Abstract
Magnetic and inertial sensors have been widely used to estimate the orientation of human segments due to their low cost, compact size and light weight. However, the accuracy of the estimated orientation is easily affected by external factors, especially when the sensor is used in an environment with magnetic disturbances. In this paper, we propose an adaptive method to improve the accuracy of orientation estimations in the presence of magnetic disturbances. The method is based on existing gradient descent algorithms, and it is performed prior to sensor fusion algorithms. The proposed method includes stationary state detection and magnetic disturbance severity determination. The stationary state detection makes this method immune to magnetic disturbances in stationary state, while the magnetic disturbance severity determination helps to determine the credibility of magnetometer data under dynamic conditions, so as to mitigate the negative effect of the magnetic disturbances. The proposed method was validated through experiments performed on a customized three-axis instrumented gimbal with known orientations. The error of the proposed method and the original gradient descent algorithms were calculated and compared. Experimental results demonstrate that in stationary state, the proposed method is completely immune to magnetic disturbances, and in dynamic conditions, the error caused by magnetic disturbance is reduced by 51.2% compared with original MIMU gradient descent algorithm.
Highlights
Micro-electromechanical systems (MEMS)-based magnetic and inertial sensors have been widely used for human motion analysis due to their advantages of low cost, light weight and compact size
It can be seen that as the permanent magnet got close to the magnetic/inertial measurement unit (MIMU), strong magnetic disturbance was detected by the magnetometer
The Euler angles are estimated by the proposed method and the MIMU algorithm
Summary
Micro-electromechanical systems (MEMS)-based magnetic and inertial sensors have been widely used for human motion analysis due to their advantages of low cost, light weight and compact size.The applications include walking speed estimation [1], hand pose and kinematics estimation [2,3], knee-joint kinematics [4] and daily-life activity assessment [5]. Micro-electromechanical systems (MEMS)-based magnetic and inertial sensors have been widely used for human motion analysis due to their advantages of low cost, light weight and compact size. A typical magnetic/inertial measurement unit (MIMU) consists of a tri-axial accelerometer, a tri-axial gyroscope and a tri-axial magnetometer. Obtaining sensor orientation is unavoidable for most of the applications and accurate orientation estimation from the MIMU is critical. The attitude of a sensor can be calculated from the measured gravitational acceleration, and the heading can be calculated from the measured geomagnetic field. Both of them can be updated by the integration of angular velocity. Accelerometer can only determine the attitude accurately in stationary
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