Improving the accuracy of head rotation angle estimation using inertial micro-electro-mechanical sensors and adaptive digital filters

Abstract

The paper proposes a method to enhance the accuracy of head rotation angle estimation by integrating micro-inertial measurement sensors and digital filtering. The method is implemented under a stable gaze condition. Experimental results show that, compared to Mahony and Kalman filters, the proposed approach significantly improves the accuracy of head rotation angle estimation, with an RMS error of less than 0.1 degrees in horizontal plane rotation while maintaining real-time performance. These results are well-suited for applications in vestibulo-ocular reflex (VOR) signal recording for vestibular disorder diagnosis.