Running Research Articles

External Mechanical Work Versus Energy Expenditure During on-Court Tennis Drills in Elite Adolescent Tennis Players

Abstract Purpose Tennis demands exceptional technical skills, speed, strength and endurance. Previous studies have highlighted the high energy expenditure during tennis drills due to constant directional changes. While metabolic monitoring and player tracking have been used to quantify exercise intensity and movements, mechanical efficiency (ME) in tennis remains poorly understood. This study aimed to investigate ME in tennis by combining metabolic and mechanical measurements during on-court drills. Methods Ten elite adolescent tennis players (males n = 5, females n = 5) performed a VO2max test on a treadmill and participated in three standard tennis drills, Spanish cross, lateral and inside out. During the tennis drill, full-body kinematics were captured, and energy expenditure was measured using a portable breath-by-breath gas analysis. ME was calculated for each drill, and individual differences were examined. Results Results revealed significant differences in energy expenditure and mechanical work between drills. ME was not associated with VO2max or running speed. highlighting the need to focus on other factors like strength, footwork technique, and neuromuscular training to enhance ME. Conclusion This study underscores the complexity of ME in tennis, with individual variations and where factors like footwork technique, muscular strength and motor abilities might influence ME.

A TMSBL underwater acoustic channel estimation method based on dictionary learning denoising

The shallow sea underwater acoustic channel exhibits a significant sparse multipath structure. The temporally multiple sparse Bayesian learning (TMSBL) algorithm can effectively estimate this sparse multipath channel. However, the complexity of the algorithm is high, the signal-to-noise ratio (SNR) of shallow-sea underwater acoustic communication is low, and the estimation performance of the TMSBL algorithm is greatly affected by noise. To address this problem, an improved TMSBL underwater acoustic channel estimation method based on a dictionary learning noise reduction algorithm is proposed. Firstly, the K-Singular Value Decomposition (K-SVD) dictionary learning method is used to reduce the noise of the received pilot matrix, reducing the influence of noise on the signal. Then, the Generalized Orthogonal Matching Pursuit (GOMP) channel estimation method is combined to obtain a priori information such as the perceptual matrix and hyperparameter matrix for TMSBL channel estimation; and the noise variance is obtained by using the null subcarrier calculation instead of iteratively updating the noise variance in the TMSBL, to improve the estimation accuracy and reduce the algorithmic complexity. Finally, the TMSBL channel estimation method is used to estimate the underwater acoustic channels of different symbols jointly. The simulation results show that the normalized mean square error of the channel estimation of the improved TMSBL method is reduced by about 92.2% compared with the TMSBL algorithm, obtaining higher estimation accuracy; running time is reduced by about 45.6%, and there is also better performance in terms of the running speed, which provides a reference for underwater acoustic channel estimation.

From lab to field: validity and reliability of inertial measurement unit-derived gait parameters during a standardised run

ABSTRACT The aim was to assess concurrent validity and test–retest reliability of spatiotemporal gait parameters from a thoracic-placed inertial measurement unit (IMU) in lab- (Phase One) and field-based (Phase Two) conditions. Spatiotemporal gait parameters were compared (target speeds 3, 5 and 7.5 m·s−1) between a 100 Hz IMU and an optical measurement system (OptoJump Next, 1000 hz) in 14 trained individuals (Phase One). Additionally, 29 English Premier League football players performed weekly 3 × 60 m runs (5 m·s−1; observations = 1227; Phase Two). Mixed effects modelling assessed the effect of speed on agreement between systems (Phase One) and test–retest reliability (Phase Two). IMU step time showed strong agreement (<0.3%) regardless of individual or running speed. Direction of mean biases up to 40 ms for contact and flight time depended on the running speed and individual. Step time, length and frequency were most reliable (coefficient of variation = 1.3-1.4%) but confounded by running speed. Step time, length and frequency derived from a thoracic-placed IMU can be used confidently. Contact time could be used if bias is corrected for each individual. To optimise test–retest reliability, a minimum running distance of 40 m is needed to ensure 10 constant-speed steps is gathered.

An integrated framework for driving risk evaluation that combines lane-changing detection and an attention-based prediction model

Objective In recent years, the increase in traffic accidents has emerged as a significant social issue that poses a serious threat to public safety. The objective of this study is to predict risky driving scenarios to improve road safety. Methods On the basis of data collected from naturalistic driving real-vehicle experiments, a comprehensive framework for identifying and analyzing risky driving scenarios, which combines an integrated lane-changing detection model and an attention-based long short-term memory (LSTM) prediction model, is proposed. The performance of the 4 machine learning methods on the CULane data set is compared in terms of model running time and running speed as evaluation metrics, and the ultrafast network with the best performance is selected as the method for lane line detection. We compared the performance of LSTM and attention-based LSTM on the basis of the prediction accuracy, recall, precision, and F1 value and selected the better model (attention-based LSTM) for risky scenario prediction. Furthermore, Shapley additive explanation analysis (SHAP) is used to understand and interpret the prediction results of the model. Results In terms of algorithm efficiency, the running time of the ultrafast lane detection network only requires 4.1 ms, and the average detection speed reaches 131 fps. For prediction performance, the accuracy rate of attention-based LSTM reaches 96%, the precision rate is 98%, the recall rate is 96%, and the F1 value is 97%. Conclusions The improved attention-based LSTM model is significantly better than the LSTM model in terms of convergence speed and prediction accuracy and can accurately identify risky scenarios that occur during driving. The importance of factors varies by risky scenario. The characteristics of the yaw rate, speed stability, vehicle speed, acceleration, and lane change significantly influence the driving risk, among which lane change has the greatest impact. This study can provide real-time risky scenario prediction, warnings, and scientific decision guidance for drivers.

Multidimensional Analysis of Physiological Entropy during Self-Paced Marathon Running.

The pacing of a marathon is arguably the most challenging aspect for runners, particularly in avoiding a sudden decline in speed, or what is colloquially termed a "wall", occurring at approximately the 30 km mark. To gain further insight into the potential for optimizing self-paced marathon performance through the coding of comprehensive physiological data, this study investigates the complex physiological responses and pacing strategies during a marathon, with a focus on the application of Shannon entropy and principal component analysis (PCA) to quantify the variability and unpredictability of key cardiorespiratory measures. Nine recreational marathon runners were monitored throughout the marathon race, with continuous measurements of oxygen uptake (V˙O2), carbon dioxide output (V˙CO2), tidal volume (Vt), heart rate, respiratory frequency (Rf), and running speed. The PCA revealed that the entropy variance of V˙O2, V˙CO2, and Vt were captured along the F1 axis, while cadence and heart rate variances were primarily captured along the F2 axis. Notably, when distance and physiological responses were projected simultaneously on the PCA correlation circle, the first 26 km of the race were positioned on the same side of the F1 axis as the metabolic responses, whereas the final kilometers were distributed on the opposite side, indicating a shift in physiological state as fatigue set in. The separation of heart rate and cadence entropy variances from the metabolic parameters suggests that these responses are independent of distance, contrasting with the linear increase in heart rate and decrease in cadence typically observed. Additionally, Agglomerative Hierarchical Clustering further categorized runners' physiological responses, revealing distinct clusters of entropy profiles. The analysis identified two to four classes of responses, representing different phases of the marathon for individual runners, with some clusters clearly distinguishing the beginning, middle, and end of the race. This variability emphasizes the personalized nature of physiological responses and pacing strategies, reinforcing the need for individualized approaches. These findings offer practical applications for optimizing pacing strategies, suggesting that real-time monitoring of entropy could enhance marathon performance by providing insights into a runner's physiological state and helping to prevent the onset of hitting the wall.

High-Intensity Interval Training and Vitamin D3 Supplementation Decrease CCL-5 and CCR5 Expression In White Adipose Tissue of Diabetic Rats Fed with A High-Fat Diet and Streptozotocin.

The purpose of this study was to investigate the effects of 8 weeks of high-intensity interval training (HIIT) and vitamin D3 supplementation on Chemokine (C-C motif) Ligand 5 (CCL-5) and C-C motif chemokine receptor 5 (CCR5) in the white adipose tissue (WAT) of male rats with type 2 diabetes (T2DM). The experimental study involved 40 male Wistar rats divided into 5 groups (n=8). These groups were healthy control (HC), diabetic control (DC), diabetic+HIIT (DHIIT), diabetic+vitamin D3 (DD3), and diabetic+HIIT+vitamin D3 (DHIITD3). The rats completed 8 weeks of HIIT, consisting of 12 sessions lasting 1 minute each at an intensity of 90-95% of their maximum running speed. Additionally, the rats were administered a weekly dose of 10,000 IU/kg of vitamin D3 for 8 weeks. The levels of CCL-5 (P<0.001) and CCR5 (P=0.003) were found to be higher in the DC group as compared to the HC group. However, when HIIT training and vitamin D3 were administered together, there was a decrease in CCL-5 (P=0.001) and CCR5 (P<0.001) in the DHIITD3 group (P=0.001). Similarly, vitamin D3 alone reduced CCR5 levels in the DD3 group (P< 0.001). Also, the decrease of CCR5 in the DD3 group was higher than in the DHIIT group (P=0.022), and the DHIITD3 group was higher than in the DHIIT group (P<0.001), but there was no difference between the DD3 and DHIITD3 groups (P≥0.05). The results indicate that combining HIIT training with vitamin D3 has a greater effect on reducing the expression of CCL-5 and CCR5 in the white adipose tissue of rats with type 2 diabetes induced by streptozotocin (STZ) and a high-fat diet (HFD), compared to the effects of each one alone. It is recommended that the study be conducted by measuring the variables involved in the mechanisms and the changes in CCL-5 and CCR5.

Temporal relation transformer for robust visual tracking with dual-memory learning

Recently, transformer trackers mostly associate multiple reference images with the search area to adapt to the changing appearance of the target. However, they ignore the learned cross-relations between the target and surrounding, leading to difficulties in building coherent contextual models for specific target instances. This paper presents a Temporal Relation Transformer Tracker (TRTT) for robust visual tracking, providing a concise approach to modeling temporal relations by dual target memory learning. Specifically, a temporal relation transformer network generates paired memories based on static and dynamic templates, which are reinforced interactively. The memory contains implicit relation hints that capture the relations between the tracked object and its immediate surroundings. More importantly, to ensure consistency of target instance identities between frames, the relation hints from previous frames are transferred to the current frame for merging temporal contextual attention. Our method also incorporates mechanisms for reusing favorable cross-relations and instance-specific features, thereby overcoming background interference in complex spatio-temporal interactions through a sequential constraint. Furthermore, we design a memory token sparsification method that leverages the key points of the target to eliminate interferences and optimize attention calculations. Extensive experiments demonstrate that our method surpasses advanced trackers on 8 challenging benchmarks while maintaining real-time running speed.

AL-MobileNet: a novel model for 2D gesture recognition in intelligent cockpit based on multi-modal data

As the degree of automotive intelligence increases, gesture recognition is gaining more attention in human-vehicle interaction. However, existing gesture recognition methods are computationally intensive and perform poorly in multi-modal sensor scenarios. This paper proposes a novel network structure, AL-MobileNet (MobileNet with Attention and Lightweight Modules), which can quickly and accurately estimate 2D gestures in RGB and infrared (IR) images. The innovations of this paper are as follows: Firstly, to enhance multi-modal data, we created a synthetic IR dataset based on real 2D gestures and employed a coarse-to-fine training approach. Secondly, to speed up the model's computation on edge devices, we introduced a new lightweight computational module called the Split Channel Attention Block (SCAB). Thirdly, to ensure the model maintains accuracy in large datasets, we incorporated auxiliary networks and Angle-Weighted Loss (AWL) into the backbone network. Experiments show that AL-MobileNet requires only 0.4 GFLOPs of computational power and 1.2 million parameters. This makes it 1.5 times faster than MobileNet and allows for quick execution on edge devices. AL-MobileNet achieved a running speed of up to 28 FPS on the Ambarella CV28. On both general datasets and our dataset, our algorithm achieved an average PCK0.2 score of 0.95. This indicates that the algorithm can quickly generate accurate 2D gestures. The demonstration of the algorithm can be reviewed in gesturebaolong.

Cerebellar activity in PINK1 knockout rats during volitional gait.

Preclinical models of Parkinson's disease are imperative to gain insight into the neural circuits that contribute to gait dysfunction in advanced stages of the disease. A PTEN-induced putative kinase 1 knockout early-onset model of Parkinson's disease may be a useful rodent model to study the effects of neurotransmitter degeneration caused by a loss of PTEN-induced putative kinase 1 function on brain activity during volitional gait. The goal of this study was to measure changes in neural activity at the cerebellar vermis at 8 months of age. It was found that gait deficits, except run speed, were not significantly different from age-matched wild-type controls, as previously reported. PTEN-induced putative kinase 1 knockout (n = 4) and wild-type (n = 4) rats were implanted with a micro-electrocorticographic array placed over cerebellar vermis Lobules VI (a-c) and VII. Local field potential recordings were obtained during volitional gait across a runway. Power spectral analysis and coherence analysis were used to quantify network oscillatory activity in frequency bands of interest. Cerebellar vermis power was hypoactive in the beta (VIb, VIc and VII) and alpha (VII) bands at cerebellar vermis Lobules VIb, VIc and VII in PTEN-induced putative kinase 1 knockout rats compared with wild-type controls during gait (P < 0.05). These results suggest that gait improvement in PTEN-induced putative kinase 1 knockout rats at 8 months may be a compensatory mechanism attributed to movement corrections caused by a decreased inhibition of the alpha band of cerebellar vermis Lobule VII and beta band of Lobules VIb, VIc and VII. The PTEN-induced putative kinase 1 knockout model may be a valuable tool for understanding the circuit mechanisms underlying gait dysfunction in patients with early-onset Parkinson's disease with a functional loss of PTEN-induced putative kinase 1. Future studies investigating the cerebellar vermis as a potential biomarker and therapeutic target for the treatment of gait dysfunction in Parkinson's disease are warranted.

Cerebellar activity in hemi-parkinsonian rats during volitional gait and freezing.

Parkinson's disease is a neurodegenerative disease characterized by gait dysfunction in the advanced stages of the disease. The unilateral 6-hydroxydopamine toxin-induced model is the most studied animal model of Parkinson's disease, which reproduces gait dysfunction after >68% dopamine loss in the substantia nigra pars compacta. The extent to which the neural activity in hemi-parkinsonian rats correlates to gait dysfunction and dopaminergic cell loss is not clear. In this article, we report the effects of unilateral dopamine depletion on cerebellar vermis activity using micro-electrocorticography during walking and freezing on a runway. Gait and neural activity were measured in 6-hydroxydopamine- and sham-lesioned rats aged between 4 and 5 months at 14, 21 and 28 days after infusion of 6-hydroxydopamine or control vehicle into the medial forebrain bundle (n = 20). Gait deficits in 6-hydroxydopamine rats were different from sham rats at 14 days (P < 0.05). Gait deficits in 6-hydroxydopamine rats improved at 21 and 28 days except for run speed, which decreased at 28 days (P = 0.018). No differences in gait deficits were observed in sham-lesioned rats at any time points. Hemi-parkinsonian rats showed hyperactivity in the cerebellar vermis at 21 days (P < 0.05), but not at 14 and 28 days, and the activity was reduced during freezing epochs in Lobules VIa, VIb and VIc (P < 0.05). These results suggest that dopaminergic cell loss causes pathological cerebellar activity at 21 days post-lesion and suggest that compensatory mechanisms from the intact hemisphere contribute to normalized cerebellar activity at 28 days. The decrease in cerebellar oscillatory activity during freezing may be indicative of neurological changes during freezing of gait in patients with Parkinson's disease making this region a potential location for biomarker detection. Although the unilateral 6-hydroxydopamine model presents gait deficits that parallel clinical presentations of Parkinson's disease, further studies in animal models of bilateral dopamine loss are needed to understand the role of the cerebellar vermis in Parkinson's disease.

Advances and Challenges in the Hunting Instability Diagnosis of High-Speed Trains.

With the continuous increase in train running speeds and the rapid complexity of operation environments, running stability of the high-speed train is facing significant challenges. A series of abnormal vibration issues, caused by hunting instability, have emerged, including bogie instability alarm, carbody swaying, and carbody shaking, posing a significant threat to the safe and stable operation of high-speed trains. Therefore, the monitoring and diagnosis of hunting instability have become important research topics in rail transit. This review follows the development of fault diagnosis for bogie hunting instability and carbody hunting instability. It first summarizes the existing evaluation standards and innovative diagnostic methods. Due to the current limitation of hunting instability evaluation standards, which can only detect large-amplitude hunting, this paper addresses the gap in evaluation criteria for early-stage, small amplitude hunting instability diagnosis. A thorough overview of the progress made by researches in this field of research is given, emphasizing three primary facets: diagnostic signal sources, diagnostic features, and diagnostic targets. Furthermore, given that existing methods only classify faults into small and large amplitudes, which does not meet the practical need for quickly and accurately identifying fault types and severity during operation, this review introduces existing works on the detailed assessment and fault tracing of hunting instability, as well as the mechanisms underlying its occurrence, with the aim of achieving a comprehensive diagnosis of hunting instability. Finally, the limitations of current methods and the future development trends in hunting instability diagnostics are discussed and summarized. This paper provides readers with a framework for the research process of hunting instability diagnosis, offering valuable references and innovative perspectives for their future research efforts.

Construction of Wushu Routine Training Program for Wellness Promotion in Secondary School Students

Background and Aim: As an important way of small and medium-sized sports communication, the current schools propose to stimulate the physical quality of middle school students in Wushu training. Wushu training is also to train primary and middle school students to enhance their physical fitness, enhance their self-confidence, and improve their emotional conditions. Therefore, the research goal of this paper is to promote the construction of healthy Wushu sports training programs for middle school students. The main research objects of this paper are middle school students. Research method: this study adopts the literature method, questionnaire method, and experimental comparison method of the exercise intervention of middle school students’ physique and mental health, in this paper, a total number of 50 students in Xianyang City, 50 were tested, and 30 could not be tested due to some reasons, such as lower limb injury, cardiopulmonary disease, and other symptoms. Result: After the eight-week Wushu routine exercise training intervention, the lung capacity increased (endurance quality), sitting forward flexion (flexibility quality), high leg lift (coordination ability), and 50 m short distance running (speed strength quality) were all improved and enhanced. the improvement of emotional state, self-confidence, and the improvement of anti-frustration ability to establish a sense of achievement reduce anxiety, and resist depression was significantly reduced. the subjects of lung capacity increase, flexibility, coordination, speed strength and aerobic endurance, anxiety, and depression mood significantly decreased. The results: the main ways to stimulate the physical quality of middle school students through Wushu routine training. It shows that wushu routine training can not only improve the physique of middle school students, but also promote mental health, and provides a certain basis for exercise training practice through exercise intervention experiments. Conclusion: After the eight-week Wushu routine training intervention, the lung capacity increased (endurance quality), sitting forward flexion (flexibility quality), high leg lift (coordination ability), and 50 m short distance running (speed strength quality) were all improved and enhanced. the improvement of emotional state, and self-confidence, and the improvement of anti-frustration ability to establish a sense of achievement reduces anxiety and resist depression was significantly reduced.

Enhancing Sports Injury Risk Assessment in Soccer Through Machine Learning and Training Load Analysis.

Sports injuries pose significant challenges in athlete welfare and team dynamics, particularly in high-intensity sports like soccer. This study used machine learning algorithms to assess non-contact injury risk in professional male soccer players from physiological and mechanical load variables. Twenty-five professional male soccer players with a first-time, non-contact muscle injury were included in this study. Recordings of external load (speed, distance, and acceleration/deceleration data) and internal load (heart rate) were obtained during all training sessions and official matches over a 4-year period. Machine learning model training and evaluation features were calculated for each of nine different metrics for a 28-day period prior to the injury and an equal-length baseline epoch. The acute surge in the values of each workload metric was quantified by the deviation of maximum values from the average, while the variations of cumulative workload over the last four weeks preceding injury were also calculated. Seven features were selected by the model as prominent estimators of injury incidence. Three of the features concerned acute load deviations (number of sprints, training load score-incorporating heart rate and muscle load- and time of heart rate at the 90-100% of maximum). The four cumulative load features were (total distance, high speed and sprint running distance and training load score). The accuracy of the muscle injury risk assessment model was 0.78, with a sensitivity of 0.73 and specificity of 0.85. Our model achieved high performance in injury risk detection using a limited number of training load variables. The inclusion, for the first time, of heart rate related variables in an injury risk assessment model highlights the importance of physiological overload as a contributor to muscle injuries in soccer. By identifying the important parameters, coaches may prevent muscle injuries by controlling surges of training load during training and competition.

Fascicle Behavior and Muscle Activity of The Biceps Femoris Long Head during Running at Increasing Speeds.

Hamstring strain injuries (HSIs) are prevalent in sports involving high-speed running and most of the HSIs are biceps femoris long head (BFlh) injuries. The primary cause for HSIs during high-speed running remains controversial due to the lack of in vivo measurement of the BFlh muscle behavior during running. Therefore, the purpose of this study was to quantify the muscle-tendon unit (MTU) and fascicle behavior of BFlh during running. Seven college male sprinters (22.14 ± 1.8 years; 177.7 ± 2.5 cm; 70.57 ± 5.1 kg; personal bests in 100m: 11.1 ± 0.2 s) were tested on a motorized treadmill instrumented with two force plate for running at 4, 5, 6m/s. The ground reaction force (GRF), 3D lower limb kinematics, EMG, and ultrasound images of biceps femoris long head (BFlh) in the middle region were recorded simultaneously. BFlh fascicles undergo little length change (about 1 cm) in the late swing phase during running at three submaximal speeds. BFlh fascicle lengthening accounted for about 30% of MTU length change during the late swing phase. BFlh was most active during the late swing and early stance phases, ranging from 83%MVC at a running speed of 4 m/s to 116%MVC at 6 m/s. Muscle fascicles in the middle region of BFlh undergo relatively little lengthening relative to the MTU in the late swing phase during running in comparison to results from simulation studies. These results suggest that there is a decoupling between the fascicle in the middle region and MTU length changes during the late swing phase of running.

Reliability assessment of additively manufactured TB6 titanium alloy wheel hubs

The strength and reliability of the additively manufactured titanium alloy wheel hub have been investigated and analyzed. The running speed of the supercar, which utilizes the additively manufactured titanium alloy wheel hub, is divided into three levels. The impact power on the wheel hub is computed for each speed level. Then, the maximum stress of the wheel hub under each level of impact is obtained using finite element analysis. Formulas for calculating the residual strength and reliability under each level of fatigue impact are provided. Additionally, formulas for calculating residual strength and reliability of wheel hubs, considering the random cross occurrence of the three types of impacts, are given. Finally, the changes in residual strength and reliability are analyzed. This method is not only suitable for the reliability calculation of additively manufactured titanium alloy wheels but also applicable to the reliability calculation of other alloy wheels.

Dynamic impact analysis of the time-delay levitation control system on maglev vehicle system after adding smith predictor

The time delay (TD) in the levitation control system significantly affects the dynamic performance of the closed-loop system in electromagnetic suspension (EMS) maglev vehicles. Excessive TD can cause levitation instability, making it essential to explore effective mitigation methods. To address this issue, a Smith Predictor (SP) is integrated into the traditional PID levitation control system. The combination of theoretical analysis and numerical simulation is employed to assess the stability of the time-delay levitation control system after the integration of the Smith Predictor. Theoretical analysis reveals that when TD exceeds a critical threshold, the levitation system becomes unstable. The addition of SP alters the root trajectory of the system characteristic equation from positive to negative, and recovers the levitation system to stable status. Assuming complete knowledge of the dynamic system, the TD compensation value in the SP becomes a key parameter that determines its performance. A minimum effective value (MEV) for TD compensation is identified, correlating with the system's stability region. Under the influence of TD, more complex systems and higher running speeds of the maglev vehicle lead to a narrower stable region and a larger MEV for TD compensation. Given the simulation parameters in this paper, with a system TD of 15 ms and a maximum vehicle speed of 160 km/h, the MEV for TD compensation in the SP should be set at 12 ms.

Hubungan Daya Tahan Kekuatan Otot Tungkai dengan Laju Lari 100 M pada siswa Kelas VII-3 SMP Negeri 1 Bonepantai

In an effort to improve running ability, muscle strength endurance is very important. The aim of this research is to explain the relationship between the strength endurance of body movements, especially the leg or leg muscles, and the extent to which the ability to withstand the strength of the leg or leg muscles affects 100 meter running speed. junior high school students in grades VII�3. In this research, the correlation method is used simultaneously with a quantitative approach. To collect data, a Leg Dynamometer and a Stop Watch were used. Data is analyzed using simple methods and multiple correlations, along with the Product Moment formula. The results showed that (1) there was a significant relationship between leg muscle strength and running speed for 100 meters, with a correlation value of 0.449. The results show that (1) leg muscle endurance influences 100 m running speed because the calculated value is 2.510 &gt; table is 2.008, and (2) variable X influences variable Y. The determination coefficient of 0.201 from this output shows that the influence of the independent variable ( leg muscle endurance) in the dependent variable (100 m running speed) is 20.1% and the significance value is 0.001&lt;0.005

EMG Activity of Lower Limb Muscles during Anti-Gravity Treadmill Running with Different Loads and Speeds

The study’s objective was to identify the features of internal movement structure that depend on speed and the importance of unloading when jogging on an anti-gravity treadmill. The aim was to investigate whether the internal structure of running changes under unloaded conditions, using an anti-gravity treadmill. Twenty male competitive middle- and long-distance runners with the following characteristics participated in the study: age, 25 ± 5 years; body weight, 67.2 ± 8.9 kg; body height, 177 ± 11 cm; and training experience, 9 ± 5 years. The gastrocnemius (GC), tibialis anterior (T), quadriceps femoris (Q), biceps femoris (B), and gluteus (G) were the five lower limb muscles whose muscle activity was evaluated. Surface electromyography (sEMG) was used to measure muscle activation while jogging and running on the AlterG Anti-Gravity Treadmill. The study method involved capturing the examined muscular activity at four different speeds: 6, 10, 14, and 18 km/h. At each of these speeds, four two-minute measurements were taken with varying body weight relief: 100%, 75%, 50%, and 25% of body weight. Repeated measures multivariate analysis of variance (RM-MANOVA) [F = 3.4663 p = 0.0001] showed that as running speed increases, the muscular activity of each muscle, expressed as a percentage of maximum muscle tension (%MVIC), decreases significantly. Results indicate that running pace affects the dynamics of the reduction in muscle activity in every examined muscle. As one runs faster, the decline in dynamics becomes more intense. At the slowest jogging pace (6 km/h), the variations were almost negligible (±4 percentage points between 25% and 100% body weight relief) as unloading increased. However, the discrepancies reached up to 14 percentage points at the fastest running speed (18 km/h). In every muscle studied, distinctive patterns and significant dynamics at high speeds were observed. The study’s findings suggest that using an anti-gravity treadmill for training can be beneficial, yet it is important to consider the significant relationships between speed and relief, as these variables could impact maintaining a proper movement pattern and running style. This knowledge may be useful when choosing the right training regimens and loads for runners recovering from injuries.

Menstrual Cycle Phases and Elite Female Soccer During Training: Exercise Load Perception and External Workload Monitoring

BACKGROUND: Female soccer has grown exponentially in the last years, however studies on women soccer players are very few compared with male ones and several inconsistencies are reported in the literature for female players. Physiological hormonal fluctuations during the different moments of menstrual cycle could have important implications on soccer performance, therefore, the aim of the present study was to investigate the impact of menstrual cycle phases on external and internal loads in elite women’ soccer players during an in-season training period, and to describe the internal-external training load relationship, in relation to different menstrual cycle moments. METHODS: 16 elite players from Italian soccer first division were monitored for 12 weeks. The main internal parameter (rate of perceived exertion - RPE), external variables (total time, total distance, high speed running - HSR, numbers of accelerations/decelerations) and session-RPE were collected during training sessions and analyzed trough a repeated-measures ANOVA to identify differences in the MC weeks. Menstrual cycle was monitored through daily questionnaires and was divided into four phases: menstruation week, pre-ovulation, post-ovulation, and pre-cycle. RESULTS: HSR and total distance were significantly lower during menstruation week than post-ovulation week (18318.70 ±1802.04 m vs 20358.41 ± 1639.27 m, respectively; p=0.022). A significant correlation was found in pre-cycle week between RPE and total distance (r=0.545; p=0.029), and between session-RPE with total distance (r=0.514; p=0.042) and total time (r=0.502; p=0.048). When considering the whole menstrual cycle, weak and moderate correlations were found for RPE and session-RPE with total time, total distance and HSR. CONCLUSION: Appropriate menstrual cycle monitoring is required for better interpretation of players’ response in elite women’s soccer training, given that during menstruation week, external load variables could be impaired. RPE and session-RPE values do not change statistically with changes in external variables, and their relationship showed unclear results, highlighting caution when interpreting them, and suggesting their use in combination with other parameters, especially during early follicular phase.

Preseason and In-Season High-Speed Running Demands of 2 Professional Australian Rules Football Teams.

Australian Rules Football athletes complete long preseasons, yet injuries occur frequently at early stages of the competitive season. Little is known about the high-speed running (HSR) prescription during a preseason or whether players are adequately prepared for competition. This study described absolute and relative preseason and in-season HSR demands of 2 professional Australian football teams. HSR and sprinting volumes are significantly lower in elite Australian Rules football athletes during in-season compared with preseason. Cohort study. Level 3. During the 2019 season, HSR volume was collected for 2 professional Australian football teams (n = 55). Individual maximum speeds (Vmax) were captured to calculate relative running speed thresholds, as reported in 5% increments from 70%Vmax to 100%Vmax. Weekly volume of running above 70%Vmax (P = 0.01; r = 0.56) and 80%Vmax (P = 0.01; r = 0.58) was significantly greater in the preseason than the in-season. The weekly volume completed above 90%Vmax was not significantly greater in the preseason than the in-season (P = 0.10; r = 0.22). Individual variation in the distance completed at specific percentages of Vmax expressed as a coefficient of variation was reported as 51% at 71% to 80%Vmax, 39% at 81% to 90%Vmax, and 41% at 91% to 100%Vmax. The volume of HSR completed by athletes is far greater in the initial 4 weeks of the preseason than in any other point in preseason or competitive phases. At the individual level, there is substantial variation in the distance covered. This supports the concept of a heavily individualized approach to high-speed prescription and monitoring. Practitioners should carefully consider individual variation regarding sprinting volume during both preseason and in-season when prescribing and monitoring training to improve on-field performance and reduce the risk of injury.