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Article Dans Une Revue Journal of Computing and Information Technology Année : 2002

Experimental Methodology for the Evaluation of the 3D Visualization of Quantitative Information: a Case Study Concerning SEEG Information

Résumé

The visual analysis of Stereoeletroencephalographic (SEEG) signals in their anatomical context is aimed at the understanding of the spatio-temporal dynamics of epileptic processes. The magnitude of these signals may be encoded by graphical glyphs, having a direct impact on the perception of the values. This problem has motivated an evaluation of the quantitative visualization of these signals, specifically to the influence of the coding scheme of the glyphs on the understanding and the analysis of the signals. This work describes an experiment conducted with human observers in order to evaluate three different coding schemes used to visualize the magnitude of SEEG signals in their 3D anatomical context. In advance we had no clue to which of these schemes would provide better performances to the human observers, since we found in the literature theories that could support different answers. Through this experiment we intended to study if any of these coding schemes allows better performances in two aspects: accuracy and speed. A protocol has been developed in order to measure these aspects. The results that will be presented in this work were obtained from 40 human observers. The comparison between the three coding schemes has first been performed through an Exploratory Data Analysis (EDA). The statistical significance of this comparison has then been established using nonparametric methods. The influence on the observers' performance of some other factors has also been investigated.
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Dates et versions

inserm-00133392 , version 1 (15-11-2007)

Identifiants

  • HAL Id : inserm-00133392 , version 1

Citer

Beatriz Sousa Santos, Jean-Louis Dillenseger, Carlos G. Ferreira. Experimental Methodology for the Evaluation of the 3D Visualization of Quantitative Information: a Case Study Concerning SEEG Information. Journal of Computing and Information Technology, 2002, 10 (2), pp.103-113. ⟨inserm-00133392⟩
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