UWB-Aided Inertial Motion Capture for Lower Body 3-D Dynamic Activity and Trajectory Tracking

This paper introduces a novel method for simultaneous 3-D trajectory tracking and lower body motion capture (MoCap) under various dynamic activities such as walking and jumping. The proposed method uses wearable inertial sensors fused with an ultrawideband localization system using a cascaded Kalman...

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Veröffentlicht in:IEEE transactions on instrumentation and measurement Jg. 64; H. 12; S. 3577 - 3587
Hauptverfasser: Zihajehzadeh, Shaghayegh, Yoon, Paul K., Bong-Soo Kang, Park, Edward J.
Format: Journal Article
Sprache:Englisch
Veröffentlicht: New York IEEE 01.12.2015
The Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Schlagworte:
Accelerometers
Inertial measurement unit (IMU)
inertial motion tracking
Kalman filter (KF)
Kalman filters
Microelectromechanical systems
microelectromechanical systems (MEMS)
Sensor fusion
Trajectory tracking
ultrawideband (UWB) localization
Wearable sensors
wearable technology
Inertial measurement unit (IMU)
inertial motion tracking
ultrawideband (UWB) localization
wearable technology
microelectromechanical systems (MEMS)
Kalman filter (KF)
ISSN:0018-9456, 1557-9662
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Zusammenfassung:This paper introduces a novel method for simultaneous 3-D trajectory tracking and lower body motion capture (MoCap) under various dynamic activities such as walking and jumping. The proposed method uses wearable inertial sensors fused with an ultrawideband localization system using a cascaded Kalman filter-based sensor fusion algorithm, which consists of a separate orientation filter cascaded with a position/velocity filter. In addition, to further improve the joint angle tracking accuracy, anatomical constraints are applied to the knee joint. Currently, available self-contained inertial tracking methods are not only drift-prone over time but also their accuracy is degraded under fast movements with unstable ground contact states due to the lack of external references. However, our experimental results, which benchmark the system against a reference camera-based motion tracking system, show that the proposed fusion method can accurately capture the dynamic activities of a subject without drift. The results show that the proposed system can maintain similar accuracies between fast and slow motions in lower body MoCap and 3-D trajectory tracking. The obtained accuracies of the system for 3-D body localization and knee joint angle tracking for fast motions were less than 5 cm and 2.1°, respectively.
Bibliographie:ObjectType-Article-1
SourceType-Scholarly Journals-1
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ISSN:0018-9456
1557-9662
DOI:10.1109/TIM.2015.2459532