Treffer: Spatiotemporal Volumetric Analysis of Dynamic Plantar Pressure Data

Title:
Spatiotemporal Volumetric Analysis of Dynamic Plantar Pressure Data
Source:
Medicine and science in sports and exercise. 43(8):1582-1589
Publisher Information:
Hagerstown, MD: Lippincott Williams & Wilkins, 2011.
Publication Year:
2011
Physical Description:
print, 25 ref
Original Material:
INIST-CNRS
Document Type:
Fachzeitschrift Article
File Description:
text
Language:
English
Author Affiliations:
Department of Bioengineering, Shinshu University, Japan
Institutefor Sport Science, Chemnitz University of Technology, Germany
ISSN:
0195-9131
Rights:
Copyright 2015 INIST-CNRS
CC BY 4.0
Sauf mention contraire ci-dessus, le contenu de cette notice bibliographique peut être utilisé dans le cadre d’une licence CC BY 4.0 Inist-CNRS / Unless otherwise stated above, the content of this bibliographic record may be used under a CC BY 4.0 licence by Inist-CNRS / A menos que se haya señalado antes, el contenido de este registro bibliográfico puede ser utilizado al amparo de una licencia CC BY 4.0 Inist-CNRS
Notes:
Vertebrates : body movement. Posture. Locomotion. Flight. Swimming. Physical exercise. Rest. Sports
Accession Number:
edscal.24363252
Database:
PASCAL Archive

Weitere Informationen

Purpose: The purposes of this study were (i) to develop a three-dimensional interactive visualization tool for exploring plantar pressure time series and spatiotemporal statistical volumes and (ii) to demonstrate the benefits of volumetric analyses using various running and walking data sets. Methods: A data exploration tool was developed in Python using the open-source Visualization Toolkit. Multiple-pressure isosurfaces were computed and were then rendered with interactive rotation and adjustable thresholds and transparencies. Plantar pressure data were collected: (i) from two running subjects, one with a heel-loading pattern and one with a forefoot-loading pattern; (ii) from one individual while running straight and then while performing a cutting maneuver; and (iii) from one subject walking at three different speeds. All data were spatiotemporally aligned, and mean volumes were computed. Statistical volumes were also computed for the walking data set, and significance was assessed topologically using techniques from three-dimensional brain imaging. Results: After converting raw plantar pressure data into a rapidly readable format, volumetric renderings were presented in ∼50 ms, a negligible time lag for interactive data exploration. We observed that consideration of only spatial two-dimensional variables yielded impulse illusions that could be resolved most effectively with three-dimensional renderings. For all data sets, we found that dynamic foot behavior was clearest through interactive three-dimensional exploration. Conclusions: Plantar pressure data contain high-quality biomechanical information in their original three-dimensional form. The main benefit of the proposed visualization technique is that it affords qualitatively rich and unique holistic explorations of dynamic foot behavior.