FILTERING TECHNIQUES FOR ACCURATE IDENTIFICATION OF CLINICIAN HAND POSTURE

摘要

Inertial and magnetic sensors are commonly used to determine orientation as they do not rely on a line of sight. There are many different techniques to fuse inertial measurement unit (IMU) data and obtain useful rotational data . This study uses two separate data fusion techniques; a direction cosine matrix-based (DCM) technique and a quaternion-based Extended Kalman Filter (EKF) technique. These techniques were altered based on performance metrics to weight sensor data when certain sensors proved not as reliable as others. IMU sensors were tested on a hand mannequin and filters were developed using MATLAB software. Simulation results displayed a root-mean-squared error of less than .06° for each rotation angle. Experimental results maintained errors of less than 8° in each rotation angle.