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The study objective is to test general- and sport-specific adaption during a single training on the Flexibility Trainer. The device is designed to trigger residual muscle tone decreases of the hip-joint muscles by providing (nearly) isokinetic resistance during a full range of motion strength training in adduction/abduction and flexion/extension direction. Static hip flexion and abduction as well as kinematics of double side kicks were analysed on 15 participants before and after training (or rest for controls) to assess general flexibility and sport-specific movement range. Tests were recorded by a Vicon® motion capturing system. Static hip flexion and abduction as well as leg vector spreading angles (VSA) at different nodes of the kick were selected to determine adaptions of active and passive flexibility. Normalised hip joint moments, movement velocities and VSA were calculated to evaluate the training with the device. ANOVAs with 4-repeated measures and Friedman tests were performed to identify time differences and Bonferroni post-hoc test to identify between-subject effects. Significant differences were found for both static flexibility tests (Flexion = 13.65%; Abduction = 9.94%) and the VSA at specific action phases (≤15.15%). Results indicate that short-term adaptions when training with the Flexibility Trainer are exceeding comparable literature showing improved flexibility and sport-specific performance. [ABSTRACT FROM AUTHOR]

With recent technological advancements, quantitative analysis has become an increasingly important area within professional sports. However, the manual process of collecting data on relevant match events like passes, goals and tacklings comes with considerable costs and limited consistency across providers, affecting both research and practice. In football, while automatic detection of events from positional data of the players and the ball could alleviate these issues, it is not entirely clear what accuracy current state-of-the-art methods realistically achieve because there is a lack of high-quality validations on realistic and diverse data sets. This paper adds context to existing research by validating a two-step rule-based pass and shot detection algorithm on four different data sets using a comprehensive validation routine that accounts for the temporal, hierarchical and imbalanced nature of the task. Our evaluation shows that pass and shot detection performance is highly dependent on the specifics of the data set. In accordance with previous studies, we achieve F-scores of up to 0.92 for passes, but only when there is an inherent dependency between event and positional data. We find a significantly lower accuracy with F-scores of 0.71 for passes and 0.65 for shots if event and positional data are independent. This result, together with a critical evaluation of existing methodologies, suggests that the accuracy of current football event detection algorithms operating on positional data is currently overestimated. Further analysis reveals that the temporal extraction of passes and shots from positional data poses the main challenge for rule-based approaches. Our results further indicate that the classification of plays into shots and passes is a relatively straightforward task, achieving F-scores between 0.83 to 0.91 ro rule-based classifiers and up to 0.95 for machine learning classifiers. We show that there exist simple classifiers that accurately differentiate shots from passes in different data sets using a low number of human-understandable rules. Operating on basic spatial features, our classifiers provide a simple, objective event definition that can be used as a foundation for more reliable event-based match analysis. [ABSTRACT FROM AUTHOR]

The work investigates the relationship between the leg spread and hip joint flexibility during kicking action of highly skilled martial artists. Vector-based spreading angles (VSAs), as a simplified way to assess kick execution patterns and movement ranges, are proposed. The first VSA measures the angle between the two femur vectors (i.e., upper leg spread), whereas the second describes the full-leg spread. The proposed measures were applied to 3D motion analysis performed on 33 participants at various skill levels who executed double side kicks and performed two static flexibility tests (hip joint flexion and abduction). Statistical analysis showed that the proposed parameters differentiate between skill levels. Both VSAs and VSA rate of change showed high Pearson correlation to the quality of execution (the average of 10 subjective kickboxing experts' evaluation scores) at critical instants of the kick execution , i.e., during the first leg elevation and kick (angles: ρ > 0.8; p < 0.001). In addition, they significantly correlated to maximum static hip abduction at any instant (ρ = 0.37–0.69; p < 0.05). The work established that both static and dynamic joint flexibility contribute to high-performance levels and could be used for initial selection and assessment of training effectiveness. [ABSTRACT FROM AUTHOR]

Gait asymmetry and skeletal deformities are common in many children with cerebral palsy (CP). Changes of the hip joint loading, i.e. hip joint contact force (HJCF), can lead to pathological femoral growth. A child's gait pattern and femoral morphology affect HJCFs. The twofold aim of this study was to (1) evaluate if the asymmetry in HJCFs is higher in children with CP compared to typically developing (TD) children and (2) identify if the bony morphology or the subject-specific gait pattern is the main contributor to asymmetric HJCFs. Magnetic resonance images (MRI) and three-dimensional gait analysis data of twelve children with CP and fifteen TD children were used to create subject-specific musculoskeletal models and calculate HJCF using OpenSim. Root-mean-square-differences between left and right HJCF magnitude and orientation were computed and compared between participant groups (CP versus TD). Additionally, the influence on HJCF asymmetries solely due to the femoral morphology and solely due to the gait pattern was quantified. Our findings demonstrate that the gait pattern is the main contributor to asymmetric HJCFs in CP and TD children. Children with CP have higher HJCF asymmetries which is probably the result of larger asymmetries in their gait pattern compared to TD children. The gained insights from our study highlight that clinical interventions should focus on normalizing the gait pattern and therefore the hip joint loading to avoid the development of femoral deformities. [ABSTRACT FROM AUTHOR]

The correct estimation of gait events is essential for the interpretation and calculation of 3D gait analysis (3DGA) data. Depending on the severity of the underlying pathology and the availability of force plates, gait events can be set either manually by trained clinicians or detected by automated event detection algorithms. The downside of manually estimated events is the tedious and time-intensive work which leads to subjective assessments. For automated event detection algorithms, the drawback is, that there is no standardized method available. Algorithms show varying robustness and accuracy on different pathologies and are often dependent on setup or pathology-specific thresholds. In this paper, we aim at closing this gap by introducing a novel deep learning-based gait event detection algorithm called IntellEvent, which shows to be accurate and robust across multiple pathologies. For this study, we utilized a retrospective clinical 3DGA dataset of 1211 patients with four different pathologies (malrotation deformities of the lower limbs, club foot, infantile cerebral palsy (ICP), and ICP with only drop foot characteristics) and 61 healthy controls. We propose a recurrent neural network architecture based on long-short term memory (LSTM) and trained it with 3D position and velocity information to predict initial contact (IC) and foot off (FO) events. We compared IntellEvent to a state-of-the-art heuristic approach and a machine learning method called DeepEvent. IntellEvent outperforms both methods and detects IC events on average within 5.4 ms and FO events within 11.3 ms with a detection rate of ≥ 99% and ≥ 95%, respectively. Our investigation on generalizability across laboratories suggests that models trained on data from a different laboratory need to be applied with care due to setup variations or differences in capturing frequencies. [ABSTRACT FROM AUTHOR]

To identify the relationship between load and the number of repetitions performed to momentary failure in the pin press exercise, the present study compared different statistical model types and structures using a Bayesian approach. Thirty resistance-trained men and women were tested on two separate occasions. During the first visit, participants underwent assessment of their one-repetition maximum (1-RM) in the pin press exercise. On the second visit, they performed sets to momentary failure at 90%, 80% and 70% of their 1-RM in a fixed order during a single session. The relationship between relative load and repetitions performed to failure was fitted using linear regression, exponential regression and the critical load model. Each model was fitted according to the Bayesian framework in two ways: using an across-subjects pooled data structure and using a multilevel structure. Models were compared based on the variance explained (R2) and leave-one-out cross-validation information criterion (LOOIC). Multilevel models, which incorporate higher-level commonalities into individual relationships, demonstrated a substantially better fit (R2: 0.97–0.98) and better predictive accuracy compared to generalised pooled-data models (R2: 0.89–0.93). The multilevel 2-parameter exponential regression emerged as the best representation of data in terms of model fit, predictive accuracy and model simplicity. The relationship between load and repetitions performed to failure follows an individually expressed exponential trend in the pin press exercise. To accurately predict the load that is associated with a certain repetition maximum, the relationship should therefore be modelled on a subject-specific level. [ABSTRACT FROM AUTHOR]

The aim of this study was to determine the differences in golf swing execution in terms of the parameters of the pelvis and thorax movement between the sexes in junior golfers and their relation to the golf club velocity. Elite female and male players (age: 15.4 ± 1.0 and 15.8 ± 1.7 years, respectively) performed 10 golf swings with a driver under laboratory conditions. Pelvis and thorax movement parameters and golf club velocities were measured using a three-dimensional motion capture system. Statistical parametric mapping analysis of pelvis–thorax coupling revealed a significant difference (p < 0.05) between boys and girls during backswing. Analysis of variance showed a significant effect of sex on the parameters of maximal pelvic rotation (F = 6.28, p = 0.02), X-factor (F = 5.41, p = 0.03), and golf club velocity (F = 31.98, p < 0.01). No significant relationship was found between pelvis and thorax movement parameters and golf club velocity in the girls. We found a significant negative relationship between the parameters of maximal thorax rotation and golf club velocity (r = −0.941, p < 0.01) and between X-Factor and golf club velocity (r = −0.847, p < 0.05) in the boys. We suggest that these negative relationships in males were caused by the influence of hormones during their maturation and biological development, where there is decreased flexibility (lower shoulders rotation and X-factor) and growth of muscle strength (higher club head velocity). [ABSTRACT FROM AUTHOR]

Conventional corrective insoles for flatfoot individuals traditionally utilise solid arch support to prevent the collapse of medial longitudinal arch. Such design restricts the foot arch compression and recoil in stance phase and increases the expanded energy during gait. In this study, a novel customised design insole was designed and manufactured using person's 3D foot scans. A novel elastic mesh pad was implemented in the mid-insole to replace the conventional solid arch support. The new insoles were tested in standard straight gait laboratory trials. The kinematic analysis showed that the novel insoles improved foot arch compression and recoil in stance phase with flatfooted individuals. Finally, the new insoles were provided to the participants to be habitually worn during a prolonged period of daily usage. The obtained gait analysis results and user feedback indicate strongly that the novel insoles provide improved comfort, static and dynamic balance, and arch support in stance phase. In summary, the new insoles show substantive potential in addressing the shortcomings of the widely used passive support ones while providing less restrictive and effective dynamic support. [ABSTRACT FROM AUTHOR]

Due to the chaotic nature of soccer, the predictive statistical models have become in a current challenge to decision-making based on scientific evidence. The aim of the present study was to systematically identify original studies that applied machine learning (ML) to soccer data, highlighting current possibilities in ML and future applications. A systematic review of PubMed, SPORTDiscus, and FECYT (Web of Sciences, CCC, DIIDW, KJD, MEDLINE, RSCI, and SCIELO) was performed according to the Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) guidelines. From the 145 studies initially identified, 32 were fully reviewed, and their outcome measures were extracted and analyzed. In summary, all articles were clustered into three groups: injury (n = 7); performance (n = 21), which was classified in match/league outcomes forecasting, physical/physiological forecasting, and technical/tactical forecasting; and the last group was about talent forecasting (n = 5). The development of technology, and subsequently the large amount of data available, has become ML in an important strategy to help team staff members in decision-making predicting dose-response relationship reducing the chaotic nature of this team sport. However, since ML models depend upon the amount of dataset, further studies should analyze the amount of data input needed make to a relevant predictive attempt which makes accurate predicting available. [ABSTRACT FROM AUTHOR]

The use of small, interconnected and intelligent tools within the broad framework of pervasive computing for analysis and assessments in sport and physical activity is not a trend in itself but defines a way for information to be handled, processed and utilised: everywhere, at any time. The demand for objective data to support decision making prompted the adoption of wearables that evolve to fulfil the aims of assessing athletes and practitioners as closely as possible with their performance environments. In the present paper, we mention and discuss the advancements in ubiquitous computing in sports and physical activity in the past 5 years. Thus, recent developments in wearable sensors, cloud computing and artificial intelligence tools have been the pillars for a major change in the ways sport-related analyses are performed. The focus of our analysis is wearable technology, computer vision solutions for markerless tracking and their major contribution to the process of acquiring more representative data from uninhibited actions in realistic ecological conditions. We selected relevant literature on the applications of such approaches in various areas of sports and physical activity while outlining some limitations of the present-day data acquisition and data processing practices and the resulting sensors' functionalities, as well as the limitations to the data-driven informed decision making in the current technological and scientific framework. Finally, we hypothesise that a continuous merger of measurement, processing and analysis will lead to the development of more reliable models utilising the advantages of open computing and unrestricted data access and allow for the development of personalised-medicine-type approaches to sport training and performance. [ABSTRACT FROM AUTHOR]

The aim of this study was to determine and analyze the differences between the players' internal (IL) and external load (EL) in different time zones (T1: 0–45 min, T2: 45–70 min, T3: 0–70 min, T4: 70–90 min, T5: 45–90 min, and T6: 0–90 min) in elite youth soccer matches (U17–19 age category). The monitored group comprised elite youth soccer players (n = 66; age = 17.5 ± 1.2 years; body height = 178.5 ± 8.7 cm; body mass = 70.4 ± 6.3 kg). Multivariate analysis of variances was used to compare the following variables: relative total distance covered (TDCrel), distance covered in different speed zones (Z1–Z6), high-metabolic load distance (HMLD), maximum running speed (Smax), number of acceleration (ACC) and deceleration (DCC) entries in different speed zones (Z1, Z2, Z3), and maximum heart rate (HRmax). Results revealed significant differences (p < 0.05) in the first 70 min (T3) compared to the last 20 min of the match (T4) in the following: TDCrel was higher, up to 6.6% (123.09 ± 9.48 vs. 115.03 ± 9.42 m.min−1); distance in Z5 (22.4%, 6.08 ± 1.82 vs. 4.72 ± 1.72 m.min−1); Z4 (18.6%, 20.15 ± 4.82 vs. 16.40 ± 3.48 m.min−1); Z3 (10.4%, 53.06 ± 47.52 m.min−1); and HMLD (16.1%, 34.86 ± 5.67 vs. 29.26 ± 5.11 m.min−1). We also found higher running performance in the first half (T1) than in the second half (T5) in the following parameters: TDCrel, Z5, Z4, ACCZ1, ACCZ2, and DCCZ1. With progressive time (in T4) we found a significant decrease in physical running performance, probably due to fatigue, which can lead to potential injury or losing in a match. The results of this study may provide helpful information in developing training strategies for coaches and in the set-up of plan for potential substitution of exhausted players mainly for the last 20 min of a match (T4). The present results are expressed as a relative value and should be compared with other study results with irregular timing zones. [ABSTRACT FROM AUTHOR]

In sports feedback systems, digital systems perform tasks such as capturing, analysing and representing data. These systems not only aim to provide athletes and coaches with insights into performances but also help athletes learn new tasks and control movements, for example, to prevent injuries. However, designing mobile feedback systems requires a high level of expertise from researchers and practitioners in many areas. As a solution to this problem, we present Direct Mobile Coaching (DMC) as a design paradigm and model for mobile feedback systems. Besides components for feedback provisioning, the model consists of components for data recording, storage and management. For the evaluation of the model, its features are compared against state-of-the-art frameworks. Furthermore, the capabilities are benchmarked using a review of the literature. We conclude that DMC is capable of modelling all 39 identified systems while other identified frameworks (MobileCoach, Garmin Connect IQ SDK, RADAR) could (at best) only model parts of them. The presented design paradigm/model is applicable for a wide range of mobile feedback systems and equips researchers and practitioners with a valuable tool. [ABSTRACT FROM AUTHOR]

Basketball leagues track basic statistics for many decades and the number of metrics expand quickly. However, the "pass that leads to an assist", which is frequently – according to the most successful coach Phil Jackson – the most important pass of the possession, remained mainly overlooked by experts and analysts alike. With the help of NBA's SportVU positional data we analyse the characteristics and effects of this event through more than 500 games. Results show that teams having more secondary assists create space in areas related to higher expected points, get more open and therefore obtain better quality shots. The number of secondary assists might turn out to be one of the best metrics to measure quality ball movement. [ABSTRACT FROM AUTHOR]

Running field tests are utilised to assess the athlete's fitness level with high specificity. However, in graded exercise tests the lack of speed control can result in an uneven pace, reducing reproducibility and accuracy. The purpose of this study was to develop feedback variants (FV) and investigate their effect on the athlete's ability to keep the pace constant. Forty-eight participants completed four trials of a Conconi test (randomised) over four paces (7.5 − 10 km·h−1). A smartphone app provided athletes with four FVs: Classic, Sound (verbal), Vibration, and Sound & Vibration. We found a significant effect of FV on adherence (defined as time within 0.3 km·h−1 of target speed): F(3,141) = 41.45, p <.001, η2 =.268. Adherence in Classic (M± SD) 39.51 ± 13.51% was significantly lower (p <.001) than in Vibration (53.24 ± 14.98%), Sound (60.34 ± 11.21%) and Sound & Vibration (59.17 ± 15.17%). The novel FV provided better adherence compared to the conventional method, with Sound and Sound & Vibration showing the highest adherence. Generally, the novel FVs have the advantage of being easily implemented and decreasing the required time for setup, data collection and processing, therefore proving useful in conducting field performance tests. [ABSTRACT FROM AUTHOR]

A technique in Martial Arts is often indicated by an athlete's preceding actions, which potentially enables an opponent to detect or counter it. Prior to kicks, fighters attain balance and ease leg elevation by re-distributing their weight (WRT) or ease following sequences by elevating COM (CET). The aim of this study was to define such movements and to compare them by their duration and motion amplitude. The kick preceding actions and regular fighting movements of a kicking combination performed by 44 fighters across different skill levels (advanced to world leading) were compared. The initiation action start was determined by the moment during the preparatory phase, when a joint angle significantly exceeds or subceeds a specific threshold (3Sd). Descriptive statistics and qualitative analysis were used to summarise movement types, durations, and amplitudes. T- and Wilcoxon tests were performed to analyse differences in movement start and amplitude between WRT and CET, while Friedman- and Dunn-Bonferroni tests were used between body segments. Results showed that WRTs start earlier, happen more often, and are more subtle than CETs. Furthermore, proximal segments tend to move earlier [Sequence: COM; torso; hips> arms; knees] and with less movement amplitude [Sequence: arms > hips; knees > torso]. [ABSTRACT FROM AUTHOR]

The study was designed to investigate the validity of different technologies used to determine movement velocity in resistance training. Twenty-four experienced powerlifters (18 male and 6 female; age, 25.1 ± 5.1 years) completed a progressive loading test in the squat, bench press, and conventional deadlift until reaching their 1 repetition maximum. Peak and mean velocity were simultaneously recorded with 4 field-based systems: GymAware (GA), FitroDyne (FD), PUSH (PU), and Beast Sensor (BS). 3D motion capturing was used to calculate specific gold standard trajectory references for each device. GA provided the most accurate output across exercises (r = 0.99-1, ES 5 -0.05 to 0.1). FD showed similar results for peak velocity (r = 1, standardized mean bias [ES] = -0.1 to -0.02) but considerably less validity for mean velocity (r = 0.92-0.95, ES = -0.57 to -0.29). Reasonably valid to highly valid output was provided by PU in all exercises (r = 0.91-0.97, ES = -0.5 to 0.28) and by BS in the bench press and for mean velocity in the squat (r 5 0.87-0.96, ES 5 -0.5 to -0.06). However, BS did not reach the thresholds for reasonable validity in the deadlift and for peak velocity in the squat, mostly due to high standardized mean bias (ES 5 -0.78 to -0.63). In conclusion, different technologies should not be used interchangeably. Practitioners who require negligible measurement error in their assessment of movement velocity are advised to use linear position transducers over inertial sensors. [ABSTRACT FROM AUTHOR]

Background: Musculoskeletal simulations are widely used in the research community. The locations of surface markers are mostly used to scale a generic model to the participant's anthropometry. Marker-based scaling approaches include errors due to inaccuracies in marker placements.Research Question: How do scaling errors of the thigh and shank segments influence simulation results?Methods: Motion capture data and magnetic resonance images from a child with cerebral palsy and a typically developing child were used to create a subject-specific reference model for each child. These reference models were modified to mimic scaling errors due to inaccurately placed lateral epicondyle markers, which are frequently used to scale the thigh and shank segments. The thigh length was altered in 1 % steps from the original length and the shank length was accordingly adjusted to keep the total leg length constant. Thirty additional models were created, which included models with an altered thigh length of ±15 %. Subsequently, musculoskeletal simulations with OpenSim were performed with all models. Joint kinematics, joint kinetics, muscle forces and joint contact forces (JCF) were compared between the reference and altered models.Results: The investigated scaling error influenced joint kinematics and joint kinetics by up to 9.4° (hip flexion angle) and 0.15 Nm/kg (knee flexion moment), respectively. Maximum muscle and JCF differences of 46 % (medial gastrocnemius) and 72 % (hip JCF) bodyweight, respectively, were observed between the reference and altered models. Scaling errors mainly changed the magnitude but not the shape of most analyzed parameters. The influence of scaling errors on simulation results were similar in both participants.Significance: Scaling errors of the thigh segment influence simulation results at all joints due to the global optimization approach used in musculoskeletal simulations. Our findings can be used to estimate potential errors due to marker-based scaling approaches in previous and future studies. [ABSTRACT FROM AUTHOR]

This study investigated the activity profile during small-sided games (SSG) in elite youth soccer players. Internal load (IL) including heart rate (HR) and external load (EL) such as distance covered in different speed-zones (SZ) were collected from forty-eight players of three different teams (U15, U16, U18). The investigation included a total of eighteen 5vs.5 SSGs, each consisting of four 2-minute bouts on a 40x32m pitch during spring season. Total group results (n = 48) showed a reduction in total-distance (p = 0.001; ηp2 = 0.12), high-intensity-running (p = 0.009; ηp2 = 0.09), and low-intensity-running distance (p = 0.028; ηp2 = 0.07) between bouts. Similarly, a reduction in the number of both acceleration-low (p = 0.001; ηp2 = 0.12) and deceleration-high (p = 0.003; ηp2 = 0.11) values was observed. Additionally, time spent in HR-zones 3 and 4 (p≤0.007; ηp2 ≥ 0.10), increased, with a reduction in HR-zone 1 (p = 0.000, ηp2 = 0.25). Age group comparison showed less distance covered in SZ 1 (p≤0.000; ηp2 = 0.56) and greater deceleration-high values (p≤0.038; ηp2 = 0.32) in U15 players compared to other age groups. Further, U15 showed lower values in low-intensity-running compared to U18 (p = 0.038; ηp2 = 0.22). No age-related differences were found for IL and repeated sprint ability (RSA) values. The higher EL in younger age groups should be taken into account when implementing soccer specific SSGs. In addition, HRmean values between 80–85% of HRmax and RSA numbers, which are similar to match-play data, indicate SSGs as an effective training tool to prepare youth soccer athletes for the demands of competition. [ABSTRACT FROM AUTHOR]

In everyday muscle action or exercises, a stretch-shortening cycle (SSC) is performed under different levels of intensity. Thereby, compared to a pure shortening contraction, the shortening phase in a SSC shows increased force, work, and power. One mechanism to explain this performance enhancement in the SSC shortening phase is, besides others, referred to the phenomenon of stretch-induced increase in muscle force (known as residual force enhancement; rFE). It is unclear to what extent the intensity of muscle action influences the contribution of rFE to the SSC performance enhancement. Therefore, we examined the knee torque, knee kinematics, m. vastus lateralis fascicle length, and pennation angle changes of 30 healthy adults during isometric, shortening (CON) and stretch-shortening (SSC) conditions of the quadriceps femoris. We conducted maximal voluntary contractions (MVC) and submaximal electrically stimulated contractions at 20%, 35%, and 50% of MVC. Isometric trials were performed at 20° knee flexion (straight leg: 0°), and dynamic trials followed dynamometer-driven ramp profiles of 80°–20° (CON) and 20°–80°–20° (SSC), at an angular velocity set to 60°/s. Joint mechanical work during shortening was significantly (p < 0.05) enhanced by up to 21% for all SSC conditions compared to pure CON contractions at the same intensity. Regarding the steady-state torque after the dynamic phase, we found significant torque depression for all submaximal SSCs compared to the isometric reference contractions. There was no difference in the steady-state torque after the shortening phases between CON and SSC conditions at all submaximal intensities, indicating no stretch-induced rFE that persisted throughout the shortening. In contrast, during MVC efforts, the steady-state torque after SSC was significantly less depressed compared to the steady-state torque after the CON condition (p = 0.034), without significant differences in the m. vastus lateralis fascicle length and pennation angle. From these results, we concluded that the contribution of the potential enhancing factors in SSCs of the m. quadriceps femoris is dependent on the contraction intensity and the type of activation. [ABSTRACT FROM AUTHOR]