公开英国24名青少年糖尿病患者使用智能手表的多源数据集，助力糖尿病管理研究。
BrisT1D Dataset: Young Adults with Type 1 Diabetes in the UK using Smartwatches
- 采集24名患者日常血糖设备与智能手表数据，结合月度访谈
- 提供处理后与原始数据，支持血糖预测与算法开发
- 适合医疗健康、人机交互与慢性病管理研究者使用
1型糖尿病（T1D）管理技术快速发展，是未来慢性病管理的典型案例。为推动该领域技术进步，我们构建了布里斯托尔T1D数据集（BrisT1D），基于对英国24名年轻成人患者开展的纵向研究，其在常规管理基础上使用智能手表。数据集包含参与者使用的糖尿病管理设备与智能手表的双源数据，以及每月访谈和焦点小组的转录文本。设备数据以处理态和原始态两种形式提供，便于快速分析与深入挖掘新发现。定量数据可用于血糖预测、低血糖预警及闭环算法研发；定性数据则支持用户使用体验、意见探索及混合方法研究，揭示智能手表在糖尿病管理中的实际作用。
原文摘要 · Abstract (English)
Background: Type 1 diabetes (T1D) has seen a rapid evolution in management technology and forms a useful case study for the future management of other chronic conditions. Further development of this management technology requires an exploration of its real-world use and the potential of additional data streams. To facilitate this, we contribute the BrisT1D Dataset to the growing number of public T1D management datasets. The dataset was developed from a longitudinal study of 24 young adults in the UK who used a smartwatch alongside their usual T1D management. Findings: The BrisT1D dataset features both device data from the T1D management systems and smartwatches used by participants, as well as transcripts of monthly interviews and focus groups conducted during the study. The device data is provided in a processed state, for usability and more rapid analysis, and in a raw state, for in-depth exploration of novel insights captured in the study. Conclusions: This dataset has a range of potential applications. The quantitative elements can support blood glucose prediction, hypoglycaemia prediction, and closed-loop algorithm development. The qualitative elements enable the exploration of user experiences and opinions, as well as broader mixed-methods research into the role of smartwatches in T1D management.
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