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  1. 1

    Evaluating fabric-based IMU and blue trident system against optical motion capture for lower body kinematics in badminton specific movement

    Tan, K., McErlain-Naylor, S. A.
    Published in 29th Annual Congress of the European College of Sport Science, 2-5 July 2024, Book of Abstracts (2024)
    “…sensor…”
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  2. 2

    The influence of the inertial motor unit location (lumbosacral vs. thoracic regions) on the external load registered during badminton matches

    García-López, J., Pino-Ortega, J., Fernández-Fernández, J., García-Tormo, J. V.
    Published in Sensors (2025)
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  3. 3

    Characterization of muscle activation and muscle synergism in the 'forward lunge' gait movement of badminton players using surface electromyography sensors

    Jiang, J., Li, H., Xiu, C.
    Published in Sensors (2025)
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  4. 4

    Mechanical load differences between practice and match play in badminton

    Smith, S., Jessop, D., Grimes, P., Baczala, O.
    Published in International Journal of Racket Sports Science (2023)
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  5. 5

    Inertial sensors containing device-based match characteristics that act as prognosticators of elite, male badminton players' performance levels

    Abdullahi, Y., Coetzee, B.
    Published in Proceedings of the 9th International Performance Analysis Workshop and Conference & 5th IACSS Conference. PACSS 2021. Advances in Intelligent Systems and Computing, vol 1426 (2022)
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  6. 6

    Quantifying hitting load in racket sports: A scoping review of key technologies

    Brich, Q., Casals, M., Crespo, M., Reid, M., Baiget, E.
    Published in International Journal of Sports Physiology and Performance (2024)
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  7. 7

    Badminton stroke identification using wireless inertial sensor and neural network

    Ooi, J. H., Gouwanda, D.
    Published in Proceedings of the Institution of Mechanical Engineers, Part P: Journal of Sports Engineering and Technology (2023)
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  8. 8

    Optimierung der Spielanalyse in den Einzeldisziplinen im Badminton (Optimization of the game analysis in the individual disciplines in badminton)

    Hammes, F., Link, D.
    Published in 20. Frühjahrsschule "Technologien im Leistungssport" 7./8. September 2022 in Leipzig (2022)
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  9. 9

    Badminton stroke classification based on accelerometer data: from individual to generalized models

    Peralta, D., Herbruggen, B. V., Fontaine, J., Debyser, W., Wieme, J., Poorter, E. D.
    Published in 2022 IEEE International Conference on Big Data (Big Data) (2022)
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  10. 10

    Reliability and validity of motion sensor and radar for measuring shuttlecock velocity in badminton

    Phomsoupha, M., Bonneau, F., Laffaye, G.
    Published in International Journal of Racket Sports Science (2022)
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  11. 11

    Evaluation of an electronic sensor-based agility test system for badminton players' development

    Marrylin Yalin, J. E., Haris, H., Hasnan, M. M. I. M., Saad, I.
    Published in IEEE Xplore (2022)
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  12. 12

    Differences in high trunk acceleration during single-leg landing after an overhead stroke between junior and adolescent badminton athletes

    Sasaki, S., Nagano, Y., Ichikawa, H.
    Published in Sports Biomechanics (2022)
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  13. 13

    Evaluation of a freely available sensor racket as a diagnostic and training tool in elite badminton

    Gawin, W., Herbstreit, A., Fries, U., Maiwald, C.
    Published in International Journal of Racket Sports Science (2022)
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  14. 14

    DeCoach: Deep learning-based coaching for badminton player assessment

    Ghosh, I., Ramamurthy, S. R., Chakma, A., Roy, N.
    Published in Pervasive and Mobile Computing (2022)
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  15. 15

    Monitoring movements with high trunk acceleration during badminton games: an approach combining a microsensor unit and video analysis

    Sasaki, S., Nagano, Y., Shimada, Y., Ichikawa, H.
    Published in British Journal of Sports Medicine (2021)
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  16. 16

    Badminton activity recognition using accelerometer data

    Steels, T., Van Herbruggen, B., Fontaine, J., De Pessemier, T., Plets, D., De Poorter, E.
    Published in Sensors (2020)
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  17. 17

    Automatic badminton action recognition using CNN with adaptive feature extraction on sensor data

    Wang, Y., Fang, W., Ma, J., Li, X., Zhong, A.
    Published in Intelligent computing theories and application (2019)
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  18. 18

    Accelerometer can accurately measure training load in badminton

    Lin, Y.-C., Liu, T.-H., Shiang, T.-Y.
    Published in 6th World Congress of Racket Sport Science (2018)
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  19. 19

    Characterization of the fine hand movement in badminton by a smart glove

    Song, X., Peng, Y., Hu, B., Liu, W.
    Published in Instrumentation Science & Technology (2020)
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  20. 20

    Quantitative analysis of hand movement in badminton

    Jacob, A., Zakaria, W. N. W., Tomari, M. R. B. M.
    Published in Advanced Computer and Communication Engineering Technology. Lecture Notes in Electrical Engineering (2016)
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