Article: article from journal or magazin.
Gaussian process framework for pervasive estimation of swimming velocity with body-worn IMU
Presented is an accurate swimming velocity estimation method using an inertial measurement unit (IMU) by employing a simple biomechanical constraint of motion along with Gaussian process regression to deal with sensor inherent errors. Experimental validation shows a velocity RMS error of 9.0 cm/s and high linear correlation when compared with a commercial tethered reference system. The results confirm the practicality of the presented method to estimate swimming velocity using a single low-cost, body-worn IMU.
Gaussian processes, biomechanics, estimation theory, motion estimation, regression analysis, velocity measurement, Gaussian process regression, biomechanical motion constraint, commercial tethered reference system, high linear correlation, inertial measurement unit, pervasive estimation, sensor inherent errors, single low-cost body-worn IMU, swimming velocity estimation, velocity RMS error
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