Improve and Accurate Data Acquisition for Estimation Orientation using Inertial Measurement Units Sensor

Abstract

This paper presents an improved, accurate data acquisition from an Inertial Measurement Units sensor. The system includes Inertial Measurement Units Chips included on the board are: gyroscope, accelerometer and compass can be mounted on the human body to obtain information on the human arm movement. Thus, in this paper, Accelerometer and gyroscope data were fused using a context enhanced extended Kalman filter, it was developed to capture accurate data using Arduino. The filter is designed based on motion in order to adjust Kalman filter parameters. In addition, an automated approach is introduced to estimate the variance of the noise of the sensors during the operation. Considering motion context and automatic noise detection, the robustness of monitoring is enhanced against errors related to motion context i.e., high acceleration and long term motions. The proposed method is compared with the conventional method using experiments. It is found that the proposed model method reduces the accumulative orientation estimation errors and is useful for virtual reality system.