Abstract
Inertial measurement units (IMU) are proven as efficient tools for swimming analysis by overcoming the limits of video-based systems application in aquatic environments. However, coaches still believe in the lack of a reliable and easy-to-use analysis system for swimming. To provide a broad view of swimmers' performance, this paper describes a new macro-micro analysis approach, comprehensive enough to cover a full training session, regardless of the swimming technique. Seventeen national level swimmers (5 females, 12 males, 19.6 ± 2.1 yrs) were equipped with six IMUs and asked to swim 4 × 50 m trials in each swimming technique (i.e., frontcrawl, breaststroke, butterfly, and backstroke) in a 25 m pool, in front of five 2-D cameras (four under water and one over water) for validation. The proposed approach detects swimming bouts, laps, and swimming technique in macro level and swimming phases in micro level on all sensor locations for comparison. Swimming phases are the phases swimmers pass from wall to wall (wall push-off, glide, strokes preparation, swimming, and turn) and micro analysis detects the beginning of each phase. For macro analysis, an overall accuracy range of 0.83–0.98, 0.80–1.00, and 0.83–0.99 were achieved, respectively, for swimming bouts detection, laps detection and swimming technique identification on selected sensor locations, the highest being achieved with sacrum. For micro analysis, we obtained the lowest error mean and standard deviation on sacrum for the beginning of wall-push off, glide and turn (−20 ± 89 ms, 4 ± 100 ms, 23 ± 97 ms, respectively), on shank for the beginning of strokes preparation (0 ± 88 ms) and on wrist for the beginning of swimming (−42 ± 72 ms). Comparing the swimming techniques, sacrum sensor achieves the smallest range of error mean and standard deviation during micro analysis. By using the same macro-micro approach across different swimming techniques, this study shows its efficiency to detect the main events and phases of a training session. Moreover, comparing the results of both macro and micro analyses, sacrum has achieved relatively higher amounts of accuracy and lower mean and standard deviation of error in all swimming techniques.
Highlights
As a highly competitive sport, swimming is one of the most popular events with world-class athletes, aiming to optimize their performance
In order to generate the results, the data of all laps are used for swimming technique identification and the phases are investigated from the beginning of each swimming bout up to the end of the turn to have all the phases completely
Right shank provides an estimation with lowest error mean and standard deviation for beginning of strokes preparation, while it is detected with negative or positive error mean on other sensor locations
Summary
As a highly competitive sport, swimming is one of the most popular events with world-class athletes, aiming to optimize their performance. To help coaches with these tasks, research community has studied swimming from various perspectives such as physiology (Pendergast et al, 1980; Lavoie and Montpetit, 1986; Zamparo et al, 2005), motor control (Seifert et al, 2011a; Morais et al, 2020), and biomechanics (Payton and Bartlett, 1995; Morais et al, 2012). All these aspects have their own significance, studies show the dominance of biomechanical factors over the other aspects (Figueiredo et al, 2013). To evaluate the swimmer’s performance, many studies focused on extracting specific parameters such as stroke rate (Siirtola et al, 2011; Beanland et al, 2014), distance per stroke (Bächlin et al, 2008), velocity (Wright and Stager, 2013; Dadashi et al, 2015), lower limbs actions rate (Fulton et al, 2009), or body coordination (Osborough et al, 2010; Silva et al, 2015)
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