NDLI: An inertial-based human motion tracking system with twists and exponential maps

Content Provider	IEEE Xplore Digital Library
Author	Xi Chen Jie Zhang Hamel, W.R. Jindong Tan
Copyright Year	2014
Description	Author affiliation: Beijing Univ. of Chem. Technol., Beijing, China (Jie Zhang) \|\| Dept. of Mech., Aerosp. & Biomed. Eng., Univ. of Tennessee, Knoxville, TN, USA (Xi Chen; Hamel, W.R.; Jindong Tan)
Abstract	Wearable inertial tracking is well accepted due to its convenience for free-style motion tracking with high accuracy. Traditionally, complicated high-order calculations for human kinematic modeling and inaccurate estimation of sensor placement are interfering the efficiency of real-time tracking. In order to tackle the challenges, a wearable human motion tracking system is developed by applying twists and exponential maps techniques. When the body segments are articulated by product of exponential maps, joint positions are continuously updated based on these techniques and their rotational angles are represented individually within the global frame. It is more efficient to achieve real-time motion tracking with low-order calculations. Meanwhile by applying the well-designed calibration procedure, it is more convenient to estimate a sensor's position and orientation regardless of knowing its placement. This paper presents our approach and exemplifies the assessment of proposed motion tracking system by several tests of limb and full body motion tracking. The comparisons with Vicon and OptiTrack motion capture systems verify satisfactorily high accuracy.
Starting Page	5665
Ending Page	5670
File Size	442106
Page Count	6
File Format	PDF
ISBN	9781479936854
DOI	10.1109/ICRA.2014.6907692
Language	English
Publisher	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Publisher Date	2014-05-31
Publisher Place	China
Access Restriction	Subscribed
Rights Holder	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Subject Keyword	Joints Tracking Shoulder Elbow Kinematics Quaternions Real-time systems
Content Type	Text
Resource Type	Article

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