PATHOLOGY CLASSIFICATION OF GAIT HUMAN GESTURES

Fabio Martínez, Juan Carlos León, Eduardo Romero

2011

Abstract

Gait patterns may be distorted in a large set of pathologies. In the clinical practice, the gait is studied using a set of measurements which allows identification of pathological disorders, thereby facilitating diagnosis, treatment and follow up. These measurements are obtained from a set of markers, carefully placed in some specific anatomical locations. This conventional procedure is obviously invasive and alters the natural movement gestures, a great drawback for diagnosis and management of the early disease stages, when accuracy is a crucial issue. Instead, markerless approaches attempt to capture the very nature of the movement with practically no intervention on the movement patterns. These techniques remain still limited concernig their clinical applications since they do not segment with sufficient precision the human silhouette. This article introduces a novel markerless strategy for classiying normal and pathological gaits, using a temporal-spatial characterization of the subject from 2 differents views. The feature vector is constructed by associating the spatial information obtained with SURF and the temporal information from a ∑-∆ operator. The strategy was evaluated in three groups of patients: normal, musculoskeletal disorders and parkinson’s disease, obtaining a precision and a recall of about 60%

Paper Citation

in Harvard Style

Martínez F., Carlos León J. and Romero E. (2011). PATHOLOGY CLASSIFICATION OF GAIT HUMAN GESTURES . In Proceedings of the International Conference on Computer Vision Theory and Applications - Volume 1: VISAPP, (VISIGRAPP 2011) ISBN 978-989-8425-47-8, pages 710-713. DOI: 10.5220/0003375907100713

in Bibtex Style

@conference{visapp11,
author={Fabio Martínez and Juan Carlos León and Eduardo Romero},
title={PATHOLOGY CLASSIFICATION OF GAIT HUMAN GESTURES},
booktitle={Proceedings of the International Conference on Computer Vision Theory and Applications - Volume 1: VISAPP, (VISIGRAPP 2011)},
year={2011},
pages={710-713},
publisher={SciTePress},
organization={INSTICC},
doi={10.5220/0003375907100713},
isbn={978-989-8425-47-8},
}

in EndNote Style

TY - CONF
JO - Proceedings of the International Conference on Computer Vision Theory and Applications - Volume 1: VISAPP, (VISIGRAPP 2011)
TI - PATHOLOGY CLASSIFICATION OF GAIT HUMAN GESTURES
SN - 978-989-8425-47-8
AU - Martínez F.
AU - Carlos León J.
AU - Romero E.
PY - 2011
SP - 710
EP - 713
DO - 10.5220/0003375907100713