Exocentric and Egocentric Views for Biomedical Data Analytics in Virtual Environments-A Usability Study.

Jing Ng,David Arness, Ashlee Gronowski,Zhonglin Qu,Chng Wei Lau,Daniel Catchpoole,Quang Vinh Nguyen

Journal of Imaging（2024）

Western Sydney Univ | Childrens Hosp Westmead

Cited 1|Views10

Abstract

Biomedical datasets are usually large and complex, containing biological information about a disease. Computational analytics and the interactive visualisation of such data are essential decision-making tools for disease diagnosis and treatment. Oncology data models were observed in a virtual reality environment to analyse gene expression and clinical data from a cohort of cancer patients. The technology enables a new way to view information from the outside in (exocentric view) and the inside out (egocentric view), which is otherwise not possible on ordinary displays. This paper presents a usability study on the exocentric and egocentric views of biomedical data visualisation in virtual reality and their impact on usability on human behaviour and perception. Our study revealed that the performance time was faster in the exocentric view than in the egocentric view. The exocentric view also received higher ease-of-use scores than the egocentric view. However, the influence of usability on time performance was only evident in the egocentric view. The findings of this study could be used to guide future development and refinement of visualisation tools in virtual reality.

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Key words

virtual reality,virtual environment,exocentric visualization,egocentric visualization,biomedical data

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