Abstract
Human foot motion localization using inertial measurement unit (IMU) is a challenging problem due to IMU's drift and noise. This paper presents a localization algorithm, which can accurately estimate the position, velocity and attitude of human foot motion based on IMU measurements. The proposed algorithm works efficiently in a real-time and dynamic speed manner. A dynamic Gait Phase Detection (GPD) method is utilized to produce a high accuracy of human foot gait phase detection in dynamic speeds. We then integrate the GDP with an Inertial Navigation System (INS), a Zero Velocity Update (ZVU) and an Extended Kalman Filter (EKF) in a realtime manner to handle the IMU drift problem as well as the noise. Finally, the proposed algorithm is validated and compared with other existing techniques.
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