Changes in muscle activity and kinematics of highly trained cyclists during fatigue

Anserine, Balenine, and Ergothioneine: Impact of Histidine-Containing Compounds on Exercise Performance-A Narrative Review

Histidine is an amino acid which plays a critical role in protein synthesis, muscle buffering during anaerobic exercise, and antioxidation. It also acts as a precursor to carnosine, a dipeptide that enhances physical performance by being present in fast-contracting muscle fibers and contributing to buffering capacity. Recent studies have examined other histidine-containing compounds, such as anserine, balenine, and ergothioneine, to assess their potential benefits for physical activity. This narrative review focuses on the literature about the effects of dietary supplementation with these histidine-containing compounds on exercise capacity in animals and humans. The findings indicate that anserine may improve physical performance and reduce fatigue, particularly in quick, repetitive activities. Although balenine has been less extensively studied, it has shown promise in enhancing muscle regeneration and antioxidative defense in animal models. Ergothioneine, a sulfur-containing histidine derivative, displayed antioxidant and anti-inflammatory properties in both animal and human studies, suggesting its potential role in reducing exercise-induced oxidative stress and aiding recovery. The diversity of the presented studies and their limitations do not provide an opportunity to confirm the ergogenic properties of the histidine-containing compounds studied. Nevertheless, supplementation with anserine and ergothioneine shows promise for enhancing physical performance and recovery, though further research is required to better understand their mechanisms and optimize their use in sports and exercise.

Effectiveness of Using a Digital Wearable Plantar Pressure Device to Detect Muscle Fatigue: Within-Subject, Repeated Measures Experimental Design

Background

Muscle fatigue, characterized by reduced force generation during repetitive contractions, impacts older adults doing daily activities and athletes during sports activities. While various sensors detect muscle fatigue via muscle activity, biochemical markers, and kinematic parameters, a real-time wearable solution with high usability remains limited. Plantar pressure monitoring detects muscle fatigue through foot loading changes, seamlessly integrating into footwear to improve the usability and compliance for home-based monitoring.

Objective

This study aimed to investigate the effects of muscle fatigue on plantar pressure measurements using a self-developed wearable plantar pressure system.

Methods

Twelve healthy participants completed a 5-minute calf muscle fatigue protocol. The plantar pressures and surface electromyography (sEMG) activity of the gastrocnemius muscles were recorded before and after exercise. The plantar pressures at 6 regions and the median frequency (MDF) of sEMG were analyzed to quantify fatigue.

Results

The self-developed foot pressure system showed a significant decrease in plantar pressure peak values at the heel of the left (P=.003) and right feet (P=.001) and at the lateral toe of the left (P=.001) and right feet (P=.026). A significant increase was observed at the metatarsal head of both the left foot (P=.001) and the right foot (P=.017). The MDF of sEMG signals significantly decreased in the left (P=.001) and right gastrocnemius (P<.001).

Conclusions

Plantar pressure changes and sEMG signals effectively detect gastrocnemius muscle fatigue using the proposed wearable system, supporting the development of a wearable solution for detecting muscle fatigue suitable for home-use.

Influence of compression garments on fatigue behaviour during running based on nonlinear dynamical analysis

The purpose of this study was to assess quantitatively the effects of compression garments (CGs) on fatigue behaviour during sport activities such as running, which are the subject of a series of qualitative and physiological studies. A quantitative biomechanical analysis of the effects of CGs could assist coaches and athletes to adopt these types of performance enhancement garments. In this research, kinematic changes are measured using 2D phase portraits to study the influence of CGs on fatigue behaviour. Fifteen healthy male intermediate athletes participated in this study and the kinematic data of hip repetitive movements with and without CG were measured during running tasks. These data are used to reconstruct the state space and the local flow variation method is adopted to quantify the trajectory drifts caused by fatigue in the state space. The effects of CGs on the complexity of kinematic changes are also evaluated using permutation entropy. The results indicate that fluctuations in the kinematics are reduced when compression garments are used. It is also shown that adoption of CGs results in a reduction of the rate of fatigue development and decreased complexities in the movement kinematics.

Bicycle Set-Up Dimensions and Cycling Kinematics: A Consensus Statement Using Delphi Methodology

Bicycle set-up dimensions and cycling kinematic data are important components of bicycle fitting and cyclist testing protocols. However, there are no guidelines on how bicycles should be measured and how kinematic data should be collected to increase the reliability of outcomes. This article proposes a consensus regarding bicycle set-up dimensions and recommendations for collecting cycling-related kinematic data. Four core members recruited panellists, prepared the document to review in each round for panellists, analysed the scores and comments of the expert panellists, reported the decisions and communicated with panellists. Fourteen experts with experience in research involving cycling kinematics and/or bicycle fitting agreed to participate as panellists. An initial list of 17 statements was proposed, rated using a five-point Likert scale and commented on by panellists in three rounds of anonymous surveys following a Delphi procedure. The consensus was agreed upon when more than 80% of the panellists scored the statement with values of 4 and 5 (moderately and strongly agree) with an interquartile range of less than or equal to 1. A consensus was achieved for eight statements addressing bicycle set-up dimensions (e.g. saddle height, saddle setback, etc.) and nine statements for cycling kinematic assessment (e.g. kinematic method, two-dimensional methodology, etc.). This consensus statement provides a list of recommendations about how bicycle set-up dimensions should be measured and the best practices for collecting cycling kinematic data. These recommendations should improve the transparency, reproducibility, standardisation and interpretation of bicycle measurements and cycling kinematic data for researchers, bicycle fitters and cycling related practitioners.

Alternative Models for Pelvic Marker Occlusion in Cycling

Bike fitting aims to optimize riders' positions to improve their performance and reduce the risk of injury. To calculate joint angles, the location of the joint centers of the lower limbs needs to be identified. However, one of the greatest difficulties is the location of the hip joint center due to the frequent occlusion of the anterior superior iliac spine markers. Therefore, the objective of this study was to validate a biomechanical model adapted to cycling (modified pelvic model, MPM), based on the traditional pelvic model (TPM) with an additional lateral technical marker placed on the iliac crests. MPM was also compared with a widely used model in cycling, trochanter model (TM). Thirty-one recreational cyclists pedaled on a roller bike while the movement was captured with a 7-camera VICON system. The position of the hip joint center and knee angle were calculated and compared with the TPM continuously (along 10 pedaling cycles) and discreetly at 90° and 180° crank positions. No significant differences were found in the position of the hip joint center or in the knee flexion/extension angle between the TPM and the MPM. However, there are differences between TPM and TM (variations between 4.1° and 6.9° in favor of the TM at 90° and 180°; P < .001). Bland-Altman graphs comparing the models show an average difference or bias close to 0° (limits of agreement [0.2 to -8.5]) between TPM and MPM in both lower limbs and a mean difference of between -4° and -7° (limits of agreement [-0.6 to -13.2]) when comparing TPM and TM. Given the results, the new cycling pelvic model has proven to be valid compared with the TPM when performing bike fitting studies, with the advantage that the occluded markers are avoided. Despite its simplicity, the TM presents measurement errors that may be relevant when making diagnoses, which makes its usefulness questionable.

A dataset for fatigue estimation during shoulder internal and external rotation movements using wearables

Wearable sensors have recently been extensively used in sports science, physical rehabilitation, and industry providing feedback on physical fatigue. Information obtained from wearable sensors can be analyzed by predictive analytics methods, such as machine learning algorithms, to determine fatigue during shoulder joint movements, which have complex biomechanics. The presented dataset aims to provide data collected via wearable sensors during a fatigue protocol involving dynamic shoulder internal rotation (IR) and external rotation (ER) movements. Thirty-four healthy subjects performed shoulder IR and ER movements with different percentages of maximal voluntary isometric contraction (MVIC) force until they reached the maximal exertion. The dataset includes demographic information, anthropometric measurements, MVIC force measurements, and digital data captured via surface electromyography, inertial measurement unit, and photoplethysmography, as well as self-reported assessments using the Borg rating scale of perceived exertion and the Karolinska sleepiness scale. This comprehensive dataset provides valuable insights into physical fatigue assessment, allowing the development of fatigue detection/prediction algorithms and the study of human biomechanical characteristics during shoulder movements within a fatigue protocol.

Agreement between Ventilatory Thresholds and Bilaterally Measured Vastus Lateralis Muscle Oxygen Saturation Breakpoints in Trained Cyclists: Effects of Age and Performance

This study focused on comparing metabolic thresholds derived from local muscle oxygen saturation (SmO2) signals, obtained using near-infrared spectroscopy (NIRS), with global pulmonary ventilation rates measured at the mouth. It was conducted among various Age Groups within a well-trained cyclist population. Additionally, the study examined how cycling performance characteristics impact the discrepancies between ventilatory thresholds (VTs) and SmO2 breakpoints (BPs).

METHODS

Junior (n = 18) and Senior (n = 15) cyclists underwent incremental cycling tests to assess their aerobic performance and to determine aerobic (AeT) and anaerobic (AnT) threshold characteristics through pulmonary gas exchange and changes in linearity of the vastus lateralis (VL) muscle SmO2 signals. We compared the relative power (Pkg) at ventilatory thresholds (VTs) and breakpoints (BPs) for the nondominant (ND), dominant (DO), and bilaterally averaged (Avr) SmO2 during the agreement analysis. Additionally, a 30 s sprint test was performed to estimate anaerobic performance capabilities and to assess the cyclists' phenotype, defined as the ratio of P@VT2 to the highest 5 s sprint power.

RESULTS

The Pkg@BP for Avr SmO2 had higher agreement with VT values than ND and DO. Avr SmO2 Pkg@BP1 was lower (p < 0.05) than Pkg@VT1 (mean bias: 0.12 ± 0.29 W/kg; Limits of Agreement (LOA): -0.45 to 0.68 W/kg; R2 = 0.72) and mainly among Seniors (0.21 ± 0.22 W/kg; LOA: -0.22 to 0.63 W/kg); there was no difference (p > 0.05) between Avr Pkg@BP2 and Pkg@VT2 (0.03 ± 0.22 W/kg; LOA: -0.40 to 0.45 W/kg; R2 = 0.86). The bias between two methods correlated significantly with the phenotype (r = -0.385 and r = -0.515 for AeT and AnT, respectively).

CONCLUSIONS

Two breakpoints can be defined in the NIRS-captured SmO2 signal of VL, but the agreement between the two methods at the individual level was too low for interchangeable usage of those methods in the practical training process. Older cyclists generally exhibited earlier thresholds in muscle oxygenation signals compared to systemic responses, unlike younger cyclists who showed greater variability and no significant differences in this regard in bias values between the two threshold evaluation methods with no significant difference between methods. More sprinter-type cyclists tended to have systemic VT thresholds earlier than local NIRS-derived thresholds than athletes with relatively higher aerobic abilities.

Data-Driven Approach for Upper Limb Fatigue Estimation Based on Wearable Sensors

Muscle fatigue is defined as a reduced ability to maintain maximal strength during voluntary contraction. It is associated with musculoskeletal disorders that affect workers performing repetitive activities, affecting their performance and well-being. Although electromyography remains the gold standard for measuring muscle fatigue, its limitations in long-term work motivate the use of wearable devices. This article proposes a computational model for estimating muscle fatigue using wearable and non-invasive devices, such as Optical Fiber Sensors (OFSs) and Inertial Measurement Units (IMUs) along the subjective Borg scale. Electromyography (EMG) sensors are used to observe their importance in estimating muscle fatigue and comparing performance in different sensor combinations. This study involves 30 subjects performing a repetitive lifting activity with their dominant arm until reaching muscle fatigue. Muscle activity, elbow angles, and angular and linear velocities, among others, are measured to extract multiple features. Different machine learning algorithms obtain a model that estimates three fatigue states (low, moderate and high). Results showed that between the machine learning classifiers, the LightGBM presented an accuracy of 96.2% in the classification task using all of the sensors with 33 features and 95.4% using only OFS and IMU sensors with 13 features. This demonstrates that elbow angles, wrist velocities, acceleration variations, and compensatory neck movements are essential for estimating muscle fatigue. In conclusion, the resulting model can be used to estimate fatigue during heavy lifting in work environments, having the potential to monitor and prevent muscle fatigue during long working shifts.

Bioelectrical, Anthropometric, and Hematological Analysis to Assess Body Fluids and Muscle Changes in Elite Cyclists during the Giro d’Italia

This study aimed to characterize and monitor the body fluid and muscle changes during the Giro d’Italia in nine elite cyclists via bioelectrical (whole-body and muscle-localized) anthropometric and hematological analysis. There were three checkpoint assessments: at the beginning, middle, and end of the race. The Wilcoxon signed-rank test was used to compare the data at baseline and follow up. The Spearman correlation was used to explore relationships between variables. Hotelling’s T2 test was used to determine bioelectrical differences in the complex vector. Bodyweight did not change during the competition, despite bioelectrical and hematological data indicating that at the first half of the race, there was a fluid gain, and in the second half a fluid loss occurred, reaching baseline values. These changes were especially prevalent in the extracellular water compartment. Significant correlations between whole-body bioelectrical vector changes and red blood cell parameter changes were reported. The muscle group most sensitive to changes were the calves. Quadriceps, hamstrings, and calves reported a PhA decrease trend during the first half of the race, and an increase during the second half. Bioelectrical impedance vector analysis appears to be sensitive enough to detect hydration and cellular integrity adaptions induced by competitions as demanding as the Giro d’Italia.

The Soft Prefabricated Orthopedic Insole Decreases Plantar Pressure during Uphill Walking with Heavy Load Carriage

This study aimed to investigate the effect of varying the hardness of prefabricated orthopedic insoles on plantar pressure and muscle fatigue during uphill walking with a heavy backpack. Fifteen healthy male recreational athletes (age: 20.4 ± 1.0 years, height: 176.9 ± 5.7 cm, weight: 76.5 ± 9.0 kg) wore prefabricated orthopedic insoles with foot arch support; a heel cup with medium (MI), hard (HI), and soft (SI) relative hardnesses; and flat insoles (FI). They performed treadmill walking on uphill gradients with 25 kg backpacks. The plantar pressure and surface electromyographic activity were recorded separately, in 30 s and 6 min uphill treadmill walking trials, respectively. The HI, MI, and SI significantly decreased peak plantar pressure in the lateral heel compared to FI. The MI and SI significantly decreased the peak plantar pressure in the fifth metatarsal compared to FI. The MI significantly reduced the pressure–time integral in the lateral heel compared to FI. The HI significantly increased the peak plantar pressure and pressure–time integral in the toes compared to other insoles, and decreased the contact area in the metatarsal compared to SI. In conclusion, a prefabricated orthopedic insole made of soft material at the fore- and rearfoot, with midfoot arch support and a heel cup, may augment the advantages of plantar pressure distribution during uphill weighted walking.

A New Approach to Noninvasive-Prolonged Fatigue Identification Based on Surface EMG Time-Frequency and Wavelet Features

In sports, fatigue management is vital as adequate rest builds strength and enhances performance, whereas inadequate rest exposes the body to prolonged fatigue (PF) or also known as overtraining. This paper presents PF identification and classification based on surface electromyography (EMG) signals. An experiment was performed on twenty participants to investigate the behaviour of surface EMG during the inception of PF. PF symptoms were induced in accord with a five-day Bruce Protocol treadmill test on four lower extremity muscles: the biceps femoris (BF), rectus femoris (RF), vastus medialis (VM), and vastus lateralis (VL). The results demonstrate that the experiment successfully induces soreness, unexplained lethargy, and performance decrement and also indicate that the progression of PF can be observed based on changes in frequency features (ΔF _med and ΔF _mean) and time features (ΔRMS and ΔMAV) of surface EMG. This study also demonstrates the ability of wavelet index features in PF identification. Using a naïve Bayes (NB) classifier exhibits the highest accuracy based on time and frequency features with 98% in distinguishing PF on RF, 94% on BF, 9% on VL, and 97% on VM. Thus, this study has positively indicated that surface EMG can be used in identifying the inception of PF. The implication of the findings is significant in sports to prevent a greater risk of PF.

Effectiveness of a 3D bikefitting method in riding pain, fatigue, and comfort: a randomized controlled clinical trial

To investigate the effects of bike fitting compared to qualitative-based riding posture recommendations on comfort, fatigue, and pain in amateur cyclists. This was a randomised controlled parallel trial of 162 amateur cyclists divided into two groups: bike fitting group (BFG) - participants received a bike fitting session based on 3D kinematic assessments; and a control group (QG) - participants who received a handout containing qualitative-based cycling posture recommendations. Primary outcomes were perceived comfort (FEEL Scale), perceived fatigue (OMNI Scale), and perceived pain (numeric rating pain scale, NRPS). Outcomes were assessed at baseline, when the interventions were delivered, and after 15 days. Intention-to-treat analyses were conducted using student t-tests between pre and post intervention on both groups. All dependent variables from BFG displayed significant statistical difference between both groups post-intervention (p < 0.05). FEEL Scale and OMNI Scale results showed the highest changes of all variables under analysis (mean differences of 3.12 and 3.95 points, respectively); while the body parts with more reduction in riding pain were Groin and Back (mean differences of 1.68 and 1.35, respectively). In conclusion, 3D kinematic bikefit demonstrated superior improvements over riding pain, comfort and fatigue compared to qualitative riding posture recommendations.

Validity of Calculating Continuous Relative Phase during Cycling from Measures Taken with Skin-Mounted Electro-Goniometers

The aim of this study was to assess the validity of electro-goniometers as a tool for recording continuous relative phase data at two joint couplings during cycling tasks at a range of cadences. Seven participants (4 male, 3 female, age: 29 ± 7 years, height: 1.76 ± 0.10 m, mass: 71.97 ± 11.57 kg) performed exercise bouts of 30 s at four prescribed cadences (60, 80, 100, 120 rev·min^-1) on a stationary ergometer (Wattbike, Nottingham, UK). Measures were synchronously recorded by bi-axial electro-goniometers (Biometrics, UK) and a 12-camera motion-capture system (Qualisys, Gothenburg, Sweden), with both systems sampling at 500 Hz. Sagittal plane joint angle and joint angular velocity were recorded at the hip, knee and ankle and analysed for ten complete pedal revolutions per participant per condition. Data were interpolated to 100 time points and used to calculate mean continuous relative phase (CRP) per pedal revolution at two intra-limb couplings: (i) knee flexion/extension-ankle plantarflexion/dorsiflexion (KA) and (ii) hip flexion/extension-knee flexion/extension (HK). At the KA coupling, significant differences in mean CRP were found between measurement systems at 120 rev·min^-1 (p = 0.006). At the HK coupling, significant differences in mean CRP were found between measurement systems at 80 rev·min^-1 (p = 0.043) and 100 rev·min^-1 (p = 0.028). ICC values for most comparisons were below 0.5, suggesting poor levels of agreement between systems. Significant differences in mean CRP per pedal revolution and poor levels of agreement between systems suggests that electro-goniometers are not a suitable alternative to motion-capture systems when attempting to record CRP during cycling.

Acute Ingestion of a Commercially Available Pre-workout Supplement Improves Anaerobic Power Output and Reduces Muscular Fatigue

The effect of a pre-workout supplement on anaerobic power output and muscular fatigue was examined. 18 participants took part in this double-blinded crossover study, reporting for testing on 3 occasions. Participants completed a 6×6 second repeated sprint test, with 20s recovery between sprints. Anaerobic power output was recorded as the highest power achieved during sprint test. Muscular fatigue was reported as a fatigue index across the six sprints ((maximum power - minimum power) ÷ total sprint time). During a baseline visit, participants consumed 250ml of water 30 minutes prior to testing, whilst in subsequent visits a taste-matched placebo (250ml water mixed with sugar-free juice) or a pre-workout supplement (250ml water mixed with one serving of 'THE PRE' myprotein.com). Anaerobic power output increased following pre-workout ingestion (pre-workout supplement, 885.8 ± 216.9W; Placebo, 853.6 ± 206.5W; Baseline, 839.3 ± 192.6W). Baseline vs pre-workout supplement (p = 0.01, g = 0.30); Placebo vs pre-workout supplement (p = 0.01, g = 0.20); Baseline vs Placebo (p = 0.59 g = 0.09). Muscular fatigue was reduced following pre-workout ingestion (Baseline, 4.92 ± 1.83W.s; Placebo, 4.39 ± 1.93W.s; pre-workout supplement, 3.31 ± 1.34W.s). Baseline vs pre-workout supplement (p = < 0.01 g = 0.98); Placebo vs pre-workout supplement (p = 0.01, g = 0.63); Baseline vs Placebo (p = 0.20, g = 0.28). Acute ingestion of a pre-workout supplement significantly improves anaerobic power output and attenuates muscular fatigue during repeated sprint cycling.

Impact of Centre-of-Mass Acceleration on Perceived Exertion, the Metabolic Equivalent and Heart Rate Reserve in Triathlete Spin Cycling: A Pilot Study

Indoor spin cycling has gained popularity as a training modality for triathletes. Part of its appeal is that it can form a component of a structured periodised training program and provide an alternative to outdoor cycling. Indices of physiological components (i.e., the metabolic equivalent, caloric cost, perceived exertion) and changes in the body position can be inferred by wearable technology such as an accelerometer. This pilot study aimed to investigate the relationship between the rating of perceived exertion, heart rate reserve, and the metabolic equivalent between the whole body centre of mass acceleration using a sacrum mounted triaxial accelerometer during 20 minutes of 6 varied power conditions of indoor spin cycling. Compared with other conditions, cycling at a steady state (>152-205 W) resulted in extremely large effects (> 0.9) in mediolateral acceleration and the rating of perceived exertion (p < 0.0001). The relationship between the body position (aerodynamic to drops) induced significant changes in anteroposterior acceleration magnitude (p < 0.0001), although moving from drops to the aerodynamic position was not significant despite a large increase in heart rate reserve and extremely large effects of perceived exertion. The rating of perceived exertion scale and the metabolic equivalent comparative to the whole body centre of mass acceleration magnitude and power displayed a strong correlation (r = 0.865). An individually determined whole body centre of mass accelerations combined with perceived exertion, the metabolic equivalent and heart rate reserve could potentially contribute to improved indoor triathlete spin cycling performance.

Implications of Optimal Feedback Control Theory for Sport Coaching and Motor Learning: A Systematic Review

Best practice in skill acquisition has been informed by motor control theories. The main aim of this study is to screen existing literature on a relatively novel theory, Optimal Feedback Control Theory (OFCT), and to assess how OFCT concepts can be applied in sports and motor learning research. Based on 51 included studies with on average a high methodological quality, we found that different types of training seem to appeal to different control processes within OFCT. The minimum intervention principle (founded in OFCT) was used in many of the reviewed studies, and further investigation might lead to further improvements in sport skill acquisition. However, considering the homogenous nature of the tasks included in the reviewed studies, these ideas and their generalizability should be tested in future studies.

Acute Effects of Aerobic Exercise on Muscle Strength and Power in Trained Male Individuals: A Systematic Review with Meta-analysis

BACKGROUND

Concurrent training can be an effective and time-efficient method to improve both muscle strength and aerobic capacity. A major challenge with concurrent training is how to adequately combine and sequence strength exercise and aerobic exercise to avoid interference effects. This is particularly relevant for athletes.

OBJECTIVE

We aimed to examine the acute effects of aerobic exercise on subsequent measures of muscle strength and power in trained male individuals.

DESIGN

We performed a systematic review with meta-analysis.

DATA SOURCES

Systematic literature searches in the electronic databases PubMed, Web of Science, and Google Scholar were conducted up to July 2021.

ELIGIBILITY CRITERIA FOR SELECTING STUDIES

Studies were included that applied a within-group repeated-measures design and examined the acute effects of aerobic exercise (i.e., running, cycling exercise) on subsequent measures of lower limb muscle strength (e.g., maximal isometric force of the knee extensors) and/or proxies of lower limb muscle power (e.g., countermovement jump height) in trained individuals.

RESULTS

Fifteen studies met the inclusion criteria. Aerobic exercise resulted in moderate declines in muscle strength (standardized mean difference [SMD] = 0.79; p = 0.003). Low-intensity aerobic exercise did not moderate effects on muscle strength (SMD = 0.65; p = 0.157) while moderate-to-high intensity aerobic exercise resulted in moderate declines in muscle strength (SMD = 0.65; p = 0.020). However, the difference between subgroups was not statistically significant (p = 0.979). Regarding aerobic exercise duration, large declines in muscle strength were found after > 30 min (SMD = 1.02; p = 0.049) while ≤ 30 min of aerobic exercise induced moderate declines in muscle strength (SMD = 0.59; p = 0.013). The subgroup difference was not statistically significant (p = 0.204). Cycling exercise resulted in significantly larger decrements in muscle strength (SMD = 0.79; p = 0.002) compared with running (SMD = 0.28; p = 0.035). The difference between subgroups was statistically significant (p < 0.0001). For muscle power, aerobic exercise did not result in any statistically significant changes (SMD = 0.04; p = 0.846).

CONCLUSIONS

Aerobic exercise induced moderate declines in measures of muscle strength with no statistically significant effects on proxies of muscle power in trained male individuals. It appears that higher compared with lower intensity as well as longer compared with shorter aerobic exercise duration exacerbate acute declines in muscle strength. Our results provide evidence for acute interference effects when aerobic exercies is performed before strength exercises. These findings may help practitioners to better prescribe single training sessions, particularly if environmental and/or infrastructural reasons (e.g., availability of training facilities) do not allow the application of strength training before aerobic exercise.

A Dynamic Approach to Cycling Biomechanics

Cycling biomechanics is a complex analysis of the cyclist and the bicycle. It is important to assess the cyclist dynamically because kinematics and muscle patterns are influenced by their type of riding and fatigue and intensity. Intrinsic factors such as anthropometrics and flexibility should guide the initial bicycle configuration. Static kinematics are a valid and reliable tool in the process of bike fitting, providing an initial fast and cost-effective method of assessing the cyclist. Dynamic assessment methods should then be used to fine tune the bicycle configuration according to the specific needs and workloads of the cyclist.

Prevalence, Characteristics, Association Factors of and Management Strategies for Low Back Pain Among Italian Amateur Cyclists: an Observational Cross-Sectional Study

Background

Low back pain (LBP) is a burdensome problem affecting amateur cyclists. This cross-sectional study analysed Italian amateur cycling cohort’s demographic and sport-specific characteristics, the prevalence and characteristics of LBP among this population, its possible association factors, the management strategies adopted to deal with LBP and the sample’s beliefs among possible LBP triggers. A web-based cross-sectional survey was created. The questionnaire included 56 questions divided into six sections, querying the sample’s demographic, clinical, and cycling characteristics. Binomial logistic regression with a Wald backward method was performed to ascertain the effects of some covariates (“Sex”, “Age”, “Body Mass Index”, “Sleep hours”, “Work type”, “Cycling year”, “Number of training sessions per week”, “Stretching sessions”, “Being supervised by a coach or following a scheduled training”, “Other sports practised regularly”, “Number of cycling competitions per year”, “Past biomechanic visits”, “Specific pedal training”, “LBP before cycling”) on the likelihood of developing LBP in the last 12 months.

Results

A total of 1274 amateur cyclists answered the survey. The prevalence of LBP appeared to be 55.1%, 26.5% and 10.8% in life, in the last 12 months and the last 4 weeks, respectively. The final model of the logistic regression included the covariates “Sex”, “Work type”, “Cycling year”, “Being supervised by a coach or following a scheduled training”, “Other sports practised regularly”, “Specific pedal training”, “LBP before cycling”, among which “Cycling year” (variable “Between 2 and 5 years” vs. “Less than 2 years”, OR 0.48, 95% CI [0.26–0.89]), “Being supervised by a coach or following a scheduled training” (OR 0.53, 95% CI [0.37–0.74]), “Specific pedal training” (OR 0.69, 95% CI [0.51–0.94]), and “LBP before cycling” (OR 4.2, 95% CI [3.21–5.40]) were found to be significant.

Conclusions

The prevalence of LBP among Italian amateur cyclists seems to be less frequent compared to the general population. Moreover, undergoing previous specific pedal training and being supervised by a coach or following scheduled training drew a negative association with LBP development. This evidence highlights the importance of being overseen by specific sport figures that could offer a tailored evidence-based training to reach good physical level and to practise sports safely.

Supplementary Information

The online version contains supplementary material available at 10.1186/s40798-021-00370-2.

Changes in the Trunk and Lower Extremity Kinematics Due to Fatigue Can Predispose to Chronic Injuries in Cycling

Kinematic analysis of the cycling position is a determining factor in injury prevention and optimal performance. Fatigue caused by high volume training can alter the kinematics of the lower body and spinal structures, thus increasing the risk of chronic injury. However, very few studies have established relationships between fatigue and postural change, being these in 2D analysis or incremental intensity protocols. Therefore, this study aimed to perform a 3D kinematic analysis of pedaling technique in a stable power fatigue protocol 23 amateur cyclists (28.3 ± 8.4 years) participated in this study. For this purpose, 3D kinematics in hip, knee, ankle, and lumbar joints, and thorax and pelvis were collected at three separate times during the protocol. Kinematic differences at the beginning, middle, and end of the protocol were analyzed for all joints using one-dimensional statistical parametric mapping. Significant differences (p < 0.05) were found in all the joints studied, but not all of them occur in the same planes or the same phase of the cycle. Some of the changes produced, such as greater lumbar and thoracic flexion, greater thoracic and pelvic tilt, or greater hip adduction, could lead to chronic knee and lumbar injuries. Therefore, bike fitting protocols should be carried out in fatigue situations to detect risk factor situations.

Quantification of the effect of compression garments on fatigue behavior in cycling

Effectiveness of compression garments to enhance athletic performance is the subject of numerous qualitative studies. This study aims at quantification of the effect of compression garments using nonlinear dynamics approach. Kinematic data of fifteen healthy male athletes was obtained and the state space was reconstructed. The trajectory drifts caused by fatigue in the state space were quantified using local flow variation technique. The study illustrates that compression garments (CGs) decrease rate of fatigue development and the body exhibits a more restricted complexity (more predictable and smaller fluctuations) when CGs are worn.

Impact of Power Output on Muscle Activation and 3D Kinematics During an Incremental Test to Exhaustion in Professional Cyclists

This study aimed to quantify the influence of an increase in power output (PO) on joint kinematics and electromyographic (EMG) activity during an incremental test to exhaustion for a population of professional cyclists. The hip flexion/extension and internal/external rotation as well as knee abduction/adduction ranges of motion were significantly decreased at 100% of the maximal aerobic power (MAP). EMG analysis revealed a significant increase in the root mean square (RMS) for all muscles from 70% of the MAP. Gastrocnemius muscles [lateralis gastrocnemius (GasL) and medialis gastrocnemius (GasM)] were the less affected by the increase of PO. Cross-correlation method showed a significant increase in the lag angle values for VM in the last stage compared to the first stage, meaning that the onset of the activation started earlier during the pedaling cycle. Statistical Parametric Mapping (SPM) demonstrated that from 70% MAP, biceps femoris (BF), tibialis anterior (TA), gluteus maximus (GM), and rectus femoris (RF) yielded larger ranges of the crank cycle on which the level of recruitment was significantly increased. This study revealed specific muscular and kinematic coordination for professional cyclists in response to PO increase.

Anthropometrics, flexibility and training history as determinants for bicycle configuration

Intrinsic factors such as leg length, arm length, flexibility and training history are factors that may be relevant to the optimisation of the individual bicycle configuration process. Bike fitting methods do not always take all these variables into account, and as yet there have been limited studies examining how these variables can affect the cyclist's position on the bicycle. The main aims of this study were to establish how individual anthropometrics, training history and flexibility may influence cyclists' freely chosen bicycle configuration, and to determine the full-body static flexion angles chosen by cyclists on the bicycle.

Fifty well-trained male cyclists were recruited for the study. A multivariate linear regression analysis was performed to predict the four main configurations of a bicycle (saddle height, saddle setback, handlebar reach and handlebar drop) based on individual anthropometrics, flexibility and training history. Average joint kinematic ranges for the knee (36°±7°) and elbow (19°±8°) joint supported previous recommendations. Hip (77°±5°) and shoulder (112°±7°) joint angles should be determined as true clinical joints.

Trochanteric leg length (p < 0.01), Knee Extension Angle test (p < 0.01) and mSchober test (p = 0.04) were significant predictors for determining saddle height. Hamstring flexibility can be used to predict handlebar drop (p = 0.01).

A cyclist who wishes to adopt a more aerodynamic position with an increased handlebar drop should aim to improve their hamstring flexibility.

Influence of muscle fatigue on the pedaling kinetic and kinematics in different cycling protocols: a scoping review

ABSTRACT The aim of this study was to review the literature on the effects of muscle fatigue generated by different cycling protocols, on the kinetics and kinematics of the crank cycle. Twenty-two studies were included in the review. The establishment of the fatigue processes caused an increase in the resulting and effective forces (all tests), together with the pedaling efficiency (incremental and constant tests). In addition, fatigue caused joint changes in the lower limbs (increased range of motion in the ankle and reduced contribution to total torque) in different cycling tests. Therefore, these pedaling strategies may be related to the maintenance of muscle work to postpone the cyclists’ exhaustion.

Vibrotactile feedback for correcting aerodynamic position of a cyclist

Guidance to maintain an optimal aerodynamic position is currently unavailable during cycling. This study used real-time vibrotactile feedback to guide cyclists to a reference position with minimal projected frontal area as an indicator of aerodynamic drag, by optimizing torso, shoulder, head and elbow position without compromising comfort when sitting still on the bike. The difference in recapturing the aerodynamic reference position during cycling after predefined deviations from the reference position at different intensities was analysed for 14 participants between three interventions, consisting of 1) vibrotactile feedback with a margin of error of 1.5% above the calibrated reference projected frontal area, 2) vibrotactile feedback with a margin of 3%, and 3) no feedback. The reference position is significantly more accurately achieved using vibrotactile feedback compared to no feedback (p < 0.001), but there is no significant difference between the 1.5% and 3% margin (p = 0.11) in terms of relative projected frontal area during cycling compared to the calibrated reference position (1.5% margin -0.46 ± 1.76%, 3% margin -0.01 ± 2.01%, no feedback 2.59 ± 3.29%). The results demonstrate that vibrotactile feedback can have an added value in assisting and correcting cyclists in recapturing their aerodynamic reference position.

Cycling: joint kinematics and muscle activity during differing intensities

Full body kinematics and electromyographic (EMG) patterns may alter based on the workloads that are encountered during cycling. Understanding the effect of differing intensities on the cyclist can guide clinicians and bike fitters in improving specific muscle strength and cycling posture to optimise training and racing. We aimed to assess changes in lower limb EMG magnitudes and full body 3D kinematics of 17 well-trained cyclists at three different exercise intensities: 60%, 80% and 90% of maximum heart rate. Significant results were demonstrated for all the joints except the hip and shoulder. Cyclists' ankle dorsiflexion and knee extension increased between 6% and 9% with higher intensities. The elbow adopted a significantly more flexed position, increasing flexion by 39% from 60% to 90% intensity, whilst the lumbar and thoracic flexion increased by 7% at the higher intensity. There were significant increases in EMG signal amplitude at higher intensities for all muscle groups measured. These results will guide clinicians in strengthening specific muscles at specific ranges of the cycling pedal revolution. Guidelines for optimal bicycle configuration should take into account the full body position of the cyclist as well as the training and racing intensity when assessing kinematics.

An EMG Patch for the Real-Time Monitoring of Muscle-Fatigue Conditions During Exercise

In recent years, wearable monitoring devices have been very popular in the health care field and are being used to avoid sport injuries during exercise. They are usually worn on the wrist, the same as sport watches, or on the chest, like an electrocardiogram patch. Common functions of these wearable devices are that they use real time to display the state of health of the body, and they are all small sized. The electromyogram (EMG) signal is usually used to show muscle activity. Thus, the EMG signal could be used to determine the muscle-fatigue conditions. In this study, the goal is to develop an EMG patch which could be worn on the lower leg, the gastrocnemius muscle, to detect real-time muscle fatigue while exercising. A micro controller unit (MCU) in the EMG patch is part of an ARM Cortex-M4 processor, which is used to measure the median frequency (MF) of an EMG signal in real time. When the muscle starts showing tiredness, the median frequency will shift to a low frequency. In order to delete the noise of the isotonic EMG signal, the EMG patch has to run the empirical mode decomposition algorithm. A two-electrode circuit was designed to measure the EMG signal. The maximum power consumption of the EMG patch was about 39.5 mAh. In order to verify that the real-time MF values measured by the EMG patch were close to the off-line MF values measured by the computer system, we used the root-mean-square value to estimate the difference in the real-time MF values and the off-line MF values. There were 20 participants that rode an exercise bicycle at different speeds. Their EMG signals were recorded with an EMG patch and a physiological measurement system at the same time. Every participant rode the exercise bicycle twice. The averaged root-mean-square values were 2.86 ± 0.86 Hz and 2.56 ± 0.47 Hz for the first and second time, respectively. Moreover, we also developed an application program implemented on a smart phone to display the participants' muscle-fatigue conditions and information while exercising. Therefore, the EMG patch designed in this study could monitor the muscle-fatigue conditions to avoid sport injuries while exercising.

Comparing functional dynamic normalization methods to maximal voluntary isometric contractions for lower limb EMG from walking, cycling and running

There is no consensus on the most appropriate method for normalizing an individual's electromyography (EMG) signals from walking, cycling and running in the same data collection. The aim of this study was to compare how the magnitude and repeatability of normalization values differ from three normalization methods and to compare their scaling effect in three moderate intensity activities. Three rounds of maximal voluntary isometric contractions (MVICs), sprint cycling and sprint running were performed to obtain normalization values for each method. EMG from five moderate intensity trials of walking, cycling and running were performed and normalized using each normalization value. Normalization values, coefficients of variation, and peak normalized EMG from the three moderate intensity activities were compared across normalization methods. Sprint running resulted in greater normalization values for 6/9 muscles. MVICs produced the lowest variance in 6/9 muscles. Comparing peak normalized signals of interest across normalization methods, there were significant differences in 6/9, 7/9 and 8/9 muscles for walking, cycling and running, respectively. When investigating a combination of walking, cycling and/or running EMG data, sprint running could be used for normalization, due to its simplicity and its ability to produce a larger normalization value, despite lower repeatability.

Oxygen uptake and muscle activity limitations during stepping on a stair machine at three different climbing speeds

This laboratory study examined human stair ascending capacity and constraining factors including legs' local muscle fatigue (LMF) and cardiorespiratory capacity. Twenty-five healthy volunteers, with mean age 35.3 years, maximal oxygen uptake (VO_2max) of 46.7 mL·min^-1·kg^-1 and maximal heart rate (HR) of 190 bpm, ascended on a stair machine at 60 and 75% (3 min each) and 90% of VO_2max (5 min or until exhaustion). The VO₂, maximal heart rate (HR_max) and electromyography (EMG) of the leg muscles were measured. The average VO_2highest reached 43.9 mL·min^-1·kg^-1, and HR_highest peaked at 185 bpm at 90% of VO_2max step rate (SR). EMG amplitudes significantly increased at all three levels, p < .05, and median frequencies decreased mostly at 90% of VO_2max SR evidencing leg LMF. Muscle activity interpretation squares were developed and effectively used to observe changes over time, confirming LMF. The combined effects of LMF and cardiorespiratory constraints reduced ascending tolerance and constrained the duration to 4.32 min. Practitioner Summary: To expedite ascending evacuation from high-rise buildings and deep underground structures, it is necessary to consider human physical load. This study investigated the limiting physiological factors and muscle activity rate changes (MARC) used in the muscle activity interpretation squares (MAIS) to evaluate leg local muscle fatigue (LMF). LMF and cardiorespiratory capacity significantly constrain human stair ascending capacities at high, constant step rates.

A machine learning approach to detect changes in gait parameters following a fatiguing occupational task

The purpose of this study is to provide a method for classifying non-fatigued vs. fatigued states following manual material handling. A method of template matching pattern recognition for feature extraction ($1 Recognizer) along with the support vector machine model for classification were applied on the kinematics of gait cycles segmented by our stepwise search-based segmentation algorithm. A single inertial measurement unit on the ankle was used, providing a minimally intrusive and inexpensive tool for monitoring. The classifier distinguished between states using distance-based scores from the recogniser and the step duration. The results of fatigue detection showed an accuracy of 90% across data from 20 recruited subjects. This method utilises the minimum amount of data and features from only one low-cost sensor to reliably classify the state of fatigue induced by a realistic manufacturing task using a simple machine learning algorithm that can be extended to real-time fatigue monitoring as a future technology to be employed in the manufacturing facilities. Practitioner Summary: We examined the use of a wearable sensor for the detection of fatigue-related changes in gait based on a simulated manual material handling task. Classification based on foot acceleration and position trajectories resulted in 90% accuracy. This method provides a practical framework for predicting realistic levels of fatigue.

Muscle Performance Investigated With a Novel Smart Compression Garment Based on Pressure Sensor Force Myography and Its Validation Against EMG

Muscle activity and fatigue performance parameters were obtained and compared between both a smart compression garment and the gold-standard, a surface electromyography (EMG) system during high-speed cycling in seven participants. The smart compression garment, based on force myography (FMG), comprised of integrated pressure sensors that were sandwiched between skin and garment, located on five thigh muscles. The muscle activity was assessed by means of crank cycle diagrams (polar plots) that displayed the muscle activity relative to the crank cycle. The fatigue was assessed by means of the median frequency of the power spectrum of the EMG signal; the fractal dimension (FD) of the EMG signal; and the FD of the pressure signal. The smart compression garment returned performance parameters (muscle activity and fatigue) comparable to the surface EMG. The major differences were that the EMG measured the electrical activity, whereas the pressure sensor measured the mechanical activity. As such, there was a phase shift between electrical and mechanical signals, with the electrical signals preceding the mechanical counterparts in most cases. This is specifically pronounced in high-speed cycling. The fatigue trend over the duration of the cycling exercise was clearly reflected in the fatigue parameters (FDs and median frequency) obtained from pressure and EMG signals. The fatigue parameter of the pressure signal (FD) showed a higher time dependency (R² = 0.84) compared to the EMG signal. This reflects that the pressure signal puts more emphasis on the fatigue as a function of time rather than on the origin of fatigue (e.g., peripheral or central fatigue). In light of the high-speed activity results, caution should be exerted when using data obtained from EMG for biomechanical models. In contrast to EMG data, activity data obtained from FMG are considered more appropriate and accurate as an input for biomechanical modeling as they truly reflect the mechanical muscle activity. In summary, the smart compression garment based on FMG is a valid alternative to EMG-garments and provides more accurate results at high-speed activity (avoiding the electro-mechanical delay), as well as clearly measures the progress of muscle fatigue over time.

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.

Spatiotemporal analysis of 3D kinematic asymmetry in professional cycling during an incremental test to exhaustion

This study investigated the influence of an incremental exercise on bilateral asymmetry through the spatio-temporal evolution of 3D joint angular displacement, using the Normalized Symmetry Index ([Formula: see text]) and cross-correlation methods. Twelve professional cyclists performed an incremental test to exhaustion, during which motion capture was used. Results revealed a decrease in range of motion between the first and last stages for twelve of the eighteen joint rotations, with the highest impact observed for right hip flexion/extension (61.8 ± 4.7° to 58.8 ± 4.1°, p < 0.05, ES = 0.68). For both stages, significant bilateral differences greater than 10° were observed for hip and knee flexion/extension (p < 0.05, ES>0.90) and ankle and hip internal/external rotation (p < 0.05, ES>0.25). Cross-correlation displayed the lowest pattern similarities for hip abduction/adduction and the highest similarities for knee flexion/extension, ankle plantarflexion/dorsiflexion and hip internal/external rotation. The cross-correlation method showed that the right leg was mostly ahead of time with respect to the left leg, a trend that was accentuated with power output increase. Instantaneous [Formula: see text] fluctuated up to 18% throughout the pedalling cycle, with different behaviour between the power and recovery phases. This study demonstrated the workload effects on side-to-side joint angular pattern similarity.

Limitations of oxygen uptake and leg muscle activity during ascending evacuation in stairways

Stair ascending performance is critical during evacuation from buildings and underground infrastructures. Healthy subjects performed self-paced ascent in three settings: 13 floor building, 31 floor building, 33 m stationary subway escalator. To investigate leg muscle and cardiorespiratory capacities and how they constrain performance, oxygen uptake (VO₂), heart rate (HR) and ascending speed were measured in all three; electromyography (EMG) in the first two. The VO₂ and HR ranged from 89 to 96% of the maximum capacity reported in the literature. The average highest VO₂ and HR ranged from 39 to 41 mL·kg^-1·min^-1 and 162 to 174 b·min^-1, respectively. The subjects were able to sustain their initial preferred maximum pace for a short duration, while the average step rate was 92-95 steps·min^-1. In average, VO₂ reached relatively stable values at ≈37 mL·kg^-1·min^-1. EMG amplitudes decreased significantly and frequencies were unchanged. Speed reductions indicate that climbing capacity declined in the process of fatigue development. In the two buildings, the reduction of muscle power allowed the subjects to extend their tolerance and complete ascents in the 48 m and 109 m high stairways in 2.9 and 7.8 min, respectively. Muscle activity interpretation squares were developed and proved advantageous to observe fatigue and recovery over time.

Assessment of Three-Dimensional Trunk Kinematics and Muscle Activation during Cycling with Independent Cranks

Independent cranks (IC) are recently introduced bicycle cranks that are decoupled; therefore allowing each leg to pedal independent of the other. Despite this introduction, limited research has been conducted assessing biomechanical changes when cycling with IC. Therefore, the purpose of this study was to evaluate and compare trunk kinematics and surface electromyography (sEMG) during IC and normal crank (NC) cycling during a graded exercise test to volitional fatigue. Ten healthy, physically active men performed two tests (IC and NC) on a cycling ergometer on separate days. 3D motion capture data of the trunk and pelvis and sEMG of the latissimus dorsi, tibialis anterior, gastrocnemius lateral head, rectus femoris, vastus lateralis and the biceps femoris were collected bilaterally. The first 30 seconds (beginning) and the last 30 seconds (end) of each trial were analyzed with respect to external load (beginning vs end), crank type (IC vs NC) side (left vs right), and phase of the pedal cycle (push vs recovery). Mean load at volitional fatigue in NC (351 W) was significantly greater than IC (318 W; p < 0.001). As external load increased, there was a similar increase in spine flexion angle in the sagittal plane for both NC (8.2°) and IC (4.6°). The NC condition demonstrated significantly greater increase in muscle activation from the beginning to the end than the IC condition in the tibialis anterior, rectus femoris and biceps femoris in the push phase, and the rectus femoris and biceps femoris in the recovery phase. As IC demonstrated less increase in activation, they cause less variation in muscular contraction from beginning to end throughout the full pedal range of motion, yet do not alter gross trunk kinematics. Due to altered muscle activation patterns when cycling with IC, they are proposed as a potentially beneficial training tool to increase training diversity.

Estimating Gait Stability: Asymmetrical Loading Effects Measured Using Margin of Stability and Local Dynamic Stability

Changes to intersegmental locomotor control patterns may affect body stability. Our study aimed to (a) characterize upper body dynamic stability in response to the unilateral addition of mass to the lower extremity and (b) evaluate the efficacy of 2 different stability measures commonly used in the literature to detect resulting symmetrical step pattern modifications across the weighted segments (spatial) and between epochs of the gait cycle (temporal). Young adults walked on a treadmill while unloaded or with weights applied unilaterally to their foot, shank, or thigh. Both margin of stability and local dynamic stability (LDS) estimates detected similar trends of distal segment weighting resulting in more unstable upper body movement compared to proximal weighting; however only LDS detected anteroposterior changes in upper body stability over time.

Electromyographic Patterns during Golf Swing: Activation Sequence Profiling and Prediction of Shot Effectiveness

This study analyzes muscle activity, recorded in an eight-channel electromyographic (EMG) signal stream, during the golf swing using a 7-iron club and exploits information extracted from EMG dynamics to predict the success of the resulting shot. Muscles of the arm and shoulder on both the left and right sides, namely flexor carpi radialis, extensor digitorum communis, rhomboideus and trapezius, are considered for 15 golf players (∼5 shots each). The method using Gaussian filtering is outlined for EMG onset time estimation in each channel and activation sequence profiling. Shots of each player revealed a persistent pattern of muscle activation. Profiles were plotted and insights with respect to player effectiveness were provided. Inspection of EMG dynamics revealed a pair of highest peaks in each channel as the hallmark of golf swing, and a custom application of peak detection for automatic extraction of swing segment was introduced. Various EMG features, encompassing 22 feature sets, were constructed. Feature sets were used individually and also in decision-level fusion for the prediction of shot effectiveness. The prediction of the target attribute, such as club head speed or ball carry distance, was investigated using random forest as the learner in detection and regression tasks. Detection evaluates the personal effectiveness of a shot with respect to the player-specific average, whereas regression estimates the value of target attribute, using EMG features as predictors. Fusion after decision optimization provided the best results: the equal error rate in detection was 24.3% for the speed and 31.7% for the distance; the mean absolute percentage error in regression was 3.2% for the speed and 6.4% for the distance. Proposed EMG feature sets were found to be useful, especially when used in combination. Rankings of feature sets indicated statistics for muscle activity in both the left and right body sides, correlation-based analysis of EMG dynamics and features derived from the properties of two highest peaks as important predictors of personal shot effectiveness. Activation sequence profiles helped in analyzing muscle orchestration during golf shot, exposing a specific avalanche pattern, but data from more players are needed for stronger conclusions. Results demonstrate that information arising from an EMG signal stream is useful for predicting golf shot success, in terms of club head speed and ball carry distance, with acceptable accuracy. Surface EMG data, collected with a goal to automatically evaluate golf player's performance, enables wearable computing in the field of ambient intelligence and has potential to enhance exercising of a long carry distance drive.

Wet, volatile, and dry biomarkers of exercise-induced muscle fatigue

Background

The physiological background of exercise-induced muscle fatigue(EIMUF) is only poorly understood. Thus, monitoring of EIMUF by a single or multiple biomarkers(BMs) is under debate.

After a systematic literature review 91 papers were included.

Results

EIMUF is mainly due to depletion of substrates, increased oxidative stress, muscle membrane depolarisation following potassium depletion, muscle hyperthermia, muscle damage, impaired oxygen supply to the muscle, activation of an inflammatory response, or impaired calcium-handling. Dehydration, hyperammonemia, mitochondrial biogenesis, and genetic responses are also discussed. Since EIMUF is dependent on age, sex, degree of fatigue, type, intensity, and duration of exercise, energy supply during exercise, climate, training status (physical fitness), and health status, BMs currently available for monitoring EIMUF have limited reliability. Generally, wet, volatile, and dry BMs are differentiated. Among dry BMs of EIMUF the most promising include power output measures, electrophysiological measures, cardiologic measures, and questionnaires. Among wet BMs of EIMUF those most applicable include markers of ATP-metabolism, of oxidative stress, muscle damage, and inflammation. VO₂-kinetics are used as a volatile BM.

Conclusions

Though the physiology of EIMUF remains to be fully elucidated, some promising BMs have been recently introduced, which together with other BMs, could be useful in monitoring EIMUF. The combination of biomarkers seems to be more efficient than a single biomarker to monitor EIMUF. However, it is essential that efficacy, reliability, and applicability of each BM candidate is validated in appropriate studies.

The Effects of Vibration and Muscle Fatigue on Trunk Sensorimotor Control in Low Back Pain Patients

INTRODUCTION

Changes in sensorimotor function and increased trunk muscle fatigability have been identified in patients with chronic low back pain (cLBP). This study assessed the control of trunk force production in conditions with and without local erector spinae muscle vibration and evaluated the influence of muscle fatigue on trunk sensorimotor control.

METHODS

Twenty non-specific cLBP patients and 20 healthy participants were asked to perform submaximal isometric trunk extension torque with and without local vibration stimulation, before and after a trunk extensor muscle fatigue protocol. Constant error (CE), variable error (VE) as well as absolute error (AE) in peak torque were computed and compared across conditions. Trunk extensor muscle activation during isometric contractions and during the fatigue protocol was measured using surface electromyography (sEMG).

RESULTS

Force reproduction accuracy of the trunk was significantly lower in the patient group (CE = 9.81 ± 2.23 Nm; AE = 18.16 ± 3.97 Nm) than in healthy participants (CE = 4.44 ± 1.68 Nm; AE = 12.23 ± 2.44 Nm). Local erector spinae vibration induced a significant reduction in CE (4.33 ± 2.14 Nm) and AE (13.71 ± 3.45 Nm) mean scores in the patient group. Healthy participants conversely showed a significant increase in CE (8.17 ± 2.10 Nm) and AE (16.29 ± 2.82 Nm) mean scores under vibration conditions. The fatigue protocol induced erector spinae muscle fatigue as illustrated by a significant decrease in sEMG median time-frequency slopes. Following the fatigue protocol, patients with cLBP showed significant decrease in sEMG root mean square activity at L4-5 level and responded in similar manner with and without vibration stimulation in regard to CE mean scores.

CONCLUSIONS

Patients with cLBP have a less accurate force reproduction sense than healthy participants. Local muscle vibration led to significant trunk neuromuscular control improvements in the cLBP patients before and after a muscle fatigue protocol. Muscle vibration stimulation during motor control exercises is likely to influence motor adaptation and could be considered in the treatment of cLBP. Further work is needed to clearly identify at what levels of the sensorimotor system these gains are achievable.

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.

The progression of muscle fatigue during exercise estimation with the aid of high-frequency component parameters derived from ensemble empirical mode decomposition

Muscle fatigue is often monitored via the median frequency derived from the surface electromyography (sEMG) power spectrum during isometric contractions. The power spectrum of sEMG shifting toward lower frequencies can be used to quantify the electromanifestation of muscle fatigue. The dynamic sEMG belongs to a nonstationary signal, which will be affected by the electrode moving, the shift of the muscle, and the change of innervation zone. The goal of this study is to find a more sensitive and stable method in order to sense the progression of muscle fatigue in the local muscle during exercise in healthy people. Five male and five female volunteers participated. Each subject was asked to run on a multifunctional pedaled elliptical trainer for about 30 min, twice a week, and was recorded a total of six times. Three decomposed methods, discrete wavelet transform (DWT), empirical mode decomposition (EMD), and ensemble EMD (EEMD), were used to sense the progression of muscle fatigue. They compared with each other. Although the highest frequency components of sEMG by DWT, EMD, and EEMD have the better performance to sense the progression of muscle fatigue than the raw sEMG, the EEMD has the best performance to reduce nonstationary characteristics and noise of the dynamic sEMG.

The club-level road cyclist: injury, pain, and performance

OBJECTIVE

The aims of this study were to (1) examine riding habits of injured cyclists, (2) identify factors related to seeking medical treatment, (3) investigate performance of recreational road cyclists compared with established norms regarding strength and flexibility measures, and (4) propose cycling-specific injury risk factors.

DESIGN

Observational and prospective study.

SETTING

Cycling store and bicycle distribution company.

PARTICIPANTS

Sixty-three experienced road cyclists.

ASSESSMENT OF RISK FACTORS

Initial data collection included a questionnaire. A 2-week training diary and 8 weekly follow-up injury questionnaires were also collected.

MAIN OUTCOME MEASURES

Training habits and injury history, bike fit, flexibility, and isometric, dynamic, and plyometric strength measures.

RESULTS

Participants were likely to have an injury at baseline, and chronic pain was common. Cyclists trained for an equal quantity of time irrespective of experiencing pain. Injury severity in terms of pain level and participant age were factors in seeking medical care. Our participants performed poorly on our testing protocol compared with available norms. Flexibility, strength, and bike fit measures did not predict injury. Previous injury predicted prospective injury. The knee and lumbar region were most frequently injured.

CONCLUSIONS

Cycling is a sport in which injury risk and prevention need to be further studied. Cyclists are frequently injured but continue to participate in cycling at volumes equal to their healthy peers.

CLINICAL RELEVANCE

This study outlines a clinically reproducible cyclist assessment and discusses behaviors common to the cycling patient.

Impact of polyphenol antioxidants on cycling performance and cardiovascular function

This investigation sought to determine if supplementation with polyphenol antioxidant (PA) improves exercise performance in the heat (31.5 °C, 55% RH) by altering the cardiovascular and thermoregulatory responses to exercise. Twelve endurance trained athletes ingested PA or placebo (PLAC) for 7 days. Consecutive days of exercise testing were performed at the end of the supplementation periods. Cardiovascular and thermoregulatory measures were made during exercise. Performance, as measured by a 10 min time trial (TT) following 50 min of moderate intensity cycling, was not different between treatments (PLAC: 292 ± 33 W and PA: 279 ± 38 W, p = 0.12). Gross efficiency, blood lactate, maximal neuromuscular power, and ratings of perceived exertion were also not different between treatments. Similarly, performance on the second day of testing, as assessed by time to fatigue at maximal oxygen consumption, was not different between treatments (PLAC; 377 ± 117 s vs. PA; 364 ± 128 s, p = 0.61). Cardiovascular and thermoregulatory responses to exercise were not different between treatments on either day of exercise testing. Polyphenol antioxidant supplementation had no impact on exercise performance and did not alter the cardiovascular or thermoregulatory responses to exercise in the heat.

Spatio-temporal analysis reveals active control of both task-relevant and task-irrelevant variables

The Uncontrolled Manifold (UCM) hypothesis and Minimal Intervention principle propose that the observed differential variability across task relevant (i.e., task goals) vs. irrelevant (i.e., in the null space of those goals) variables is evidence of a separation of task variables for efficient neural control, ranked by their respective variabilities (sometimes referred to as hierarchy of control). Support for this comes from spatial domain analyses (i.e., structure of) of kinematic, kinetic, and EMG variability. While proponents admit the possibility of preferential as opposed to strictly uncontrolled variables, such distinctions have only begun to be quantified or considered in the temporal domain when inferring control action. Here we extend the study of task variability during tripod static grasp to the temporal domain by applying diffusion analysis. We show that both task-relevant and task-irrelevant parameters show corrective action at some time scales; and conversely, that task-relevant parameters do not show corrective action at other time scales. That is, the spatial fluctuations of fingertip forces show, as expected, greater ranges of variability in task-irrelevant variables (>98% associated with changes in total grasp force; vs. only <2% in task-relevant changes associated with acceleration of the object). But at some time scales, however, temporal fluctuations of task-irrelevant variables exhibit negative correlations clearly indicative of corrective action (scaling exponents <0.5); and temporal fluctuations of task-relevant variables exhibit neutral and positive correlations clearly indicative of absence of corrective action (scaling exponents ≥0.5). In agreement with recent work in other behavioral contexts, these results propose we revise our understanding of variability vis-á-vis task relevance by considering both spatial and temporal features of all task variables when inferring control action and understanding how the CNS confronts task redundancy. Instead of a dichotomy of presence vs. absence of control, we should speak of a continuum of weaker to stronger—and potentially different—control strategies in specific spatiotemporal domains, indicated here by the magnitude of deviation from the 0.5 scaling exponent. Moreover, these results are counter examples to the UCM hypothesis and the Minimal Intervention principle, and the similar nature of control actions across time scales in both task-relevant and task-irrelevant spaces points to a level of modularity not previously recognized.