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.
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.
History
Event
IEEE Industrial and Information Systems. Conference (10th : 2015 : Sri Lanka)
Pagination
1 - 5
Publisher
IEEE
Location
Peradeniya, Sri Lanka
Place of publication
Piscataway, N. J.
Start date
2015-12-17
End date
2015-12-20
ISBN-13
9781509017416
Language
eng
Publication classification
E Conference publication; E1 Full written paper - refereed
Copyright notice
2015, IEEE
Editor/Contributor(s)
V Herath
Title of proceedings
ICIIS 2015 : Proceedings of the 2015 IEEE 10th International Conference on Industrial and Information Systems