Motion Based Acceleration Correction for Improved Sensor Orientation Estimates

Abstract

Inertial measurement units (IMUs) including accelerometers and gyroscopes are becoming very common and can be found in cell phones, fitness trackers, and other wearable devices. With the growth in wearable computing and body sensor networks, IMUs are also becoming more prevalent research environments for estimation and tracking of human motion. We demonstrate that the accelerometer angle estimate is inaccurate for typical motions and present a method using a kinematic model to correct the accelerometer angle estimate and improve overall orientation estimates using an extended Kalman filter (EKF). Our method improves upon the raw accelerometer orientation estimation method and a gyroscope based EKF method for sensor orientation during motion and at rest.