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This paper presents the development of a fusion strategy to integrate and calibrate signals from magnetometers, gyroscopes and accelerometers to implement a magnetic, angular rate and gravity (MARG) sensor system. The aim of such algorithms is to capture signals from the individual sensors and identify, compensate and reduce external and internal errors such as bias, scale factor and drifts, which highly depend on the noise levels. The necessary calibrations to ensure the reliability of captured data are also presented. The orientation data obtained by the proposed algorithm will be compared with a commercial motion capture system, which are currently being used by researchers in biomechanical analysis and in clinical motor rehabilitation studies.
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