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

AMA 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(6):1257. https://doi.org/10.3390/s17061257

Chicago/Turabian Style

Filippeschi, Alessandro; Schmitz, Norbert; Miezal, Markus; Bleser, Gabriele; Ruffaldi, Emanuele; Stricker, Didier. 2017. "Survey of Motion Tracking Methods Based on Inertial Sensors: A Focus on Upper Limb Human Motion" Sensors 17, no. 6: 1257. https://doi.org/10.3390/s17061257

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