A Novel Technique for Gait Analysis Using Two Waist Mounted Gyroscopes

Abstract

Analysis of the human gait is used in many applications such as medicine, sports, indoor localization, and person identification. Several research studies focus on the use of MEMS inertial sensors for gait analysis and have shown promising results. Step detection and step length estimation are two basic and important gait analysis tasks. Although researchers have proposed many methods for step detection, all of them rely on experimental thresholds selected based on a limited number of subjects and walking conditions. Also, most of these methods do not distinguish walking from other activities; they can only recognize motion state from an idle state. On the other hand, step length estimation methods used in the literature either need constant calibration for each user, rely on impractical sensor placement, or both. In this paper, the human walking bipedal nature is employed for gait analysis using two waist mounted MEMS gyroscopes. This setup allows the step detection and discrimination from other non-bipedal activities without the need for magnitude thresholds. The hip rotation angle in the sagittal plane is also calculated that allowed us to estimate the step length without needing for constants calibration. By mounting an accelerometer on the center of the back of the waist, an auto-calibration method for the Weinberg equation's constant is developed. This method also improves the accuracy of the Weinberg equation for step length estimation.