Soft tissue artifact distribution on lower limbs during treadmill gait: Influence of skin markers' location on cluster design.

Détails

ID Serval
serval:BIB_ABF8E75CF076
Type
Article: article d'un périodique ou d'un magazine.
Collection
Publications
Institution
Titre
Soft tissue artifact distribution on lower limbs during treadmill gait: Influence of skin markers' location on cluster design.
Périodique
Journal of Biomechanics
Auteur⸱e⸱s
Barré A., Jolles B.M. (co-dernier), Theumann N. (co-dernier), Aminian K. (co-dernier)
ISSN
1873-2380 (Electronic)
ISSN-L
0021-9290
Statut éditorial
Publié
Date de publication
2015
Peer-reviewed
Oui
Volume
48
Numéro
10
Pages
1965-1971
Langue
anglais
Notes
Publication types: Journal ArticlePublication Status: ppublish
Résumé
Segment poses and joint kinematics estimated from skin markers are highly affected by soft tissue artifact (STA) and its rigid motion component (STARM). While four marker-clusters could decrease the STA non-rigid motion during gait activity, other data, such as marker location or STARM patterns, would be crucial to compensate for STA in clinical gait analysis. The present study proposed 1) to devise a comprehensive average map illustrating the spatial distribution of STA for the lower limb during treadmill gait and 2) to analyze STARM from four marker-clusters assigned to areas extracted from spatial distribution. All experiments were realized using a stereophotogrammetric system to track the skin markers and a bi-plane fluoroscopic system to track the knee prosthesis. Computation of the spatial distribution of STA was realized on 19 subjects using 80 markers apposed on the lower limb. Three different areas were extracted from the distribution map of the thigh. The marker displacement reached a maximum of 24.9mm and 15.3mm in the proximal areas of thigh and shank, respectively. STARM was larger on thigh than the shank with RMS error in cluster orientations between 1.2° and 8.1°. The translation RMS errors were also large (3.0mm to 16.2mm). No marker-cluster correctly compensated for STARM. However, the coefficient of multiple correlations exhibited excellent scores between skin and bone kinematics, as well as for STARM between subjects. These correlations highlight dependencies between STARM and the kinematic components. This study provides new insights for modeling STARM for gait activity.
Pubmed
Web of science
Création de la notice
27/08/2015 10:45
Dernière modification de la notice
21/01/2024 8:14
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