Kaleidomap visualizations of cardiovascular function in critical care medicine

Kim Bale*, Paul Chapman, Jon Purdy, Nizamettin Aydin, Paul Dark

*Corresponding author for this work

Research output: Chapter in Book/Report/Conference proceedingConference contributionpeer-review

1 Citation (Scopus)

Abstract

In this paper we consider how the use of Kaleidomaps can facilitate our understanding and interpretation of large complex multivariate medical datasets relating to cardiovascular function in critical care medicine. Kaleidomaps are a new technique for the visualization of multivariate time-series data. They build upon the classic cascade plot and use the curvature of a line to enhance the detection of periodic patterns within multivariate dual-periodicity datasets. Kaleidomaps keep user interaction to a minimum, facilitating the rapid identification of periodic patterns not only within their own variants but also across many different sets of the variants. By linking this technique with traditional line graphs and signal processing techniques, we are able to provide medical experts with a set of visualization tools that permit the combination of medical datasets in their raw form and also with the results of mathematical analysis.

Original languageEnglish
Title of host publicationProceedings - International Conference on Medical Information Visualisation - BioMedical Visualisation, MediVis 2006
Pages51-56
Number of pages6
DOIs
Publication statusPublished - 2006
Externally publishedYes
EventInternational Conference on Medical Information Visualisation - BioMedical Visualisation, MediVis 2006 - London, United Kingdom
Duration: 5 Jul 20067 Jul 2006

Publication series

NameProceedings - International Conference on Medical Information Visualisation - BioMedical Visualisation, MediVis 2006

Conference

ConferenceInternational Conference on Medical Information Visualisation - BioMedical Visualisation, MediVis 2006
Country/TerritoryUnited Kingdom
CityLondon
Period5/07/067/07/06

Keywords

  • Data mining
  • Information visualization
  • Kaleidomaps
  • Multivariate time-series data

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