The vastus lateralis neuromuscular activity during all-out cycling exercise

Local passive heating administered during recovery impairs subsequent isokinetic knee extension exercise performance

BACKGROUND: Passive heating has attracted attention as a potentially promising recovery modality in sports. However, investigations of passive heating have yielded only inconsistent results for exercise performance. OBJECTIVE: To investigate the acute effects of local passive heating administered between repeated bouts of isokinetic exercise. METHODS: The experiment was a randomized crossover study. There was a total of three visits including a familiarization visit. During the remaining two visits, eleven healthy men performed three bouts of nine sets of isokinetic knee extensions using their dominant single-leg (30 repetitions/set, 180∘/sec). A 15 min recovery, during which a local passive heating pad at control (CON) or heating (HT) was applied to the rectus femoris, was afforded after the 3rd and 6th sets (Recovery 1 and 2). Isokinetic exercise performance, as assessed by peak torque, total work, and average power was analyzed using two-way repeated-measures ANOVA. RESULTS: Following Recovery 1 and 2, isokinetic exercise performance, as assessed by peak torque, total work, and average power was reduced in Set 4 (p< 0.001, p< 0.001, p= 0.080) and Set 7 (p< 0.001, p< 0.001, p= 0.009) in the HT group relative to the CON group. Electromyography analysis revealed that signal amplitude was lower in the HT group in Set 4 (p< 0.001) subsequent to Recovery 1, and that firing frequency was higher in Set 7 (p= 0.002) in the HT group after Recovery 2. Furthermore, EMG time-frequency maps from one representative participant showed that following Recovery 1 and 2 peak energy decreased during the first five repetitions in Set 4 and 7. CONCLUSIONS: Local passive heating administered during recovery decreased subsequent performance of isokinetic knee extensors, muscle activation ability and increased firing frequency maintaining force output. Therefore, local passive heating is not an appropriate acute recovery strategy for isokinetic exercises.

Neuromuscular Fatigue Responses of Endurance- and Strength-Trained Athletes during Incremental Cycling Exercise

This study explored the development of neuromuscular fatigue responses during progressive cycling exercise. The sample comprised 32 participants aged 22.0 ± 0.54 years who were assigned into three groups: endurance-trained group (END, triathletes, n = 10), strength-trained group (STR, bodybuilders, n = 10) and control group (CG, recreationally active students, n = 12). The incremental cycling exercise was performed using a progressive protocol starting with a 3 min resting measurement and then 50 W workload with subsequent constant increments of 50 W every 3 min until 200 W. Surface electromyography (SEMG) of rectus femoris muscles was recorded during the final 30 s of each of the four workloads. During the final 15 s of each workload, participants rated their overall perception of effort using the 20-point rating of the perceived exertion (RPE) scale. Post hoc Tukey’s HSD testing showed significant differences between the END and STR groups in median frequency and mean power frequency across all workloads (p < 0.001 and p < 0.01, respectively). Athletes from the END group had significantly lower electromyogram amplitude responses than those from the STR (p = 0.0093) and CG groups (p = 0.0006). Increasing RPE points from 50 to 200 W were significantly higher in the STR than in the END group (p < 0.001). In conclusion, there is a significant variation in the neuromuscular fatigue profiles between athletes with different training backgrounds when a cycling exercise is applied. The approximately linear trends of the SEMG and RPE values of both groups of athletes with increasing workload support the increased skeletal muscle recruitment with perceived exertion or fatiguing effect.

The Refined Composite Downsampling Permutation Entropy Is a Relevant Tool in the Muscle Fatigue Study Using sEMG Signals

Surface electromyography (sEMG) is a valuable technique that helps provide functional and structural information about the electric activity of muscles. As sEMG measures output of complex living systems characterized by multiscale and nonlinear behaviors, Multiscale Permutation Entropy (MPE) is a suitable tool for capturing useful information from the ordinal patterns of sEMG time series. In a previous work, a theoretical comparison in terms of bias and variance of two MPE variants—namely, the refined composite MPE (rcMPE) and the refined composite downsampling (rcDPE), was addressed. In the current paper, we assess the superiority of rcDPE over MPE and rcMPE, when applied to real sEMG signals. Moreover, we demonstrate the capacity of rcDPE in quantifying fatigue levels by using sEMG data recorded during a fatiguing exercise. The processing of four consecutive temporal segments, during biceps brachii exercise maintained at 70% of maximal voluntary contraction until exhaustion, shows that the 10th-scale of rcDPE was capable of better differentiation of the fatigue segments. This scale actually brings the raw sEMG data, initially sampled at 10 kHz, to the specific 0–500 Hz sEMG spectral band of interest, which finally reveals the inner complexity of the data. This study promotes good practices in the use of MPE complexity measures on real data.

A Comparative Study of EMG Indices in Muscle Fatigue Evaluation Based on Grey Relational Analysis during All-Out Cycling Exercise

The increased popularization of cycling has brought an increase in cycling-related injuries, which has been suggested to be associated with muscle fatigue. However, it still remains unclear on the utility of different EMG indices in muscle fatigue evaluation induced by cycling exercise. In this study, ten cyclist volunteers performed a 30-second all-out cycling exercise after a warm-up period. Surface electromyography (sEMG) from vastus lateralis muscle (VL) and power output and cadence were recorded and EMG RMS, MF and MPF based on Fourier Transform, MDF and MNF based on wavelet packet transformation, and C(n) based on Lempel–Ziv complexity algorithm were calculated. Utility of the indices was compared based on the grey rational grade of sEMG indices and power output and cadence. The results suggested that MNF derived from wavelet packet transformation was significantly higher than other EMG indices, indicating the potential application for fatigue evaluation induced by all-out cycling exercise.

Influence of Affective Stimuli on Leg Power Output and Associated Neuromuscular Parameters during Repeated High Intensity Cycling Exercises

The aim of this study was to examine the impact of emotional eliciting pictures on neuromuscular performance during repetitive supramaximal cycling exercises (RSE). In a randomized order, twelve male participants were asked to perform five 6-s cycle sprints (interspaced by 24 s of recovery) on a cycle ergometer in front of neutral, pleasant or unpleasant pictures. During each RSE, mean power output (MPO) and electromyographic activity [root mean square (RMS) and median frequency (MF)] of the vastus lateralis and vastus medialis muscles were analyzed. Neuromuscular efficiency (NME) was calculated as the ratio of MPO to RMS. Higher RMS (232.17 ± 1.17 vs. 201.90 ± 0.47 μV) and MF (68.56 ± 1.78 vs. 64.18 ± 2.17 Hz) were obtained in pleasant compared to unpleasant conditions (p < 0.05). This emotional effect persisted from the first to the last sprint. Higher MPO was obtained in pleasant than in unpleasant conditions (690.65 ± 38.23 vs. 656.73 ± 35.95 W, p < 0.05). However, this emotional effect on MPO was observed only for the two first sprints. NME decreased from the third sprint (p < 0.05), which indicated the occurrence of peripheral fatigue after the two first sprints. These results suggested that, compared with unpleasant pictures, pleasant ones increased the neuromuscular performance during RSE. Moreover, the disappearance of the beneficial effect of pleasant emotion on mechanical output from the third sprint appears to be due to peripheral fatigue.

Predicting Blood Lactate Concentration and Oxygen Uptake from sEMG Data during Fatiguing Cycling Exercise

This article presents a study of the relationship between electromyographic (EMG) signals from vastus lateralis, rectus femoris, biceps femoris and semitendinosus muscles, collected during fatiguing cycling exercises, and other physiological measurements, such as blood lactate concentration and oxygen consumption. In contrast to the usual practice of picking one particular characteristic of the signal, e.g., the median or mean frequency, multiple variables were used to obtain a thorough characterization of EMG signals in the spectral domain. Based on these variables, linear and non-linear (random forest) models were built to predict blood lactate concentration and oxygen consumption. The results showed that mean and median frequencies are sub-optimal choices for predicting these physiological quantities in dynamic exercises, as they did not exhibit significant changes over the course of our protocol and only weakly correlated with blood lactate concentration or oxygen uptake. Instead, the root mean square of the original signal and backward difference, as well as parameters describing the tails of the EMG power distribution were the most important variables for these models. Coefficients of determination ranging from R2=0.77 to R2=0.98 (for blood lactate) and from R2=0.81 to R2=0.97 (for oxygen uptake) were obtained when using random forest regressors.