1. Chronodes: Interactive Multifocus Exploration of Event Sequences
- Author
-
Peter J. Polack, Moushumi Sharmin, Minsuk Kahng, Shang-Tse Chen, Rahul C. Basole, Duen Horng Chau, and Kaya de Barbaro
- Subjects
Potential impact ,Creative visualization ,Event (computing) ,Computer science ,media_common.quotation_subject ,05 social sciences ,020207 software engineering ,Timeline ,02 engineering and technology ,Data science ,Article ,Domain (software engineering) ,Human-Computer Interaction ,Event sequence ,Artificial Intelligence ,0202 electrical engineering, electronic engineering, information engineering ,0501 psychology and cognitive sciences ,Sequential Pattern Mining ,mHealth ,050107 human factors ,media_common - Abstract
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.
- Published
- 2018