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A machine-driven process for human limb length estimation using inertial sensors

Karunarathne, M. Sajeewani, Li, Saiyi, Ekanayake, Samitha W. and Pathirana, Pubudu N. 2015, A machine-driven process for human limb length estimation using inertial sensors, in ICIIS 2015 : Proceedings of the 2015 IEEE 10th International Conference on Industrial and Information Systems, IEEE, Piscataway, N. J., pp. 1-5.

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Title A machine-driven process for human limb length estimation using inertial sensors
Author(s) Karunarathne, M. Sajeewani
Li, Saiyi
Ekanayake, Samitha W.
Pathirana, Pubudu N.ORCID iD for Pathirana, Pubudu N. orcid.org/0000-0001-8014-7798
Conference name IEEE Industrial and Information Systems. Conference (10th : 2015 : Sri Lanka)
Conference location Peradeniya, Sri Lanka
Conference dates 17-20 Dec 2015
Title of proceedings ICIIS 2015 : Proceedings of the 2015 IEEE 10th International Conference on Industrial and Information Systems
Editor(s) Herath, V.
Publication date 2015
Start page 1
End page 5
Total pages 5
Publisher IEEE
Place of publication Piscataway, N. J.
Summary The computer based human motion tracking systems are widely used in medicine and sports. The accurate determination of limb lengths is crucial for not only constructing the limb motion trajectories which are used for evaluation process of human kinematics, but also individually recognising human beings. Yet, as the common practice, the limb lengths are measured manually which is inconvenient, time-consuming and requires professional knowledge. In this paper, the estimation process of limb lengths is automated with a novel algorithm calculating curvature using the measurements from inertial sensors. The proposed algorithm was validated with computer simulations and experiments conducted with four healthy subjects. The experiment results show the significantly low root mean squared error percentages such as upper arm - 5.16%, upper limbs - 5.09%, upper leg - 2.56% and lower extremities - 6.64% compared to measured lengths.
ISBN 9781509017416
Language eng
Field of Research 090303 Biomedical Instrumentation
090304 Medical Devices
090305 Rehabilitation Engineering
Socio Economic Objective 970109 Expanding Knowledge in Engineering
HERDC Research category E1 Full written paper - refereed
ERA Research output type E Conference publication
Copyright notice ©2015, IEEE
Persistent URL http://hdl.handle.net/10536/DRO/DU:30080699

Document type: Conference Paper
Collection: School of Engineering
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