用可穿戴数据+用户标注,让压力管理更可视、可行动。
From Wearable Data to Personalized and Actionable Health Insights

- 结合用户标注与生理数据,构建交互式可视化框架。
- 社交互动使心率平均下降4.35至5.0次/分钟。
- 适合关注自我健康、想改善压力管理的普通用户。
商用可穿戴设备持续采集丰富生理数据(如心率、呼吸),为监测压力等健康状况带来新可能。然而,如何将原始生理数据转化为日常活动中能揭示压力线索的可视化信息,并最终促进反思、提升觉知和改善压力管理,仍是重大挑战。数据噪声大且依赖上下文:心率突增可能是跑步、紧张演讲或朋友欢笑所致。为此,我们提出一个融合用户标注与可穿戴数据的框架。设计了一款网页工具,支持将日常活动、压力事件与干预措施叠加到原始生理数据流上,帮助用户反思并识别趋势。四週试点中,七名高校学生共记录269个事件。结果显示:社交互动使平均心率降低4.35至5.0次/分钟;刻意休息使平均Garmin压力分值下降10.03至13.83分;正念活动使平均心率变异性(HRV)下降6.61至13.22毫秒。
原文摘要 · Abstract (English)
Commercial wearable devices continuously capture rich physiological data (e.g., heart rate, respiration), opening new possibilities for monitoring health conditions, notably around stress. Despite their promise, turning raw wearable physiological data streams into visualizations that surface stress-related insights in daily activities, and that ultimately foster reflection, awareness, and better stress management, remains a significant challenge. The data are noisy and context-dependent: the same spike in heart rate can come from sprinting, a tense presentation, or laughing with friends. To address these challenges, we propose a framework that combines user annotations with wearable data to support better stress management. We introduce a web framework offering interactive visualizations that layer daily activities, stress events, and interventions onto raw physiological streams, enabling users to reflect and identify trends. In a four-week pilot with seven university graduate and undergraduate student participants who logged 269 events, our tool revealed patterns between different types of interventions and stress: social interaction reduced average heart rate by 4.35 to 5.0 beats per minute, deliberate rest reduced average Garmin stress scores by 10.03 to 13.83 points, and mindfulness activities decreased average HRV by 6.61 to 13.22 milliseconds.
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