Body sensor network-based strapdown orientation estimation: Application to human locomotion

摘要

In this contribution, inertial and magnetic sensors are considered for real-time strapdown orientation tracking of human limb or robotic segment orientation. By using body sensor network integrated triaxial gyrometer, accelerometer, and magnetometer measurements, two orientation estimation filters are presented and subsequently designed for bias insensitive tracking of human gait. Both filters use quaternions for rotation representation, where preprocessing accelerometer and magnetometer data is conducted with the quaternion based estimation algorithm (QUEST) as a reference filter input. This results in a significant reduction of the complexity and calculation cost on the body sensor network. QUEST-based preprocessed attitude data is used for the designed extended Kalman filter (EKF) and a new complementary sliding mode observer. EKF-QUEST and complementary sliding mode observer are designed and tested in simulations and subsequently validated with a reference motion tracking system in treadmill tests.