Suchergebnisse - Data

Zoppirolli, C., Fornasiero, A., Spörri, J., Losnegard, T., Elfmark, O. A., Sandbakk, Ø., Holmberg, H.-C. “… However, the scientific literature remains unevenly distributed, with well-established knowledge in cross-country skiing, biathlon, and alpine skiing, and limited data in disciplines such as ski mountaineering, freestyle skiing, snowboarding, ski jumping, and Nordic combined.  …”

Fortier, A., Violain, M., Brunet, E., Clanet, C. “… The formulation combines (i) a Hill-type linear torque-cadence relationship fitted to instrumented-crank data, (ii) an energy balance that accounts for aerodynamic and rolling losses, and (iii) the measured track slope.  …”

Bertschy, M., Rodrigo-Carranza, V., Wilkie, E. W. C., Healey, L. A., Noble, J., Albert, W. J., Hoogkamer, W. “… Group-level results were consistent across days, but our data indicates that at least 2 separate sessions are needed to evaluate individual responses.  …”

Braun, L., Mai, P., Hipper, M., Denis, Y., Helwig, J., Anedda, B., Utku, B., Gehring, D., Willwacher, S. “… Methods Thirty recreational runners (15 males and 15 females) ran at a constant speed of 2.5 m/s at 5 systematically varied trunk lean conditions on a force-instrumented treadmill while kinematic and kinetic data were captured. Results A change in trunk lean angle from -2° (extension) to 28° (flexion) resulted in a systematic increase in stance phase angular impulse, cumulative impulse, and peak moment at the hip joint in the sagittal and transversal plane.  …”

Kim, J.-H., Kim, J., Kang, H., Youn, B.-Y. Schlagworte: “… data input …”

Bourdillon, N., Millet, G. P. “… Heart rate variability (HRV) is most often used as a standalone, without integration of complementary data. Yet these data are at our fingertips, and a revolution might be just around the corner.  …”

McDonald, M., Baker, J. S., Gu, Y., Ugbolue, U. C. “… Of these, 21 studies were included in this systematic review, each of which conducted a biomechanical analysis of the handstand. Data from the 21 articles were extracted to conduct a biomechanical analysis of the handstand.  …”

Ramírez-Pérez, L., Su, E. Y.-S., Cuesta-Vargas, A. I., Kerr, G. K. “… Moreover, four prediction models were developed based on the use of force plate data to estimate kinematics concerning humerus acceleration (p < 0.001).  …”

Dobra, V.-A., Dobra, I.-M., Folea, S. “… With minimal hardware modifications, the system implements gesture classification using Dynamic Time Warping (DTW) to distinguish between left and right paddle strokes. The collected data, including stroke type, count, and motion similarity, are transmitted in real time to a local interface for visualization.  …”

Lin, F., Huang, J., Chen, Z., Zhu, K., Feng, C. “… To bridge this gap, we introduce Trampoline-AQA, a novel dataset comprising 206 video clips from major competitions (2018-2024), featuring dual-modality (RGB and optical flow) data and rich annotations. Leveraging this dataset, we propose a framework comprising a Temporal Feature Enhancer (TFE) and a forward-looking causal cross-modal attention (FCCA) module, which improves action quality assessment by delivering more accurate and robust scoring for long-duration, high-speed routines, particularly under motion ambiguities.  …”

Maggiolo, J. F., Reina, R., Moya-Ramón, M., Peña-González, I. “… A total of 80 players (FT1: n = 22; FT2: n = 48; FT3: n = 10) completed sprinting, change of direction, and dribbling tests. In-match data from 74 players were collected across 56 official matches.  …”

Yan, X., Yang, J., Dai, J., Tao, K. “… Fifty badminton players (25 elite, 25 enthusiasts) performed treadmill running, cycling, rope skipping, and stair walking. Data were collected using accelerometers (waist, wrists, ankles), a heart rate monitor, and indirect calorimetry (criterion EE).  …”

Thibault, G., Dixon, P. C., Pearsall, D. J. “… Moreover, the effect of preprocessing steps (separating into running cycles and amplitude normalization) and two different data splitting protocols (leave-n-subject-out and subject-dependent split) was evaluated.  …”

Sánchez-Moreno, J., Moreno-Salinas, D., Álvarez-Ortiz, J. C. “… Photogrammetry applied to sports provides precise data on athlete positions and time instants, especially with digital motion capture systems.  …”

Ibáñez, S. J., Rico-González, M., Gómez-Carmona, C. D., Pino-Ortega, J. “… What are the implications of the main findings? a) LPS and MEMS data, combined with PCA, enable basketball teams to identify the most important workload parameters and specific profiles based on contextual factors. b) Findings support individualized training prescriptions and injury prevention by understanding the dynamic nature of basketball demands during competition.  …”

Zabala, M. “… The Cycling 3.0 paradigm can amplify the benefits of 2.0, provided that its algorithms, data systems, and governance frameworks can respect the humanistic and ethical foundations that rescued cycling from its 1.0 crises. …”

Genç, A., Aydin, G. R., Kasap, M., Özkan, A., Rakhymzhanov, A., Gürcan, H. H., Güllü, S., Demirhan, B. “… In addition, qualitative data analysis was performed to explore expert evaluations in depth, employing both content analysis and descriptive analysis techniques.  …”

Ma, J., Zou, F. “… To evaluate its contribution to winning probability, this study analyzes ATP men`s singles matches (2013-2024) and estimates the causal effects of four serve-related indicators: ace rate, first serve win rate, first serve in rate, and double fault rate.Results indicate that the ace rate shows a modest positive causal association rather than a uniformly negative one, while first serve win rate and first serve in rate exhibit context-dependent but statistically small impacts, and the double fault rate effects remain limited.These effects, although moderate in magnitude, remain statistically robust across multiple model specifications.The findings highlight the importance of adapting serve strategies across surfaces, ranking groups, and tournament levels.This study focuses exclusively on ATP men`s singles data, and future research should validate these causal relationships in WTA and mixed competitions to enhance generalizability. …”

Xiao, S., Liu, J. “… With an application and current research perspective centred around China and Asia, this article addresses the challenges remaining in these technologies including data integration, accessibility of technology, and development of intervention solutions tailored to individuals.  …”

Di Paolo, S., Viotto, M., Mendicino, M., Valastro, C., Grassi, A., Zaffagnini, S. “… Players performed pre-planned (AGTT) and unplanned football-specific cut maneuvers simulating defensive pressing (FS deceiving action). Kinematic data were collected via eight wearable inertial sensors (MTw Awinda, Movella) on trunk and lower limbs.  …”