Breast-torso movement coordination during running in different breast support.

To reduce breast motion with a bra, we need to understand what drives the motion of the breasts, and what variables change as support increases. Quantifying breast-torso coordination and movement complexity across the gait cycle may offer deeper insights than previously reported discrete time lag. We aimed to compare breast-torso coordination and mutual influence across breast support conditions during running. Twelve female participants ran on a treadmill at 10 km h-1 with an encapsulation and compression sports bra, and in no bra. Nipple and torso position was recorded. Vector coding, granger causality and transfer entropy were calculated within gait cycles. In both bra conditions, a greater percentage of gait cycles was spent with the breast and torso in-phase (> 90%) compared to no bra running (~ 66%, p < 0.001), with most time spent in-phase in the encapsulation versus compression bra (p = 0.006). There was a main effect of breast support condition on Granger causality (p < 0.001), both from breast to torso and torso to breast. Transfer of information was highest from torso to breast, compared to breast to torso in all conditions. Overall, these results provide novel insight into the mutual and complex interaction between the breast and the torso while running in different bra conditions. The approaches presented allow for a greater understanding of bra support conditions than existing discrete measures, which may relate to comfort and performance. Therefore, measures of coupling, predictability and transfer of complexity should be employed in future work examining these features.

The Cumulative Impacts of Fatigue during Overload Training Can Be Tracked Using Field-Based Monitoring of Running Stride Interval Correlations.

Integrating running gait coordination assessment into athlete monitoring systems could provide unique insight into training tolerance and fatigue-related gait alterations. This study investigated the impact of an overload training intervention and recovery on running gait coordination assessed by field-based self-testing. Fifteen trained distance runners were recruited to perform 1-week of light training (baseline), 2 weeks of heavy training (high intensity, duration, and frequency) designed to overload participants, and a 10-day light taper to allow recovery and adaptation. Field-based running assessments using ankle accelerometry and online short recovery and stress scale (SRSS) surveys were completed daily. Running performance was assessed after each training phase using a maximal effort multi-stage running test-to-exhaustion (RTE). Gait coordination was assessed using detrended fluctuation analysis (DFA) of a stride interval time series. Two participants withdrew during baseline training due to changed personal circumstances. Four participants withdrew during heavy training due to injury. The remaining nine participants completed heavy training and were included in the final analysis. Heavy training reduced DFA values (standardised mean difference (SMD) = -1.44 ± 0.90; p = 0.004), recovery (SMD = -1.83 ± 0.82; p less than 0.001), performance (SMD = -0.36 ± 0.32; p = 0.03), and increased stress (SMD = 1.78 ± 0.94; p = 0.001) compared to baseline. DFA values (p = 0.73), recovery (p = 0.77), and stress (p = 0.73) returned to baseline levels after tapering while performance trended towards improvement from baseline (SMD = 0.28 ± 0.37; p = 0.13). Reduced DFA values were associated with reduced performance (r2 = 0.55) and recovery (r2 = 0.55) and increased stress (r2 = 0.62). Field-based testing of running gait coordination is a promising method of monitoring training tolerance in running athletes during overload training.

Validity and Reliability of Movesense HR+ ECG Measurements for High-Intensity Running and Cycling.

Low-cost, portable devices capable of accurate physiological measurements are attractive tools for coaches, athletes, and practitioners. The purpose of this study was primarily to establish the validity and reliability of Movesense HR+ ECG measurements compared to the criterion three-lead ECG, and secondarily, to test the industry leader Garmin HRM. Twenty-one healthy adults participated in running and cycling incremental test protocols to exhaustion, both with rest before and after. Movesense HR+ demonstrated consistent and accurate R-peak detection, with an overall sensitivity of 99.7% and precision of 99.6% compared to the criterion; Garmin HRM sensitivity and precision were 84.7% and 87.7%, respectively. Bland-Altman analysis compared to the criterion indicated mean differences (SD) in RR' intervals of 0.23 (22.3) ms for Movesense HR+ at rest and 0.38 (18.7) ms during the incremental test. The mean difference for Garmin HRM-Pro at rest was -8.5 (111.5) ms and 27.7 (128.7) ms for the incremental test. The incremental test correlation was very strong (r = 0.98) between Movesense HR+ and criterion, and moderate (r = 0.66) for Garmin HRM-Pro. This study developed a robust peak detection algorithm and data collection protocol for Movesense HR+ and established its validity and reliability for ECG measurement.

Validity of an Inertial Measurement Unit System to Measure Lower Limb Kinematics at Point of Contact during Incremental High-Speed Running.

There is limited validation for portable methods in evaluating high-speed running biomechanics, with inertial measurement unit (IMU) systems commonly used as wearables for this purpose. This study aimed to evaluate the validity of an IMU system in high-speed running compared to a 3D motion analysis system (MAS). One runner performed incremental treadmill running, from 12 to 18 km/h, on two separate days. Sagittal angles for the shank, knee, hip and pelvis were measured simultaneously with three IMUs and the MAS at the point of contact (POC), the timing when the foot initially hits the ground, as identified by IMU system acceleration, and compared to the POC identified via force plate. Agreement between the systems was evaluated using intra-class correlation coefficients, Pearson's r, Bland-Altman limits of agreements, root mean square error and paired t-tests. The IMU system reliably determined POC (which subsequently was used to calculate stride time) and measured hip flexion angle and anterior pelvic tilt accurately and consistently at POC. However, it displayed inaccuracy and inconsistency in measuring knee flexion and shank angles at POC. This information provides confidence that a portable IMU system can aid in establishing baseline running biomechanics for performance optimisation, and/or inform injury prevention programs.

Muscle-Tendon Unit Properties in Mice Bred for High Levels of Voluntary Running: Novel Physiologies, Coadaptation, Trade-Offs, and Multiple Solutions in the Evolution of Endurance Running.

AbstractMuscle-tendon unit (MTU) morphology and physiology are likely major determinants of locomotor performance and therefore Darwinian fitness. However, the relationships between underlying traits, performance, and fitness are complicated by phenomena such as coadaptation, multiple solutions, and trade-offs. Here, we leverage a long-running artificial selection experiment in which mice have been bred for high levels of voluntary running to explore MTU adaptation, as well as the role of coadaptation, multiple solutions, and trade-offs, in the evolution of endurance running. We compared the morphological and contractile properties of the triceps surae complex, a major locomotor MTU, in four replicate selected lines to those of the triceps surae complex in four replicate control lines. All selected lines have lighter and shorter muscles, longer tendons, and faster muscle twitch times than all control lines. Absolute and normalized maximum shortening velocities and contractile endurance vary across selected lines. Selected lines have similar or lower absolute velocities and higher endurance than control lines. However, normalized shortening velocities are both higher and lower in selected lines than in control lines. These findings potentially show an interesting coadaptation between muscle and tendon morphology and muscle physiology, highlight multiple solutions for increasing endurance running performance, demonstrate that a trade-off between muscle speed and endurance can arise in response to selection, and suggest that a novel physiology may sometimes allow this trade-off to be circumvented.

Higher intensity exercise after encoding is more conducive to episodic memory retention than lower intensity exercise: A field study in endurance runners.

An acute bout of exercise in the moments after learning benefits the retention of new memories. This finding can be explained, at least partly, through a consolidation account: exercise provides a physiological state that is conducive to the early stabilisation of labile new memories, which supports their retention and subsequent retrieval. The modification of consolidation through non-invasive exercise interventions offers great applied potential. However, it remains poorly understood whether effects of exercise translate from the laboratory to naturalistic settings and whether the intensity of exercise determines the effect in memory. To this end, adult endurance runners were recruited as participants and completed two study sessions spaced two weeks apart. In each session, participants were presented with a list of words and asked to recall them on three occasions: (i) immediately following their presentation, (ii) after a 30-minute retention interval, and (iii) after 24 hours. Crucially, the 30-minute retention interval comprised our experimental manipulation: higher intensity exercise (running) in the first session and lower intensity exercise (walking) in the second, both completed in a naturalistic setting around participants' existing physical activity training programmes. Exertion was recorded through heart rate and rate of perceived exertion data. Alertness, mood, and arousal ratings were also collected before and after the 30-minute retention interval. Immediate memory for the two wordlists was matched, but participants retained significantly more words after 30 minutes and 24 hours when encoding was followed by higher than lower intensity exercise. Exertion data revealed that participants experienced vigorous and light exercise in the higher and lower intensity conditions, respectively. Significant improvements in alertness, mood, and arousal were observed following both exercise conditions, but especially in the higher intensity condition. These outcomes reveal that experiencing higher intensity physical activity in the field is conducive to declarative memory retention, possibly because it encourages consolidation.

Composite activity type and stride-specific energy expenditure estimation model for thigh-worn accelerometry.

BACKGROUND: Accurately measuring energy expenditure during physical activity outside of the laboratory is challenging, especially on a large scale. Thigh-worn accelerometers have gained popularity due to the possibility to accurately detect physical activity types. The use of machine learning techniques for activity classification and energy expenditure prediction may improve accuracy over current methods. Here, we developed a novel composite energy expenditure estimation model by combining an activity classification model with a stride specific energy expenditure model for walking, running, and cycling. METHODS: We first trained a supervised deep learning activity classification model using pooled data from available adult accelerometer datasets. The composite energy expenditure model was then developed and validated using additional data based on a sample of 69 healthy adult participants (49% female; age = 25.2 ± 5.8 years) who completed a standardised activity protocol with indirect calorimetry as the reference measure. RESULTS: The activity classification model showed an overall accuracy of 99.7% across all five activity types during validation. The composite model for estimating energy expenditure achieved a mean absolute percentage error of 10.9%. For running, walking, and cycling, the composite model achieved a mean absolute percentage error of 6.6%, 7.9% and 16.1%, respectively. CONCLUSIONS: The integration of thigh-worn accelerometers with machine learning models provides a highly accurate method for classifying physical activity types and estimating energy expenditure. Our novel composite model approach improves the accuracy of energy expenditure measurements and supports better monitoring and assessment methods in non-laboratory settings.

Assigning goal-probability value to high intensity runs in football.

High intensity run counts-defined as the number of runs where a player reaches and maintains a speed above a certain threshold-are a popular football running statistic in sport science research. While the high intensity run number gives an insight into the volume or intensity of a player's work rate it does not give any indication about the effectiveness of their runs or whether or not they provided value to the team. To provide the missing context of value this research borrows the concept of value models from sports analytics which assign continuous values to each frame of optical tracking data. In this research the value model takes the form of goal-probability for the in-possession team. By aligning the value model with high intensity runs this research identifies positive correlations between speed and acceleration with high value runs, as well as a negative correlation between tortuosity (a measure of path curvature) and high value runs. There is also a correlation between the number of players making high intensity runs concurrently and the value generated by the team, suggesting a form of movement coordination. Finally positional differences are explored demonstrating that attacking players make more in-possession high intensity runs when goal probability is high, whereas defensive players make more out-of-possession high intensity runs while goal probability is high. By assigning value to high-intensity runs practitioners are able to add new layers of context to traditional sport science metrics and answer more nuanced questions.

Influence of whole-body vibration and drop jump on the range of motion in the ankle joint and running parameters-A randomized crossover study.

BACKGROUND AND PURPOSE: Warm-up (WU) is a commonly practiced technique aimed at preparing athletes for physical activity. Although coaches and athletes consider WU essential, there is still an ongoing debate about its effectiveness. This might be due to the fact that WU procedures often rely on experiences rather than scientific research. During WU, athletes may pursue intermediate goals such as ensuring proper ranges of motion in joints, which seem crucial particularly for runners' ankle joints. Hence, the aim of this study was to evaluate influence of whole-body vibration (WBV), drop jump (DJ), and a combination of both (WBV + DJ) in terms of ankle dorsiflexion and running parameters among recreational runners. METHODS: Sixteen runners performed as a WU: five sets of 30 s calf raises without WBV (CTRL), five sets of 30 s calf raises during WBV, five sets of six DJ, five sets of 30 s calf raises during WBV followed by 6 DJ. Range of motion (ROM) of the ankle joint was measured in a prone position using an inclinometer for the soleus and gastrocnemius muscles, separately. Measurements were conducted before and after WU, and after a 3000 m run. RESULTS: There was no interaction for time and WU for left (p = 0.926) and right (p = 0.738) soleus muscle as well as for left (p = 0.748) and right (p = 0.197) gastrocnemius muscles. No difference (p = 0.914) for the running time was found. DISCUSSION: WBV, drop jumps, or a combination of both did not affect ankle dorsiflexion and running time.

Consumer-priced wearable sensors combined with deep learning can be used to accurately predict ground reaction forces during various treadmill running conditions.

Ground reaction force (GRF) data is often collected for the biomechanical analysis of running, due to the performance and injury risk insights that GRF analysis can provide. Traditional methods typically limit GRF collection to controlled lab environments, recent studies have looked to combine the ease of use of wearable sensors with the statistical power of machine learning to estimate continuous GRF data outside of these restrictions. Before such systems can be deployed with confidence outside of the lab they must be shown to be a valid and accurate tool for a wide range of users. The aim of this study was to evaluate how accurately a consumer-priced sensor system could estimate GRFs whilst a heterogeneous group of runners completed a treadmill protocol with three different personalised running speeds and three gradients. Fifty runners (25 female, 25 male) wearing pressure insoles made up of 16 resistive sensors and an inertial measurement unit ran at various speeds and gradients on an instrumented treadmill. A long short term memory (LSTM) neural network was trained to estimate both vertical ( G R F v ) and anteroposterior ( G R F a p ) force traces using leave one subject out validation. The average relative root mean squared error (rRMSE) was 3.2% and 3.1%, respectively. The mean ( G R F v ) rRMSE across the evaluated participants ranged from 0.8% to 8.8% and from 1.3% to 17.3% in the ( G R F a p ) estimation. The findings from this study suggest that current consumer-priced sensors could be used to accurately estimate two-dimensional GRFs for a wide range of runners at a variety of running intensities. The estimated kinetics could be used to provide runners with individualised feedback as well as form the basis of data collection for running injury risk factor studies on a much larger scale than is currently possible with lab based methods.

Crocus Sativus Linnaeus (Saffron) intake does not affect physiological and perceptual responses during a repeated sprint test in healthy active young males.

The study aimed to investigate the effects of acute ingestion of saffron (SAF) on physiological (i.e., heart rate and blood lactate) and perceptual (i.e., ratings of perceived exertion [RPE] and feeling scale) measures in response to a repeated-sprint ability test (RSS) in healthy young males (N = 22; mean ± SD: age, 21.7 ± 1.24 yrs.). All participants completed two experimental trials with a one-week washout period using a double-blind, placebo-controlled, crossover design. In each session, the participants were randomly chosen to receive either a capsule of saffron (300 mg) (SAF session) or a capsule of lactose (PLB session) two hours before performing the RSS.No significant differences (p > 0.05) were found for heart rate, RPE, and feeling scale between the SAF or PLB sessions at pre- and post-RSS. There were no significant changes (p > 0.05) in peak time, total time, fatigue index, and blood lactate in either the SAF or PLB sessions. Acute SAF ingestion did not significantly improve RSS performance nor physiological and perceptual measures in active young males. Future trials should address the topic by using shortened/prolonged higher doses of SAF on biological, physical, physiological, and perceptual responses to acute and chronic exercise.

The Effects of a 6-Week Plyometric and Sprint Interval Training Intervention on Soccer Player's Physical Performance.

Despite the well-documented benefits of sprint interval training (SIT) and plyometric training (PT) in improving the physical fitness of soccer players, it remains unclear which of these training methods is superior for enhancing players' aerobic and anaerobic performance. Therefore, this study aimed to compare the effects of SIT and PT on physical performance measures of male soccer players. Thirty male soccer players were randomly assigned to PT (n = 10), SIT (n = 10), and an active control group (CON, n = 10). Before and after the training period, participants underwent a battery of tests consisting of vertical jump, Wingate, linear sprint with and without ball dribbling, change of direction, ball kick, and the Yo-Yo intermittent recovery level 1 (Yo-Yo IR1) tests. Both groups exhibited similar improvements in maximal kicking distance (PT, effect size [ES] = 0.68; SIT, ES = 0.92) and measures of aerobic fitness including maximum oxygen uptake (PT, ES = 1.24; SIT, ES = 1.26) and first (PT, ES = 0.85; SIT, ES = 1.08) and second (PT, ES = 0.86; SIT, ES = 0.98) ventilatory thresholds. However, PT intervention resulted in greater changes in vertical jump (ES = 1.72 vs. 0.82, p = 0.001), anaerobic power (peak power, ES = 1.62 vs. 0.97, p = 0.009; mean power, ES = 1.15 vs. 1.20, p = 0.05), linear speed (20-m, ES = -1.58 vs. -0.98, p = 0.038; 20-m with ball, ES = -0.93 vs. 0.71, p = 0.038), and change of direction ability (ES = -2.56 vs. -2.71, p = 0.046) than SIT. In conclusion, both PT and SIT demonstrated effectiveness in enhancing aerobic performance among male soccer players. However, PT yielded superior improvements in anaerobic power, vertical jump, linear speed, and change of direction performance compared to SIT. These findings suggest that PT may offer additional benefits beyond aerobic conditioning.

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.

Characterizing Muscle Activity in Soccer Players with a History of Hamstring Strain Injuries during Accelerated Sprinting.

This study aimed to characterize muscle activity in male soccer players with a history of hamstring strain injuries (HSI) during accelerated sprinting. Thirteen patients each in the HSI group (history of HSI) and in the healthy group (with no history of HSI) were included. 26 male soccer players of which 13 with and 13 without HSI history were included in this study. Ten muscles were evaluated on electromyography activity during overground sprinting. The testing protocol consisted of a maximal sprint over a distance of 30 meters. One running stride was divided into the early stance phase, late stance phase, early swing phase, mid-swing phase, and late swing phase, and the average muscle activity per phase and the timing of the peak root-mean-square value appearance during each stride were calculated. Statistical analysis was performed using repeated-measures two-way ANOVA (group × phase), and multiple comparison tests were performed using the Bonferroni method when the interaction or main effect was significant. The statistical significance level was set at p < 0.05. Gluteus maximus (Gmax), gluteus medius (Gmed), and external oblique (EO) showed activity differences based on HSI history. Gmax was 30% lower, EO was 20% lower, and Gmed was 40% higher in HSI group. This study suggests that, despite previous findings that HSI is most likely during the late swing phase, the HSI group shows a higher injury risk in the early stance phase. This is due to differences in trunk and gluteal muscle activity between the late swing and early stance phases compared to the healthy group. In summary, HSI group had lower activity in the muscles contributing to trunk instability, especially EO and Gmax, before and after ground impact during accelerated sprinting, compared to Healthy.

Effectiveness of an Individualized Training Based on Dynamic Strength Index on Sprinting, Jumping and Change of Direction Performance in Basketball Players: A Randomized Controlled Trial.

The dynamic strength index (DSI) is calculated as the ratio between countermovement jump (CMJ) peak force and isometric mid-thigh pull (IMTP) peak force and is said to inform whether ballistic or strength training is warranted for a given athlete. This study assessed the impact of an individualized in-season resistance training program, guided by DSI on basketball players' physical performance. Forty-three elite players (19.4 ± 2.9 years; 1.97 ± 0.08 cm; 89.1 ± 9.5 kg) were divided into an intervention group (IG) (27 players) and a control group (CG) (16 players). The IG was further split based on DSI into a ballistic group (DSI ≤ 0.90, 11 players) and a strength group (DSI > 0.90, 16 players). Over five weeks, participants underwent two weekly resistance sessions, with the IG following a DSI-based program and the CG a standard program. Performance was measured pre- and post-intervention through 20-m sprints, 505 change of direction test, CMJ, and IMTP. There were statistically significant improvements in the IG, notably in sprint times (η2 = 0.12-0.21, p < 0.05) and 505 test (η2 = 0.15-0.16, p < 0.05), predominantly in the strength group. The CG's performance was either unchanged or declined for different variables. Our results suggest that DSI-guided training effectively enhances basketball players' physical performance within a competitive season.

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.

Europe has the fastest Ironman race courses and the fastest Ironman age group triathletes.

The majority of participants in Ironman triathlon races are age group athletes. We have extensive knowledge about recreational athletes' training and competition participation. Nonetheless, Ironman age group triathletes must achieve fast race times to qualify for the Ironman World Championship in Hawaii. They can, therefore, benefit from knowing where the fastest Ironman racecourses in the world are. The aim of the present study was to investigate where the fastest Ironman racecourses for age group triathletes are located in the world. Data from 677,702 Ironman age group finishers' records (544,963 from men and 132,739 from women) originating from 228 countries and participating in 444 events across 66 different Ironman race locations between 2002 and 2022 were analyzed. Data was analyzed through traditional descriptive statistics and with machine learning regression models. Four algorithms were tested (Random Forest Regressor, XG Boost Regressor, Cat Boot Regressor, and Decision Tree Regressor). The models used gender, age group, country of origin, environmental factors (average air and water temperatures), and the event location as independent variables to predict the final overall race time. Despite the majority of successful Ironman age group triathletes originating from the USA (274,553), followed by athletes from the United Kingdom (55,410) and Canada (38,264), these countries exhibited average overall race times that were significantly slower compared to the fastest countries. Most of the triathletes competed in Ironman Wisconsin (38,545), followed by Ironman Florida (38,157) and Ironman Lake Placid (34,341). The fastest overall race times were achieved in Ironman Copenhagen (11.68 ± 1.38 h), followed by Ironman Hawaii (11.72 ± 1.86 h), Ironman Barcelona (11.78 ± 1.43 h), Ironman Florianópolis (11.80 ± 1.52 h), Ironman Frankfurt (12.03 ± 1.38 h) and Ironman Kalmar (12.08 ± 1.47 h). The fastest athletes originated from Belgium (11.48 ± 1.47 h), followed by athletes from Denmark (11.59 ± 1.40 h), Switzerland (11.62 ± 1.49 h), Austria (11.68 ± 1.50), Finland (11.68 ± 1.40 h) and Germany (11.74 ± 15.1 h). Flat running and cycling courses were associated with faster overall race times. Three of the predictive models identified the 'country' and 'age group' variables as the most important predictors. Environmental characteristics showed the lowest influence regarding the other variables. The origin of the athlete was the most predictive variable whereas environmental characteristics showed the lowest influence. Flat cycling and flat running courses were associated with faster overall race times. The fastest overall race times were achieved mainly in European races such as Ironman Copenhagen, Ironman Hawaii, Ironman Barcelona, Ironman Florianópolis, Ironman Frankfurt and Ironman Kalmar. The fastest triathletes originated from European countries such as Belgium, Denmark, Switzerland, Austria, Finland, and Germany.

Influence of foot strike pattern on co-contraction around the ankle and oxygen uptake during running at 19 km/h.

This study investigated the coactivation of plantar flexor and dorsiflexor muscles and oxygen uptake during running with forefoot and rearfoot strikes at 15 and 19 km/h. We included 16 male runners in this study. The participants ran each foot strike pattern for 5 min at 15 and 19 km/h on a treadmill. During the running, respiratory gas exchange data and surface electromyographic (EMG) activity of the medial gastrocnemius (MG), lateral gastrocnemius (LG), soleus, and tibialis anterior muscles of the right lower limb were continuously recorded. The indices of oxygen uptake, energy expenditure (EE), and muscle activation were calculated during the last 2 min in each condition. During the stance phase of running at 15 and 19 km/h, activation of the tibialis anterior and MG muscles was lower and higher, respectively, with forefoot strike than with rearfoot strike. The foot strike pattern did not influence the oxygen uptake. These results suggest that the foot strike pattern has no clear effect on the oxygen uptake when running at 15 and 19 km/h. However, forefoot strike leads to plantar flexion dominance during co-contraction of the tibialis anterior and MG muscles, which are an antagonist and agonist for plantar flexion, respectively, during the stance phase.