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Multi-Sensor Calibration of Low-Cost Magnetic, Angular Rate and Gravity Systems
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 Postu...
Autores principales: | , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
MDPI
2015
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4634514/ https://www.ncbi.nlm.nih.gov/pubmed/26473873 http://dx.doi.org/10.3390/s151025919 |
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author | Lüken, Markus Misgeld, Berno J.E. Rüschen, Daniel Leonhardt, Steffen |
author_facet | Lüken, Markus Misgeld, Berno J.E. Rüschen, Daniel Leonhardt, Steffen |
author_sort | Lüken, Markus |
collection | PubMed |
description | 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 corrected. In practical validation experiments, this procedure showed promising results with a maximum RMS error of [Formula: see text]. |
format | Online Article Text |
id | pubmed-4634514 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2015 |
publisher | MDPI |
record_format | MEDLINE/PubMed |
spelling | pubmed-46345142015-11-23 Multi-Sensor Calibration of Low-Cost Magnetic, Angular Rate and Gravity Systems Lüken, Markus Misgeld, Berno J.E. Rüschen, Daniel Leonhardt, Steffen Sensors (Basel) Article 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 corrected. In practical validation experiments, this procedure showed promising results with a maximum RMS error of [Formula: see text]. MDPI 2015-10-13 /pmc/articles/PMC4634514/ /pubmed/26473873 http://dx.doi.org/10.3390/s151025919 Text en © 2015 by the authors; licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution license (http://creativecommons.org/licenses/by/4.0/). |
spellingShingle | Article Lüken, Markus Misgeld, Berno J.E. Rüschen, Daniel Leonhardt, Steffen Multi-Sensor Calibration of Low-Cost Magnetic, Angular Rate and Gravity Systems |
title | Multi-Sensor Calibration of Low-Cost Magnetic, Angular Rate and Gravity Systems |
title_full | Multi-Sensor Calibration of Low-Cost Magnetic, Angular Rate and Gravity Systems |
title_fullStr | Multi-Sensor Calibration of Low-Cost Magnetic, Angular Rate and Gravity Systems |
title_full_unstemmed | Multi-Sensor Calibration of Low-Cost Magnetic, Angular Rate and Gravity Systems |
title_short | Multi-Sensor Calibration of Low-Cost Magnetic, Angular Rate and Gravity Systems |
title_sort | multi-sensor calibration of low-cost magnetic, angular rate and gravity systems |
topic | Article |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4634514/ https://www.ncbi.nlm.nih.gov/pubmed/26473873 http://dx.doi.org/10.3390/s151025919 |
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