Factors that provides effective competitive activity in inline speed skating

This study analyzed oculomotor behavior (fixations and saccades) in 19 competitive inline speed skaters (5 males, 14 females; aged 10-26years) from the Aragonese Skating Federation (Spain), comparing high-performance (N1) and intermediate (N2) groups. Participants completed optometric assessments and eye-tracking during 200 m time trials on a banked oval track using a Pupil Labs Neon device, with recordings taken before (PRE) and after (POST) intensive training. Results showed visual behavior remained stable overall, but curved segments (C1, C2) required significantly more fixations and saccades than straights. Skaters consistently focused on the inner track line during curves, suggesting an optimized visual strategy. High-performance skaters (N1) demonstrated greater efficiency with fewer fixations and saccades in key segments. After training, N1 skaters showed increased fixations in C1 (p=0.012) but reduced saccadic velocity (SS: PRE 8.00 deg/s vs. POST 6.82 deg/s; p=0.030) and length (S1: PRE 3077.41mm vs. POST 2564.71mm; p=0.035) on straights, consistent with fatigue. N1 exhibited different patterns of ocular abilities versus N2 pre- and port-training. Strong binocular coordination was observed (right-left eye correlations ≥ 0.85; p<0.001). Conclusions indicate that experience enhances visual efficiency, with elite skaters showing more focused gaze patterns. Training-induced fatigue may primarily affect straight segments, reducing saccade speed and length. The finish line served as a consistent visual reference point. These findings highlight the importance of sport-specific visual training and fatigue management in inline speed skating. Future research should address study limitations including small sample size and gender imbalance.

This study measured the peak force (PF) in cadet inline speed skaters (ISS) and verified the physical measures that determine athletes' performance on the Isometric Mid-Thigh Pull Test (IMTP) through a multivariate regression and discriminant canonical analysis. A total of 36 high-performance male (n= 18; age= 17.4± 1.21 years; body mass= 65.1± 6.18 kg; height= 168.6± 5.1 cm) and female (n= 18; age= 17.4± 1.23 years; body mass= 55.5± 4.4 kg; height= 158.6± 5.2 cm) athletes were measured two times (with a 3-day interval). All participants performed the IMTP and sit-and-reach (SR) tests, and an evaluator performed anthropometric circumference measurements on their thighs and calves. The main results indicated that males showed a higher PF on the test (m= 59.0± 3.9 N/kg vs. f= 50.4± 5.8 N/kg; p≤ 0.001) and retest (m= 59.1± 4.2 N/kg vs. f= 51.9± 6.6 N/kg; p≤ 0.001). In the first, thigh circumference (X2= 29.01, p≤ 0.001, R2= 0.74) had an overall 91.7% prediction. The second model included using the SR and thigh circumference (X2= 49.91, p≤ 0.001, R2= 1.0) showed an overall prediction of 100.0%. The thigh circumference matrix showed better predictive power for (coefficient= 7.158) male and female IMTP performance. In conclusion, despite the gender differences, the thigh circumference is a good predictor for PF in cadet ISS athletes.

The understanding of complex muscle coordination is an important goal in human movement science. There are numerous applications in medicine, sports, and robotics. The coordination process can be studied by observing complex, often cyclic movements, which are dynamically repeated in an almost identical manner. In this paper we demonstrate how interpretable temporal patterns can be discovered within raw EMG measurements collected from tests in professional In-Line Speed Skating. We show how the Temporal Data Mining Method, a general framework to discover knowledge in multivariate time series, can be used to extract such temporal patterns. This representation of complex muscle coordination opens up new possibilities to optimize, manipulate, or imitate the movements.KeywordsMultivariate Time SeriesCyclic MovementMovement CycleKnowledge Discovery ProcessTemporal RuleThese keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.

This study proposes and verifies a method to estimate the ground reaction force (GRF) direction from supporting-leg posture during speed skating. We hypothesized that GRF direction can be accurately estimated from supporting-leg posture. Two estimation methods were developed under the assumption that the reaction force acts perpendicular to the shoe sole. One method used the coordinates of the front and rear blade ends and the ankle joint center (Est1). In contrast, the other used the coordinates of the front and rear blade ends and the knee joint center (Est2). The magnitude of each GRF component was estimated by multiplying the resultant force measured by the force plates (FP) by the corresponding unit vector components calculated in Est1 and Est2. GRFs measured using FP were adopted as true values to verify the proposed methods. Sixteen experienced university speed skaters performed straight and curved inline speed skating trials, during which three-dimensional kinematic and FP data were recorded. The root mean square error (RMSE) between FP measurements and estimates from Est1 and Est2 was calculated for each force component. The largest observed error was approximately 10% of body weight. Across all skating motions and force components, Est2 consistently exhibited smaller RMSE values than Est1. Based on these results, Est2 was selected for further verification. For straight skating and the right leg during curve skating, bias values for all components were less than 8% of body weight. For the left leg during curve skating, larger biases were observed before and after the right blade contact; however, applying regression-based corrections substantially reduced these biases. Intraclass correlation coefficient analysis indicated agreement between true and estimated values for the X' and Z' components across all skating motions. For the Y' component, several time points showed no agreement with the true values. Nevertheless, because the Y' component magnitude was very small, its influence on calculations such as joint torque or joint power of the supporting leg was minimal. Overall, Est2 is suitable for these calculations.