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Relationship between Sprint Capacity and Acceleration of Wrists in Wheelchair Basketball Players: Design and Reliability of a New Protocol.

Amelia Ferro-SánchezJavier Pérez-TejeroGuadalupe GarridoJorge Villacieros
Published in: International journal of environmental research and public health (2021)
The application of new technologies in wheelchair basketball (WB) is important for the advancement and improvement of athletic performance. The purposes of this study are twofold: (a) to develop a methodological design in order to assess WB players' performance, using wireless inertial measurement units (WIMU®) and a laser system (BioLaserSport® with computer vision), in a 20 m sprint test on court and (b) to assess bilateral symmetry as a performance indicator and for injury prevention purposes, the study of which in previous research is unknown. For both aims, the relation of the acceleration of the players' wrists to the speed achieved by the player in the wheelchair was explored. Ten elite WB players participated in an on-court 20 m sprint test during real training. BioLaserSport® with computer vision was used to assess the average velocity (Va) and maximum velocity (Vmax) of the WB players, and two WIMU® were used for the total acceleration (AcelT) of the players' wrists. A very high correlation was obtained in the assessment of the Va (0.97) and AcelT of both wrists (0.90 and 0.85). There was a significant relationship between the average AcelT of the dominant wrist and the Va on-court sprint velocity (p < 0.05). Two players did not show good wrist symmetry. In conclusion, a new methodological protocol was developed, making it possible to assess the bilateral symmetries in elite WB players in on-court real training and the relation between the acceleration of players' wrists and players' wheelchair speed. Coaches can use this protocol to assess performance or for injury prevention, as it shows very good reliability, with high ICC values.
Keyphrases
  • randomized controlled trial
  • high school
  • body composition
  • machine learning
  • deep learning
  • blood flow
  • resistance training
  • virtual reality
  • low cost