access icon free 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.

Inspec keywords: biomechanics; velocity measurement; inertial systems; motion estimation; correlation theory; measurement systems; motion measurement; least mean squares methods; measurement errors; estimation theory; regression analysis; Gaussian processes

Other keywords: regression analysis; sensor inherent error; pervasive swimming velocity estimation; RMS error; body worn IMU; inertial measurement unit; Gaussian process; biomechanical constraint; linear correlation

Subjects: Interpolation and function approximation (numerical analysis); Spatial variables measurement; Spatial variables measurement; Numerical approximation and analysis; Velocity, acceleration and rotation measurement; Other topics in statistics; Biomechanics, biorheology, biological fluid dynamics; Probability theory, stochastic processes, and statistics; Instrumentation and measurement systems; Velocity, acceleration and rotation measurement

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