DocumentCode :
743138
Title :
Fast Determination of the Planar Body Segment Inertial Parameters Using Affordable Sensors
Author :
Bonnet, Vincent ; Venture, Gentiane
Author_Institution :
Dept. of Mech. Syst. Eng., Tokyo Univ. of Agric. & Technol., Tokyo, Japan
Volume :
23
Issue :
4
fYear :
2015
fDate :
7/1/2015 12:00:00 AM
Firstpage :
628
Lastpage :
635
Abstract :
This study aimed at developing and evaluating a new method for the fast and reliable identification of body segment inertial parameters with a planar model using affordable sensors. A Kinect sensor, with a new marker-based tracking system, and a Wii balance board were used as an affordable and portable motion capture system. A set of optimal exciting motions was used in a biofeedback interface to identify the body segment parameters. The method was validated with 12 subjects performing various standardized motions. The same dynamometric quantities estimated both with the proposed system and, as a reference, with a laboratory grade force-plate were compared. The results showed that the proposed method could successfully estimate the resultant moment and the vertical ground reaction force (rms errors less than 8 Nm and 12 N, respectively). Finally, when local segment values were artificially varied, the proposed method was able to detect and estimate the additional masses accurately and with an error of less than 0.5 Kg, contrary to values generated with commonly used anthropometric tables.
Keywords :
biomechanics; biomedical telemetry; wireless sensor networks; Kinect sensor; Wii balance board; affordable sensors; anthropometric tables; biofeedback interface; dynamometric quantities; laboratory grade force-plate; marker-based tracking system; mass detection; optimal exciting motions; planar body segment inertial parameters; portable motion capture system; resultant moment estimation; standardized motions; vertical ground reaction force; Joints; Kinetic theory; Mathematical model; Robots; Sensors; Tracking; Visualization; Body segment inertial parameters; identification; inverse dynamics;
fLanguage :
English
Journal_Title :
Neural Systems and Rehabilitation Engineering, IEEE Transactions on
Publisher :
ieee
ISSN :
1534-4320
Type :
jour
DOI :
10.1109/TNSRE.2015.2405087
Filename :
7052399
Link To Document :
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