Dadashi, FarzinMillet, GregoireAminian, Kamiar2014-03-032014-03-032014-03-03201510.1016/j.pmcj.2014.03.001https://infoscience.epfl.ch/handle/20.500.14299/101264WOS:000353830400003An ubiquitous assessment of swimming velocity (main metric of the performance) is essential for the coach to provide a tailored feedback to the trainee. We present a probabilistic framework for the data-driven estimation of the swimming velocity at every cycle using a low-cost wearable inertial measurement unit (IMU). The statistical validation of the method on 15 swimmers shows that an average relative error of 0.1±9.6 % and high correlation with the tethered reference system (rX,Y = 0.91) is achievable. Besides, a simple tool to analyze the influence of sacrum kinematics on the performance is provided.Bayesian learningbreaststrokeperformancepervasive velocity estimationwearable IMUtext::journal::journal article::research article