Gaussian process framework for pervasive estimation of swimming velocity with body-worn IMU
Data(s) |
2013
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Resumo |
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. |
Identificador |
http://serval.unil.ch/?id=serval:BIB_8EADE8D8C02E isbn:0013-5194 isiid:000318235200027 |
Idioma(s) |
en |
Fonte |
Electronics Letters, vol. 49, no. 1, pp. 44-46 |
Palavras-Chave | #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 |
Tipo |
info:eu-repo/semantics/article article |