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Heterogeneous data fusion for three-dimensional gait analysis using wearable MARG sensors

Gait analysis has become a research highlight. In this paper, we propose a computing method using wearable magnetic angular rate and gravity (MARG) sensor arrays with wireless network, which calculates absolute and relative orientation and position information of human foot motion during level walking and stair climbing process. Three-dimensional foot orientation and position were estimated by a Kalman-based sensor fusion algorithm and validated by ground truth provided by Vicon system. The repeatability of the alignment procedure and the measurement errors were evaluated on healthy subjects. Experimental results demonstrate that the proposed method has a good performance at both motion patterns. No significant drifts exist in the overall results presented in the paper. The measured and estimated information can be transmitted to remote server through internet. Moreover, this method could be applied to other cyclical activity monitoring.