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Sensors 2017, 17(6), 1257; doi:10.3390/s17061257

Survey of Motion Tracking Methods Based on Inertial Sensors: A Focus on Upper Limb Human Motion

1
TeCIP Institute, Scuola Superiore Sant’Anna, 56127 Pisa, Italy
2
German Research Center for Artificial Intelligence, 67663 Kaiserslautern, Germany
3
Junior research group wearHEALTH, Department of Computer Science, University of Kaiserslautern, 67663 Kaiserslautern, Germany
*
Author to whom correspondence should be addressed.
Academic Editors: Giancarlo Fortino, Hassan Ghasemzadeh, Wenfeng Li, Yin Zhang and Luca Benini
Received: 28 March 2017 / Revised: 23 May 2017 / Accepted: 24 May 2017 / Published: 1 June 2017
(This article belongs to the Special Issue Advances in Body Sensor Networks: Sensors, Systems, and Applications)
View Full-Text   |   Download PDF [1815 KB, uploaded 1 June 2017]   |  

Abstract

Motion tracking based on commercial inertial measurements units (IMUs) has been widely studied in the latter years as it is a cost-effective enabling technology for those applications in which motion tracking based on optical technologies is unsuitable. This measurement method has a high impact in human performance assessment and human-robot interaction. IMU motion tracking systems are indeed self-contained and wearable, allowing for long-lasting tracking of the user motion in situated environments. After a survey on IMU-based human tracking, five techniques for motion reconstruction were selected and compared to reconstruct a human arm motion. IMU based estimation was matched against motion tracking based on the Vicon marker-based motion tracking system considered as ground truth. Results show that all but one of the selected models perform similarly (about 35 mm average position estimation error). View Full-Text
Keywords: kinematics; sensor fusion; motion tracking; inertial measurements units kinematics; sensor fusion; motion tracking; inertial measurements units
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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

Filippeschi, A.; Schmitz, N.; Miezal, M.; Bleser, G.; Ruffaldi, E.; Stricker, D. Survey of Motion Tracking Methods Based on Inertial Sensors: A Focus on Upper Limb Human Motion. Sensors 2017, 17, 1257.

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