%0 Journal Article
	%A Adam Świtoński and  Agnieszka Michalczuk and  Henryk Josiński and  Andrzej Polański and  KonradWojciechowski
	%D 2012
	%J International Journal of Computer and Information Engineering
	%B World Academy of Science, Engineering and Technology
	%I Open Science Index 71, 2012
	%T Dynamic Time Warping in Gait Classificationof Motion Capture Data
	%U https://publications.waset.org/pdf/14952
	%V 71
	%X The method of gait identification based on the nearest neighbor classification technique with motion similarity assessment by the dynamic time warping is proposed. The model based kinematic motion data, represented by the joints rotations coded by Euler angles and unit quaternions is used. The different pose distance functions in Euler angles and quaternion spaces are considered. To evaluate individual features of the subsequent joints movements during gait cycle, joint selection is carried out. To examine proposed approach database containing 353 gaits of 25 humans collected in motion capture laboratory is used. The obtained results are promising. The classifications, which takes into consideration all joints has accuracy over 91%. Only analysis of movements of hip joints allows to correctly identify gaits with almost 80% precision.

	%P 1289 - 1294