Improved extended Kalman fusion method for upper limb motion estimation with inertial sensors

With the rapid development of microsensors, the real-time, low-cost human motion tracking system using inertial sensors has become more and more popular. Because of the complicated indoor electromagnetic environment, magnetic disturbance has become one of the most challenging issues. This paper presents a portable real-time limb motion capture system based on extended kalman filter. In this system, a non-linear two step algorithm is used to calibrate the magnetometer. And an adaptive mechanism for weighting the measurements is introduced in the EKF to reduce the impact of the body motion and temporary magnetic disturbances. Simulation and experimental results have shown that the proposed algorithm obtains good performance in magnetically disturbed environment.