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Chronodes: Interactive Multifocus Exploration of Event Sequences

Published: 06 February 2018 Publication History
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  • 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.

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    Published In

    cover image ACM Transactions on Interactive Intelligent Systems
    ACM Transactions on Interactive Intelligent Systems  Volume 8, Issue 1
    Special Issue on Interactive Visual Analysis of Human Crowd Behaviors and Regular Paper
    March 2018
    132 pages
    ISSN:2160-6455
    EISSN:2160-6463
    DOI:10.1145/3185338
    Issue’s Table of Contents
    Permission to make digital or hard copies of all or part of this work for personal or classroom use is granted without fee provided that copies are not made or distributed for profit or commercial advantage and that copies bear this notice and the full citation on the first page. Copyrights for components of this work owned by others than ACM must be honored. Abstracting with credit is permitted. To copy otherwise, or republish, to post on servers or to redistribute to lists, requires prior specific permission and/or a fee. Request permissions from [email protected]

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    Publication History

    Published: 06 February 2018
    Accepted: 01 October 2017
    Revised: 01 July 2017
    Received: 01 January 2017
    Published in TIIS Volume 8, Issue 1

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    Author Tags

    1. Mobile health sensor data
    2. cohort discovery
    3. event alignment
    4. mHealth
    5. sequence mining

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