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Chronodes: Interactive Multifocus Exploration of Event Sequences.

Peter J Polack1, Shang-Tse Chen1, Minsuk Kahng1

  • 1Georgia Institute of Technology.

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Summary
This summary is machine-generated.

Chronodes is a new system for analyzing mobile health (mHealth) data. It helps researchers explore patterns in participant behavior over time using interactive visualizations and data mining.

Keywords:
Applied computing → Health care information systemsHuman-centered computing → Visual analyticsMobile health sensor datacohort discoveryevent alignmentmHealthsequence mining

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Area of Science:

  • Health Informatics
  • Data Visualization
  • Human-Computer Interaction

Background:

  • Mobile health (mHealth) technologies generate complex longitudinal data.
  • Existing visualization and analysis tools struggle to handle the scale and complexity of mHealth data.
  • Need for advanced methods to explore chronological patterns in mHealth data.

Purpose of the Study:

  • Introduce Chronodes, an interactive system for explorative analysis of longitudinal mHealth data.
  • Unify data mining and human-centric visualization for pattern discovery.
  • Enable multifocus event sequence analysis for comparing participant behaviors.

Main Methods:

  • Developed Chronodes, integrating data mining and visualization techniques.
  • Implemented extraction and visualization of frequent event sequences.
  • Incorporated novel interaction techniques for multifocus analysis of event sequence combinations.

Main Results:

  • Chronodes effectively visualizes chronological patterns in longitudinal mHealth data.
  • The system facilitates interactive exploration and comparison of participant behavior groups.
  • Pilot study with health experts demonstrated Chronodes's utility and potential impact.

Conclusions:

  • Chronodes offers a powerful approach for analyzing complex mHealth data.
  • The system supports health researchers in understanding behavioral patterns.
  • Identified open challenges and provided design guidelines for future mHealth research.