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  1. 1

    Quantifying kinematic and coordinated movement patterns during pumping in windsurfing: the impact of footstraps use

    Chun, S., Park, J.
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  2. 2

    Can an inertial measurement unit be used as a field tool for acrobatic gymnasts training?

    Leite, I., Goethel, M., Gómez-Landero, L. A., Ávila-Carvalho, L., Vilas-Boas, J. P., Mochizuki, L., Conceição, F.
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  3. 3

    Current biomechanical methods and practices of physical training load monitoring in women`s artistic gymnastics: a scoping review

    Boylen, A. M., Campbell, R. A., Drinkwater, E. J., Bradshaw, E. J.
    Published in Journal of Sports Sciences (2025)
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  4. 4

    Test-retest reliability of customised inertial measurement units (IMUs) in evaluating skateboarding related manoeuvres

    Ab Rasid, A. M., Musa, A., Abdullah, M. A., Abdul Majeed, A. P. P., Mohd Razmaan, M. A., Abdullah, M. R., Abu Osman, N. A., Musa, R. M.
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  5. 5

    Artificial intelligence for objective assessment of acrobatic movements: Applying machine learning for identifying tumbling elements in cheer sports

    Wesely, S., Hofer, E., Curth, R., Paryani, S., Mills, N., Ueberschär, O., Westermayr, J.
    Published in Sensors (2025)
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  6. 6

    Validity of a wearable device for measuring vertical displacement and jump count in young artistic roller skating athletes

    Rebelo, A., Teixeira, D. S., Valente-dos-Santos, J., Lima, R. F.
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  7. 7

    Bringing biomechanics to ballet: a feasibility study using wearable technology during grand allegro

    Swords, T., McClelland, J., Middleton, K., Tessarin, B., Bryce, S., Mayes, S., Rio, E.
    Published in Sports Biomechanics (2024)
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  8. 8

    IMU airtime detection in snowboard halfpipe: U-net deep learning approach outperforms traditional threshold algorithms

    Gorges, T., Davidson, P., Boeschen, M., Hotho, A., Merz, C.
    Published in Sensors (2024)
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  9. 9

    IMU- & GNSS- basierte Analyse des Springreitens (IMU- & GNSS- based analysis of show jumping)

    Lang, G., Fercher, C., Fasel, B., Schmidt, M.
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  10. 10

    Smart Truck - Wie Tricks im Skateboarden durch Machine Learning klassifizieren kann (Smart Truck - How machine learning can classify tricks in skateboarding)

    Westenberger, E., Kreiner, J., Freitas, G., Fresen, L., Hollaus, B.
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  11. 11

    Inertial analysis of acceleration, deceleration, and angular speed in the technical of the front tucked somersault in female artistic gymnastics

    Izzo, R., Biancalana, V., Ubertini, S., Cejudo, A., Cruciani, A., Hosseini Varde'i, H., Crudelini, E.
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  12. 12

    A smart ski pole for skiing pattern recognition and quantification application

    Guo, Y., Ju, R., Li, K., Lan, Z., Niu, L., Hou, X., Qian, S., Chen, W., Liu, X., Li, G.
    Published in Sensors (2024)
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  13. 13

    IMU jerk grab detection in snowboard freestyle

    Friedl, F., Gorges, T., Merz, C.
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  14. 14

    Inter-limb coordination according to the use of footstrap during pumping in windsurfer: a single subject pilot study

    Chun, S., Park, J. C.
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  15. 15

    IMU acceleration data differs between the front and rear foot in snowboard halfpipe

    Gorges, T., Thelen, M., Merz, C.
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  16. 16

    Differences between parallel skiing and carving based on wearable sensor data and technique analysis algorithms

    Debertin, D., Wargel, A., Böhmer, M., Federolf, P.
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  17. 17

    Sensor-driven analysis of angle of attack in alpine skiing: a laboratory exploration

    Schütz, S., Thorwartl, C., Thorwartl, P., Stöggl, T., Holzer, H.
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  18. 18

    IMU data-driven and PCA-based approach to establish quantifiable and practically applicable measures for V2 technique elements in cross-country skiing

    Debertin, D., Haag, L., Federolf, P.
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  19. 19

    Analyzing micro parameters of diagonal stride in cross-country skiing using microsensors on snow

    Rindal, O. M. H., Gløersen, Ø., Tjønnås, J.
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  20. 20

    Comfortable measurement of ski-turn skill using inertial and plantar-pressure sensors

    Matsumura, S., Ohta, K., Kimura, T.
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