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.

中文翻译：

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时间节点

移动健康 (mHealth) 技术的出现对当前可视化、交互式工具和算法的能力提出了挑战。我们展示了 Chronodes，这是一个交互式系统，它统一了数据挖掘和以人为中心的可视化技术，以支持纵向 mHealth 数据的探索性分析。Chronodes 提取并可视化频繁的事件序列，这些序列揭示了 mHealth 数据的多个参与者时间线中的时间顺序模式。然后，它结合了新颖的交互和可视化技术来实现多焦点事件序列分析，这允许健康研究人员使用事件序列组合以交互方式定义、探索和比较参与者行为组。通过总结从与 20 位行为和生物医学健康专家进行的试点研究中获得的见解，我们讨论了 Chronodes 在 mHealth 领域的功效和潜在影响。最后，我们概述了移动医疗中重要的开放性挑战，并为未来的研究提供了建议和设计指南。