Wearable and Implantable Body Sensor Networks, International Workshop on (2009)
June 3, 2009 to June 5, 2009
DOI Bookmark: http://doi.ieeecomputersociety.org/10.1109/BSN.2009.25
Advances in the miniaturisation of inertial sensors have allowed the design of compact wireless inertial orientation trackers. Such devices require data fusion algorithms to process sensor data into estimated orientations. This paper examines the problem of inertial sensor data fusion and compares two alternative methods for orientation estimation: complementary filtering and Kalman filtering. Experiments are presented to assess the performance and accuracy of the resulting filters. The complementary filter structure is demonstrated to require up to nine times less execution time, while maintaining better accuracy across different movement scenarios, than the Kalman filter structure.
Body sensor network, data fusion, orientation estimation, complementary filter, Kalman filter
A. Young, "Comparison of Orientation Filter Algorithms for Realtime Wireless Inertial Posture Tracking," 2009 Sixth International Workshop on Wearable & Implantable Body Sensor Networks Conference (BSN 2009)(BSN), Berkeley, CA, 2009, pp. 59-64.