This utility model reveals a wearable gesture-detection system for basketball dribbling that consists of a motion-sensing glove and a gesture-detection terminal. The gesture detection terminal comprises a Bluetooth signal receiver, the main Arduino controller, buttons, a power source, and a display screen. This technique provides a practical and valuable supplemental tool for basketball training and performance improvement by precisely capturing gesture movements during dribbling. Athletes can track and evaluate their dribbling motions in real time using the motion-sensing glove and terminal, leading to more accurate technique correction and progress. Basketball players will have improved training and performance opportunities thanks to this wearable, which will actively advance the sport.

Shenghe Wu. Wearable Basketball Dribbling Gesture Detection Method. The Frontiers of Society, Science and Technology (2023) Vol. 5, Issue 15: 1-5. https://doi.org/10.25236/FSST.2023.051501.

[1] Hoelzemann, A., Romero, J. L., Bock, M., Laerhoven, K. V., & Lv, Q. (2023). Hang-Time HAR: A Benchmark Dataset for Basketball Activity Recognition Using Wrist-Worn Inertial Sensors. Sensors, 23(13), 5879.

[2] Trigueiros, P., Ribeiro, F., & Reis, L. P. (2012). A comparison of machine learning algorithms applied to hand gesture recognition. In 7th Iberian conference on information systems and technologies (CISTI 2012) (pp. 1-6). IEEE.

[3] Gundersen, K., Bruusgaard, J., Egner, I., Eftestøl, E., & Bengtsen, M. (2018). Muscle memory: virtues of your youth? The Journal of Physiology, 596. doi:10.1113/jp276354.

[4] Pernigoni, M., Ferioli, D., Butautas, R., La Torre, A., & Conte, D. (2021). Assessing the External Load Associated With High-Intensity Activities Recorded During Official Basketball Games. Frontiers in psychology, 12, 668194. https://doi.org/10.3389/fpsyg.2021.668194