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Hand Pose Estimation by Fusion of Inertial and Magnetic Sensing Aided by a Permanent Magnet
University of Twente, Netherlands.
Lund University, Sweden.
Xsens Technology BV, Netherlands.
Linköping University, Department of Electrical Engineering, Automatic Control. Linköping University, Faculty of Science & Engineering.
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2015 (English)In: IEEE transactions on neural systems and rehabilitation engineering, ISSN 1534-4320, E-ISSN 1558-0210, Vol. 23, no 5, 796-806 p.Article in journal (Refereed) Published
Abstract [en]

Tracking human body motions using inertial sensors has become a well-accepted method in ambulatory applications since the subject is not confined to a lab-bounded volume. However, a major drawback is the inability to estimate relative body positions over time because inertial sensor information only allows position tracking through strapdown integration, but does not provide any information about relative positions. In addition, strapdown integration inherently results in drift of the estimated position over time. We propose a novel method in which a permanent magnet combined with 3-D magnetometers and 3-D inertial sensors are used to estimate the global trunk orientation and relative pose of the hand with respect to the trunk. An Extended Kalman Filter is presented to fuse estimates obtained from inertial sensors with magnetic updates such that the position and orientation between the human hand and trunk as well as the global trunk orientation can be estimated robustly. This has been demonstrated in multiple experiments in which various hand tasks were performed. The most complex task in which simultaneous movements of both trunk and hand were performed resulted in an average rms position difference with an optical reference system of 19.7 +/- 2.2 mm whereas the relative trunk-hand and global trunk orientation error was 2.3 +/- 0.9 and 8.6 +/- 8.7 deg respectively.

Place, publisher, year, edition, pages
Keyword [en]
Human body motion tracking; inertial sensing; magnetic tracking; sensor fusion; upper extremity tracking
National Category
Electrical Engineering, Electronic Engineering, Information Engineering
URN: urn:nbn:se:liu:diva-121903DOI: 10.1109/TNSRE.2014.2357579ISI: 000361317000008PubMedID: 25222952OAI: diva2:860750
Available from: 2015-10-13 Created: 2015-10-12 Last updated: 2015-11-11

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Gustafsson, Fredrik
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Automatic ControlFaculty of Science & Engineering
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