Chronodes: Interactive Multi-focus Exploration of Event Sequences

TL;DR

Chronodes is an interactive visualization system that helps researchers explore, interpret, and compare event sequences in large mobile health datasets, revealing patterns and cohorts for health analysis.

Contribution

The paper introduces Chronodes, a novel interactive tool with techniques for visualizing and analyzing event sequences in high-dimensional mobile health data.

Findings

Successfully visualized frequent event sequences across participants.

Enabled cohort comparison based on event patterns.

Pilot study demonstrated Chronodes' usefulness for health research.

Abstract

The advent of mobile health technologies presents new challenges that existing visualizations, interactive tools, and algorithms are not yet designed to support. In dealing with uncertainty in sensor data and high-dimensional physiological records, we must seek to improve current tools that make sense of health data from traditional perspectives in event-based trend discovery. With Chronodes, a system developed to help researchers collect, interpret, and model mobile health (mHealth) data, we posit a series of interaction techniques that enable new approaches to understanding and exploring event-based data. From numerous and discontinuous mobile health data streams, Chronodes finds and visualizes frequent event sequences that reveal common chronological patterns across participants and days. By then promoting the sequences as interactive elements, Chronodes presents opportunities for finding, defining, and comparing cohorts of participants that exhibit particular behaviors. We applied Chronodes to a real 40GB mHealth dataset capturing about 400 hours of data. Through our pilot study with 20 behavioral and biomedical health experts, we gained insights into Chronodes' efficacy, limitations, and potential applicability to a wide range of healthcare scenarios.