Inertial Sensor Error Reduction through Calibration and Sensor Fusion

• Published in: Sensors (Basel, Switzerland) Vol. 16; no. 2; p. 235
• Main Authors: Lambrecht, Stefan, Nogueira, Samuel, Bortole, Magdo, Siqueira, Adriano, Terra, Marco, Rocon, Eduardo, Pons, José
• Format: Journal Article
• Language: English
• Published: Switzerland MDPI AG 17.02.2016; MDPI
• Subjects: Adult; Biomechanical Phenomena; biomechanics; Biosensing Techniques; Calibration; Confidence Intervals; exoskeleton; Humans; inertial sensor; Kalman Filter; Male; Models, Theoretical; motion analysis; Sensors; exoskeleton; Kalman Filter; biomechanics; inertial sensor; calibration; motion analysis
• ISSN: 1424-8220; 1424-8220
• DOI: 10.3390/s16020235

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.