INTRODUCTION MEMS sensors (IMU`s) are widely available nowadays and tend to be used more often in swimming in the past years (Guignard, Rouard, Chollet, & Seifert, 2017). These sensors have very good measurement capabilities today, but the automatic analysis of the gathered data has not yet been implemented. Our objective is to develop and validate an automatic analysis which can provide the swimmers/coaches with nearly immediate feedback on a smartphone/tablet. METHODS A group of x swimmers (18-25 years of age) with different levels of experience were asked to swim two 50m laps at lower (1,500m pace) as well as higher (400m pace) effort levels in an temperature controlled 50m indoor pool. All trials were recorded with a 3-axis accelerometer. In each lap the participants were asked to breathe the first 25m to the right and the second 25m to the left side. The data were process in an automatic way as described by (A. Stamm, 2021). RESULTS For each lap, the following metrics were measured for the first and second 25m respectively: left and right arm distance per stroke; left and right average distance per stroke; left and right average velocity; minimum and maximum velocity for each arm; velocity pattern for left and right arm, left and right arm timings. Based on the recorded metrics the analysis was performed considering the breathing side and effectiveness of the strokes. Results have been presented as figures to visualise the findings to coaches and athletes. DISCUSSION The initial hypothesis shared among many coaches was that the strokes on the breathing side are longer and more powerful. However, the outcome of this research showed that this is only valid for around 60% of the participants. Other participants showed either shorter strokes, less powerful strokes, or even no influence on their stroke timing nor distance per stroke on their breathing side.
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