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Chronodes: Interactive Multifocus Exploration of Event Sequences.
Polack, Peter J; Chen, Shang-Tse; Kahng, Minsuk; DE Barbaro, Kaya; Basole, Rahul; Sharmin, Moushumi; Chau, Duen Horng.
Afiliação
  • Polack PJ; Georgia Institute of Technology.
  • Chen ST; Georgia Institute of Technology.
  • Kahng M; Georgia Institute of Technology.
  • DE Barbaro K; Georgia Institute of Technology.
  • Basole R; Georgia Institute of Technology.
  • Sharmin M; Western Washington University.
  • Chau DH; Georgia Institute of Technology.
Article em En | MEDLINE | ID: mdl-29515937
The advent of mobile health (mHealth) technologies challenges the capabilities of current visualizations, interactive tools, and algorithms. We present Chronodes, an interactive system that unifies data mining and human-centric visualization techniques to support explorative analysis of longitudinal mHealth data. Chronodes extracts and visualizes frequent event sequences that reveal chronological patterns across multiple participant timelines of mHealth data. It then combines novel interaction and visualization techniques to enable multifocus event sequence analysis, which allows health researchers to interactively define, explore, and compare groups of participant behaviors using event sequence combinations. Through summarizing insights gained from a pilot study with 20 behavioral and biomedical health experts, we discuss Chronodes's efficacy and potential impact in the mHealth domain. Ultimately, we outline important open challenges in mHealth, and offer recommendations and design guidelines for future research.
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Texto completo: 1 Base de dados: MEDLINE Idioma: En Ano de publicação: 2018 Tipo de documento: Article

Texto completo: 1 Base de dados: MEDLINE Idioma: En Ano de publicação: 2018 Tipo de documento: Article