Talks and presentations

Gait Deviation Assessment: from Signal to Image Analysis

October 17, 2024

Conference proceedings talk, 13th IEEE International Conference on Image Processing Theory, Tools and Applications (IPTA 2024), Rabat, Morocco

In this paper, we propose a novel framework for gait quality assessment based on image analysis, extending the traditional signal-based approach. Specifically, we construct Cycle Dissimilarity Images (CDI) from raw gait signals. Such images summarize all local dissimilarities existing in the dynamics between a gait signal and one normal gait reference. Also, we construct a typical dissimilarity image, by matching each normal gait reference to itself. Then, we propose to quantify gait deviations by computing the distance between the CDIs and the typical dissimilarity images. Our results indicate that, compared to the signal-based approach, this new framework leads to a more precise gait deviation assessment, and a more refined characterization of motor impairments, as hemiparesis, tetraparesis, and paraparesis.

An enhanced characterization of gait deviations in Hemiparesis by combining knee and ankle kinematics

September 20, 2024

Conference proceedings talk, ESMAC 2024, Oslo, Norway

Gait quality measures such as GDI [1] and GPS [2] rely on the Euclidian distance between time-normalized kinematic data to an average standard derived from healthy samples. Not accounting for temporal shifts can make these measures difficult to interpret or even unsuitable in some cases. For instance, in adult Hemiparesis, GDI and GPS are paradoxically often closer to the standard for the affected limb than for the unaffected limb [3]. We propose a novel method to characterize normal gait by identifying multiple representatives among the control group, and to compute deviations using an elastic metric taking into account temporal shifts.

Caractérisation de la marche normale et des déviations pathologiques dues aux maladies neurologiques : étude comparative des mesures de déviations de la marche

January 24, 2024

Conference proceedings talk, XXII congrès de la Société Francophone d'analyse du mouvement chez l'enfant et l'adulte (SOFAMEA), Nantes, France

Objectifs

Cette étude vise à améliorer la caractérisation de la marche normale et des déviations pathologiques induites par des maladies neurologiques. Les objectifs sont la prise en compte de la variance présente au sein de la marche normale et de la dynamique temporelle des signaux de marche, ainsi que la quantification précise des déviations pathologiques par rapport à la marche d’individus sains. Enfin, la comparaison des performances de notre nouvelle méthode sera effectuée avec le Gait Deviation Index (GDI) et le Gait Profile Score (GPS).

Gait Deviation and Neurological Diseases: a Comparative Study of Quantitative Measures

November 09, 2023

Conference proceedings talk, IEEE E-Health and Bioengineering, Bucharest, Romania

This comparative study addresses the quantification of gait deviations from normal gait, and across different motor impairments induced by neurological diseases. We compared Gait Deviation Index and Gait Profile Score, well-known in the literature, to a novel 3D-metric based on Dynamic Time Warping (DTW) [1]. These deviation measures are analyzed following the same methodology, based on unsupervised learning, on the same database. Results show that our 3D-metric outperforms the others. This confirms that for finely quantifying deviations, it is crucial to consider different references to represent normal gait variability, as well as using an elastic distance (DTW) for matching two gait cycles.