Cristian Romagnoli ^1,2* Saeid Edriss ³ Lucio Caprioli ^3* Luca Ghelardini ⁴ Ida Cariati ⁵ Anas Alashram ⁶ Nunzio Lanotte ⁷ Paolo Boatto ⁷ Elvira Padua ² Vincenzo Bonaiuto ³ Giuseppe Annino ⁸

• ¹ Università telematica San Raffaele, Rome, Italy
• ² Department of Human Science and Promotion of Quality of Life, San Raffaele Telematic University, Rome, Lazio, Italy
• ³ Department of Industrial Engineering, University of Rome Tor Vergata, Rome, Lazio, Italy
• ⁴ Italian Canoe/Kayak Federation (FICK), Rome, Italy
• ⁵ Department of Systems Medicine, Faculty of Medicine and Surgery, University of Rome Tor Vergata, Rome, Lazio, Italy
• ⁶ Department of Physiotherapy, Faculty of Allied Medical Science, Middle East University, Amman 11831, Jordan, Amman, Jordan
• ⁷ APLAB, Roma, Italy, Rome, Italy
• ⁸ Human Performance Laboratory, Centre of Space Bio-Medicine, Department of Medicine Systems, University of Rome Tor Vergata, 00133 Rome, Italy, Rome, Italy

The K2 performance depends on different kinematic and kinetic variables. There is a lack of related studies in this area; however, the researchers have tried to explain these features to understand the best paddlers' position and how their synchronization affects performance. In this study, it has been used DAQ system composed of two instrumented paddles, an IMU and a GPS (“E-kayak system”) to investigate the paddle synchronization and the specific paddlers’ position in preferred and inverted configurations. In this study, ten sub-elite paddlers respectively participated and were divided into five crews. The test provides two trials on 500m performed in preferred and inverted seats. The synchronization analysis highlighted that the rear paddler contributes efficiently to the propulsion of the boat while performing 30-40ms earlier than the front paddler in the entry and exit phases. Despite the time results on 500m, there is no evidence of a dominant indication of the preferred or inverted position of the athletes, the results showed a significant correlation (p<0.05) between force front paddler (r=-0.88), stroke frequency of the crew (r= -0.66) and total force applied by the crew with the time on 500m and between stroke frequency and force front paddler (r=0.64). Based on these indications, only for those crews who completed the 500m test in the shortest time, the equation determining the time over 500m was calculated using multiple regression analysis, considering the stroke frequency and the force of the front and rear paddler. The data showed a good estimation with a CV% = 0.22, ICC = 0.99, and ES = -0.005. In conclusion, these findings can be a beneficial tool for assessing or monitoring the K2 crew performance in sub-elite paddlers.