Estimation Of Imu Orientation Using Linear Kalman Filter Based On Correntropy Criterion

Human motion is an important issue in various medical analyses. In this paper, the application of interest is estimating the orientation of the wrist in indoor and outdoor activities using low cost Inertial Measurement Sensor IMU. We present an orientation estimation using Kalman Filter based on Correntropy Criterion (KFCC). The proposed method uses only the acceleration data in the aim to reduce the computing load with accurate orientation estimation. Optical measurement system has been used to benchmark the performance of the proposed method. Moreover, the KFCC is evaluated in indoor and outdoor activities with static and dynamic motion conditions. The proposed method proves its efficiency and reliability against existing methods.