Tracking human walking using MARG sensors
Jenn, David C.
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This thesis addresses modeling and simulation of the human lower extremities in order to track walking motion and estimate walking distance. The lower extremities are modeled as an articulated object, which consists of rigid bars connected to each other by joints. This model is tested by using both synthetic and real data. The synthetic data is created based on the main principles of biomechanics. The real data is obtained from the MARG sensors and is processed by the Factored Quaternion algorithm. Next, it is implemented in a simulation program written in Matlab. The program utilizes a mathematical model that represents the human gait-cycle and is based on the theory of forward kinematics as well as on the theory of manipulator kinematics. The simulation program is able to track the motion of the limbs that represent the lower extremities and estimate the traveled distance. Extensive laboratory tests verified the validity of the configuration.
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