.g., P(peak): 11.6 ± 0.8 vs. 11.9 ± 1 W·kg(-1)). The results showed that power output decreased following two phases. During the first phase (first 20s), power output decreased rapidly and values were higher (p < .05) in the evening than in the morning. During the second phase (last 10s), power decreased slightly and appeared independent of the time of day of testing. This power output decrease was paralleled by evolution of the MPF and NME. During the first phase, NME and MPF were higher (p < .05) in the evening. During the second phase, NME and MPF were independent of time of day. In addition, no significant differences were noticed between 7:00 and 17:00 h for EMG RMS during the whole 30 s. Taken together, these results suggest that peripheral mechanisms (i.e., muscle power and fatigue) are more likely the cause of the diurnal variation of the Wingate-test performance rather than central mechanisms.

Consistency of muscle synergies during pedaling across different mechanical constraints

The purpose of the present study was to determine whether muscle synergies are constrained by changes in the mechanics of pedaling. The decomposition algorithm used to identify muscle synergies was based on two components: “muscle synergy vectors,” which represent the relative weighting of each muscle within each synergy, and “synergy activation coefficients,” which represent the relative contribution of muscle synergy to the overall muscle activity pattern. We hypothesized that muscle synergy vectors would remain fixed but that synergy activation coefficients could vary, resulting in observed variations in individual electromyographic (EMG) patterns. Eleven cyclists were tested during a submaximal pedaling exercise and five all-out sprints. The effects of torque, maximal torque-velocity combination, and posture were studied. First, muscle synergies were extracted from each pedaling exercise independently using non-negative matrix factorization. Then, to cross-validate the results, muscle synergies were extracted from the entire data pooled across all conditions, and muscle synergy vectors extracted from the submaximal exercise were used to reconstruct EMG patterns of the five all-out sprints. Whatever the mechanical constraints, three muscle synergies accounted for the majority of variability [mean variance accounted for (VAF) = 93.3 ± 1.6%, VAF muscle > 82.5%] in the EMG signals of 11 lower limb muscles. In addition, there was a robust consistency in the muscle synergy vectors. This high similarity in the composition of the three extracted synergies was accompanied by slight adaptations in their activation coefficients in response to extreme changes in torque and posture. Thus, our results support the hypothesis that these muscle synergies reflect a neural control strategy, with only a few timing adjustments in their activation regarding the mechanical constraints.

Relation between cycling exercise capacity, fiber-type composition, and lower extremity muscle strength and muscle endurance

The aim of the study was to determine the relation between peak oxygen uptake V(O2)peak), peak work rate (WRpeak), fiber-type composition, and lower extremity strength and endurance during a maximal incremental cycle test. Thirty-nine healthy sedentary men, aged 30-46, participated in the study. Subjects performed a maximal incremental cycle test and isokinetic knee extension (KE) and flexion (KF) strength and endurance tests at velocities of 60 and 180° · s(-1). Muscle biopsies were taken from m. vastus lateralis and analyzed for fiber-type composition. A significant correlation existed between KE strength and V(O2)peak and WRpeak. Also, KF endurance correlated significantly to V(O2)peak and WRpeak. The KE endurance correlated significantly to WRpeak (rp = 0.32, p < 0.05) and almost significantly to V(O2)peak (rp = 0.28, p = 0.06). Stepwise multiple regression analyses showed that KE strength, KF endurance, and the percentage of type I fibers could explain up to 40% of the variation in V(O2) and WRpeak. The performance of sedentary subjects in a maximal incremental cycle test is highly affected by knee muscle strength and endurance. Fiber-type composition also contributes but to a smaller extent.

Effect of power output on muscle coordination during rowing

The present study was designed to quantify the effect of power output on muscle coordination during rowing. Surface electromyographic (EMG) activity of 23 muscles and mechanical variables were recorded in eight untrained subjects and seven experienced rowers. Each subject was asked to perform three 2-min constant-load exercises performed at 60, 90 and 120% of the mean power output over a maximal 2,000-m event (denoted as P60, P90, and P120, respectively). A decomposition algorithm (nonnegative matrix factorization) was used to extract the muscle synergies that represent the global temporal and spatial organization of the motor output. The results showed a main effect of power output for 22 of 23 muscles (p values ranged from <0.0001 to 0.004) indicating a significant increase in EMG activity level with power output for both untrained and experienced subjects. However, for the two populations, no dramatic modification in the shape of individual EMG patterns (mean r (max) value = 0.93 ± 0.09) or in their timing of activation (maximum lag time = -4.3 ± 3.8% of the rowing cycle) was found. The results also showed a large consistency of the three extracted muscle synergies, for both synergy activation coefficients (mean r (max) values range from 0.87 to 0.97) and muscle synergy vectors (mean r values range from 0.70 to 0.76) across the three power outputs. In conclusion, despite significant changes in the level of muscle activity, the global temporal and spatial organization of the motor output is very little affected by power output on a rowing ergometer.

The Effect of Saddle Position on Maximal Power Output and Moment Generating Capacity of Lower Limb Muscles during Isokinetic Cycling

Saddle position affects mechanical variables during submaximal cycling, but little is known about its effect on mechanical performance during maximal cycling. Therefore, this study relates saddle position to experimentally obtained maximal power output and theoretically calculated moment generating capacity of hip, knee and ankle muscles during isokinetic cycling. Ten subjects performed maximal cycling efforts (5 s at 100 rpm) at different saddle positions varying ± 2 cm around the in literature suggested optimal saddle position (109% of inner leg length), during which crank torque and maximal power output were determined. In a subgroup of 5 subjects, lower limb kinematics were additionally recorded during submaximal cycling at the different saddle positions. A decrease in maximal power output was found for lower saddle positions. Recorded changes in knee kinematics resulted in a decrease in moment generating capacity of biceps femoris, rectus femoris and vastus intermedius at the knee. No differences in muscle moment generating capacity were found at hip and ankle. Based on these results we conclude that lower saddle positions are less optimal to generate maximal power output, as it mainly affects knee joint kinematics, compromising mechanical performance of major muscle groups acting at the knee.

Force-velocity relationship in cycling revisited: benefit of two-dimensional pedal forces analysis

PURPOSE

Maximal cycling exercise has been widely used to describe the power-velocity characteristics of lower-limb extensor muscles. This study investigated the contribution of each functional sector (i.e., extension, flexion, and transitions sectors) on the total force produced over a complete pedaling cycle. We also examined the ratio of effective force to the total pedal force, termed index of mechanical effectiveness (IE), in explaining differences in power between subjects.

METHODS

Two-dimensional pedal forces and crank angles were measured during a cycling force-velocity test performed by 14 active men. Mean values of forces, power output, and IE over four functional angular sectors were assessed: top = 330 degrees -30 degrees , downstroke = 30 degrees -150 degrees , bottom = 150 degrees -210 degrees , and upstroke = 210 degrees -330 degrees .

RESULTS

Linear and quadratic force-velocity and power-velocity relationships were obtained for downstroke and upstroke. Maximal power output (Pmax) generated over these two sectors represented, respectively, 73.6% +/- 2.6% and 10.3% +/- 1.8% of Pmax assessed over the entire cycle. In the whole group, Pmax over the complete cycle was significantly related to Pmax during the downstroke and upstroke. IE significantly decreased with pedaling rate, especially in bottom and upstroke. There were significant relationships between power output and IE for top and upstroke when the pedaling rate was below or around the optimal value and in all the sectors at very high cadences.

CONCLUSIONS

Although data from force-velocity test primarily characterize the muscular function involved in the downstroke phase, they also reflect the flexor muscles' ability to actively pull on the pedal during the upstroke. IE influences the power output in the upstroke phase and near the top dead center, and IE accounts for differences in power between subjects at high pedaling rates.

In-season strength maintenance training increases well-trained cyclists' performance

We investigated the effects of strength maintenance training on thigh muscle cross-sectional area (CSA), leg strength, determinants of cycling performance, and cycling performance. Well-trained cyclists completed either (1) usual endurance training supplemented with heavy strength training twice a week during a 12-week preparatory period followed by strength maintenance training once a week during the first 13 weeks of a competition period (E + S; n = 6 [♂ = 6]), or (2) usual endurance training during the whole intervention period (E; n = 6 [♂ = 5, ♀ = 1]). Following the preparatory period, E + S increased thigh muscle CSA and 1RM (p < 0.05), while no changes were observed in E. Both groups increased maximal oxygen consumption and mean power output in the 40-min all-out trial (p < 0.05). At 13 weeks into the competition period, E + S had preserved the increase in CSA and strength from the preparatory period. From the beginning of the preparatory period to 13 weeks into the competition period, E + S increased peak power output in the Wingate test, power output at 2 mmol l(-1) [la(-)], maximal aerobic power output (W (max)), and mean power output in the 40-min all-out trial (p < 0.05). The relative improvements in the last two measurements were larger than in E (p < 0.05). For E, W (max) and power output at 2 mmol l(-1) [la(-)] remained unchanged. In conclusion, in well-trained cyclists, strength maintenance training in a competition period preserved increases in thigh muscle CSA and leg strength attained in a preceding preparatory period and further improved cycling performance determinants and performance.

The effect of cadence on timing of muscle activation and mechanical output in cycling: on the activation dynamics hypothesis

The purpose of this study was to examine the activation dynamics hypothesis, which states that, in cycling, the pattern between muscle activity and crank position shifts in regard to its angle in the crank cycle with increasing cadence to maintain invariant positioning of the mechanical output. We measured surface EMG of six muscles, and by means of force measurements at the crank and inverse dynamics calculated hip, knee, and ankle joint dynamics during cycling at five cadences (60-100 rpm) at 75% of maximal power in trained cyclists. The joint dynamics (net muscle moment and power) showed a consistent positive phase shift with increasing cadence. The phase shift in muscle activation patterns was highly variable amongst subjects and was, on average, close to zero. Our results are in contradiction with the activation dynamics hypothesis.

Prolonged activity of knee extensors and dorsal flexors is associated with adaptations in gait in diabetes and diabetic polyneuropathy

BACKGROUND

People with diabetes or diabetic polyneuropathy often experience limitations in mobility and gait. These limitations are believed to be related to disturbed muscle function and sensory information. In previous studies on diabetic gait, results were confounded by a lower, preferred walking speed in people with diabetes or diabetic polyneuropathy. This study aimed to identify gait-velocity independent effects of diabetes and diabetic polyneuropathy on lower extremity kinematics and muscle activation patterns.

METHODS

Eight people with diabetic polyneuropathy, 10 diabetic controls without polyneuropathy and ten healthy, age-matched controls walked at their preferred velocity and a standard velocity of 1.4 ms(-1). Muscle activation patterns of gluteus maximus, biceps femoris, rectus femoris, vastus medialis, gastrocnemius medialis, soleus, and tibialis anterior, and spatiotemporal and joint angles characteristics were analysed.

FINDINGS

Independent of walking speed, muscle activation differed between groups. In diabetic polyneuropathy participants activation of ankle-joint dorsal flexors was prolonged by 5-10% of the stride cycle. Activity of monoarticular knee-joint extensors lasted about 10% longer in both diabetic groups compared to healthy elderly. Initiation of muscle activity did not differ between groups. If gait velocity was controlled, spatiotemporal characteristics were similar between groups.

INTERPRETATION

The study showed that independent of the preferred lower gait velocity, people with diabetes or diabetic polyneuropathy adjust the timing of muscle activity. Contrarily, the concurrent changes in spatiotemporal characteristics occurred to be the result of changed velocity only. The delayed cessation of muscle activity suggested a reduced rate of force development underlying the adjusted timing of muscle activation.

Is interindividual variability of EMG patterns in trained cyclists related to different muscle synergies?

Our aim was to determine whether muscle synergies are similar across trained cyclists (and thus whether the same locomotor strategies for pedaling are used), despite interindividual variability of individual EMG patterns. Nine trained cyclists were tested during a constant-load pedaling exercise performed at 80% of maximal power. Surface EMG signals were measured in 10 lower limb muscles. A decomposition algorithm (nonnegative matrix factorization) was applied to a set of 40 consecutive pedaling cycles to differentiate muscle synergies. We selected the least number of synergies that provided 90% of the variance accounted for VAF. Using this criterion, three synergies were identified for all of the subjects, accounting for 93.5+/-2.0% of total VAF, with VAF for individual muscles ranging from 89.9+/-8.2% to 96.6+/-1.3%. Each of these synergies was quite similar across all subjects, with a high mean correlation coefficient for synergy activation coefficients (0.927+/-0.070, 0.930+/-0.052, and 0.877+/-0.110 for synergies 1-3, respectively) and muscle synergy vectors (0.873+/-0.120, 0.948+/-0.274, and 0.885+/-0.129 for synergies 1-3, respectively). Despite a large consistency across subjects in the weighting of several monoarticular muscles into muscle synergy vectors, we found larger interindividual variability for another monoarticular muscle (soleus) and for biarticular muscles (rectus femoris, gastrocnemius lateralis, biceps femoris, and semimembranosus). This study demonstrated that pedaling is accomplished by the combination of the similar three muscle synergies among trained cyclists. The interindividual variability of EMG patterns observed during pedaling does not represent differences in the locomotor strategy for pedaling.

Muscle coordination is key to the power output and mechanical efficiency of limb movements

The purpose of this study was to determine which features of muscle mechanics and muscle coordination affect the power output from a limb during locomotion. Eight subjects were tested while cycling at maximum exertion for 25 min on a stationary dynamometer. Cadence and load were varied to span a range of power outputs and myoelectric activity was measured from 10 muscles in the leg. Cycle-by-cycle variations in muscle coordination, cadence and power output were observed and the EMG intensity across all muscles was used as an estimate of the metabolic cost for each cycle. Data for the cycles at greatest power output were separated into three groups: maximum power, 80% power but lower EMG intensity and 80% power and higher EMG intensity. Torque-angular velocity relations were determined for the ankle and knee joints. During cycling at maximum power output the ankle joint was not extending at the velocity necessary for maximum power output; thus, maximum limb power occurs when some of the individual muscles cannot be generating maximum power output. Increases in EMG intensity occurred with no increase in power output from the limb: these corresponded to decreases in the efficiency and changes in coordination. Increases in power were achieved that were not matched by equivalent increases in EMG intensity, but did occur with changes in coordination. It is proposed that the power output from the limb is limited by the coordination pattern of the muscles rather than the maximum power output from any one muscle itself.

Effects of a noncircular chainring system on muscle activation during cycling

Previous studies evaluated cycling with noncircular chainrings and suggested that changes in muscle activation would occur in response to altered pedaling mechanics throughout the crank arm revolution. However, no previous study addressed this question. The aim of this study was to compare the magnitude of muscular activity between a conventional and a noncircular crank system during an incremental maximal cycling test. Seven mountain-bike trained cyclists completed two incremental maximal tests, separated by 48 h, one for each crank system. Each test started with a workload of 100 W and was increased by 30 W every minute until exhaustion. Power output, pedaling cadence and heart rate were monitored and compared between the crank systems using paired t-tests. Surface EMG was recorded from the right rectus femoris, vastus medialis, biceps femoris and gastrocnemius medialis. EMG was compared using a general linear model considering as factors the crank system and workload with post hoc analysis at α=0.05. RMS presented effect of workload, but no effect of crank system was found for the muscles analyzed. The present results do not support effects of the noncircular crank system on variables of performance and muscle activation during incremental cycling in trained mountain bike cyclists.

Can the electromyographic fatigue threshold be determined from superficial elbow flexor muscles during an isometric single-joint task?

The purpose of this study was to compare the electromyographic fatigue threshold (EMG(FT)) values determined simultaneously from superficial elbow flexor muscles during an isometric single-joint task. Eight subjects performed isometric elbow flexions at randomly ordered percentages of maximal voluntary contraction (20, 30, 40, 50 and 60%). During these bouts, electromyographic (EMG) activity was measured in the anterior head of Deltoïd, lateral head of Triceps brachii, Brachioradialis and both short and long head of Biceps brachii. For each subject and each muscle, the EMG amplitude data were plotted as function of time for the five submaximal bouts. The slope coefficient of the EMG amplitude versus time linear relationships were plotted against force level. EMG(FT) was determined as the y-intercept of this relationship and considered as valid only if the following criteria were met: (1) significant positive linear regression (P < 0.05) between force and slope coefficient, (2) an adjusted coefficient of determination for force versus slope coefficient relationship greater than 0.85, and (3) a standard error for the EMG(FT) below 5% of maximal voluntary contraction. The EMG(FT) could only be determined for one muscle (the long head of Biceps brachii) and only in three out of the eight subjects (mean value = 24.9 +/- 1.1% of maximal voluntary contraction). The lack of EMG(FT) in most of the subjects (5/8) could be explained by putative compensations between elbow muscles which were indirectly observed in some subjects. In this way, EMG(FT) should be studied from a more simple movement i.e., ideally a movement implying mainly one muscle.