A position tracking system using MARG sensors
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The objective of this thesis was to further the development of a personal position tracking system using MARG sensors. This work advanced the method by which distance and heading were calculated of an individual wearing one MARG sensor on his/her foot when moving about under normal walking conditions. Data was collected from the foot-mounted sensor while walking a straight-line path, a square path, and climbing stairs. The corresponding data from these activities was then used in a Matlab program to determine a computed position. The Matlab program employed a technique that reset the accelerometer error during the stance phase of the gait cycle. It also utilized a gait detection algorithm based on the magnitude of angular rate and the number of samples above/below threshold to establish the periods of the stance phase and the swing phase. Experimental results from various testing scenarios showed that it is feasible to track position of a person.
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