A Non-Restricted Measuring System for Human Step Length Estimation

In this paper, a non-restricted human step length measuring system has been derived by deploying the wearable inertial measurement sensor on subjects' foot. The measuring errors caused by the unwanted data noise, sensor drift as well as uncompensated gravity are discussed in detail. Based on the error model analysis, an efficient MARG orientation estimation method and the LRT zero-velocity update strategy have been utilized to mitigate this error induced effect. Subsequently, the procedure of estimating the step length of human ambulation is described, and the experimental assessment with subjects has also been conducted for verifying the robustness and the practicability of the proposed method. The experiment result has been statistically analyzed and shows the promising future to patients' gait clinical evaluation, human-oriented robot control as well as self-contained human movement tracking