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Sensors 2015, 15(10), 25919-25936; doi:10.3390/s151025919

Multi-Sensor Calibration of Low-Cost Magnetic, Angular Rate and Gravity Systems

Philips Chair for Medical Information Technology, RWTH Aachen University, Pauwelsstrasse 20, Aachen 52074, Germany
These authors contributed equally to this work.
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Author to whom correspondence should be addressed.
Academic Editor: Vittorio M. N. Passaro
Received: 17 August 2015 / Revised: 22 September 2015 / Accepted: 29 September 2015 / Published: 13 October 2015
(This article belongs to the Special Issue Sensor Systems for Motion Capture and Interpretation)
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Abstract

We present a new calibration procedure for low-cost nine degrees-of-freedom (9DOF) magnetic, angular rate and gravity (MARG) sensor systems, which relies on a calibration cube, a reference table and a body sensor network (BSN). The 9DOF MARG sensor is part of our recently-developed “Integrated Posture and Activity Network by Medit Aachen” (IPANEMA) BSN. The advantage of this new approach is the use of the calibration cube, which allows for easy integration of two sensor nodes of the IPANEMA BSN. One 9DOF MARG sensor node is thereby used for calibration; the second 9DOF MARG sensor node is used for reference measurements. A novel algorithm uses these measurements to further improve the performance of the calibration procedure by processing arbitrarily-executed motions. In addition, the calibration routine can be used in an alignment procedure to minimize errors in the orientation between the 9DOF MARG sensor system and a motion capture inertial reference system. A two-stage experimental study is conducted to underline the performance of our calibration procedure. In both stages of the proposed calibration procedure, the BSN data, as well as reference tracking data are recorded. In the first stage, the mean values of all sensor outputs are determined as the absolute measurement offset to minimize integration errors in the derived movement model of the corresponding body segment. The second stage deals with the dynamic characteristics of the measurement system where the dynamic deviation of the sensor output compared to a reference system is Sensors 2015, 15 25920 corrected. In practical validation experiments, this procedure showed promising results with a maximum RMS error of 3.89°. View Full-Text
Keywords: MEMS; calibration; magnetic; angular rate and gravity sensors; BSN MEMS; calibration; magnetic; angular rate and gravity sensors; BSN
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This is an open access article distributed under the Creative Commons Attribution License which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited. (CC BY 4.0).

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MDPI and ACS Style

Lüken, M.; Misgeld, B.J.; Rüschen, D.; Leonhardt, S. Multi-Sensor Calibration of Low-Cost Magnetic, Angular Rate and Gravity Systems. Sensors 2015, 15, 25919-25936.

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