Inertial Sensor Error Reduction through Calibration and Sensor Fusion

This paper presents the comparison between cooperative and local Kalman Filters (KF) for estimating the absolute segment angle, under two calibration conditions. A simplified calibration, that can be replicated in most laboratories; and a complex calibration, similar to that applied by commercial vendors. The cooperative filters use information from either all inertial sensors attached to the body, Matricial KF; or use information from the inertial sensors and the potentiometers of an exoskeleton, Markovian KF. A one minute walking trial of a subject walking with a 6-DoF exoskeleton was used to assess the absolute segment angle of the trunk, thigh, shank, and foot. The results indicate that regardless of the segment and filter applied, the more complex calibration always results in a significantly better performance compared to the simplified calibration. The interaction between filter and calibration suggests that when the quality of the calibration is unknown the Markovian KF is recommended. Applying the complex calibration, the Matricial and Markovian KF perform similarly, with average RMSE below 1.22 degrees. Cooperative KFs perform better or at least equally good as Local KF, we therefore recommend to use cooperative KFs instead of local KFs for control or analysis of walking.We acknowledge support by the CSIC Open Access Publication Initiative through its Unit of Information Resources for Research (URICI).This work was supported by the HYPER project of the CONSOLIDER-INGENIO 2010 program of Spain, under grant CSD2009-00067; Fundação de Apoio à Pesquisa do Estado de São Paulo (FAPESP), under grant 2012/05552-9; The BIOMOT project within the Seventh Framework Programme for Research of the European Commission (611695); and by a grant from the Flemish agency for Innovation by Science and Technology (MIRAD, IWT-SBO 120057) We also thank Technaid S.L. for the use of the calibration equipment. We furthermore like to thank J.C. Moreno for his valuable contributions in writing this text