Research Article
Inertial Sensor Based Motion Trajectory Visualization and Quantitative Quality Assessment of Hemiparetic Gait
@INPROCEEDINGS{10.4108/icst.bodynets.2013.253556, author={Yan Wang and James Xu and Xiaoyu Xu and Xiaoxu Wu and Gregory Pottie and William Kasier}, title={Inertial Sensor Based Motion Trajectory Visualization and Quantitative Quality Assessment of Hemiparetic Gait}, proceedings={8th International Conference on Body Area Networks}, publisher={ICST}, proceedings_a={BODYNETS}, year={2013}, month={10}, keywords={3d motion tracking trajectory visualization quantitative quality assessment}, doi={10.4108/icst.bodynets.2013.253556} }
- Yan Wang
James Xu
Xiaoyu Xu
Xiaoxu Wu
Gregory Pottie
William Kasier
Year: 2013
Inertial Sensor Based Motion Trajectory Visualization and Quantitative Quality Assessment of Hemiparetic Gait
BODYNETS
ACM
DOI: 10.4108/icst.bodynets.2013.253556
Abstract
The analysis of the biomechanics surrounding human gait has been used by many disciplines, and is especially useful in fields such as neurology, where many diseases are diagnosed clinically through careful observations of a person's movement. In patients afflicted by neurological diseases, hemiparetic gait is common and this abnormal gait causes the state of the art in motion reconstruction to fail. This paper presents two novel contributions to the area. The first is a novel gait trajectory reconstruction and visualization method with a zero velocity detection method targeting hemiparetic gait patterns, enabling reconstruction and visualization of hemiparetic gait in true 3D space. The second is a set of novel quality metrics developed in conjunction with the UCLA Department of Neurology, for evaluating patients suffering from neurological diseases.