Tennis Timing Assessment by a Machine Learning-Based Acoustic Detection System: A Pilot Study
<b>Background/Objectives:</b> In tennis, timing plays a crucial factor as it influences the technique and effectiveness of strokes and, therefore, matches results. However, traditional technical evaluation methods rely on subjective observations or video motion-tracking technology, mainl...
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| Main Authors: | Lucio Caprioli, Amani Najlaoui, Francesca Campoli, Aatheethyaa Dhanasekaran, Saeid Edriss, Cristian Romagnoli, Andrea Zanela, Elvira Padua, Vincenzo Bonaiuto, Giuseppe Annino |
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| Format: | Article |
| Language: | English |
| Published: |
MDPI AG
2025-01-01
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| Series: | Journal of Functional Morphology and Kinesiology |
| Subjects: | |
| Online Access: | https://www.mdpi.com/2411-5142/10/1/47 |
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