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Gaussian process framework for pervasive estimation of swimming velocity with body-worn IMU

Gaussian process framework for pervasive estimation of swimming velocity with body-worn IMU

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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.

References

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      • C.E. Rasmussen , C. Williams . (2006) Gaussian processes for machine learning.
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http://iet.metastore.ingenta.com/content/journals/10.1049/el.2012.3684
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