Gestational diabetes (GDM) poses a growing health risk to both pregnant women and their offspring. While telehealth interventions for GDM management have proven effective, they have traditionally relied on healthcare professionals for guidance and feedback. Our aim was to explore self-tracking in GDM with wearable sensors from self-discovery (i.e., learning associations between glucose levels and lifestyle) and user experience perspectives. We conducted a mixed-methods study with women diagnosed with GDM, utilizing continuous glucose monitor and three types of physical activity sensors (activity bracelet, hip-worn sensor, and electrocardiography sensor) for a week. Data from the sensors was collected, and participants were later interviewed about their experience with the wearable sensors. Additionally, we gathered maternal nutrition data through a 3-day food diary and recorded self-reported physical activity using a logbook. We discovered that continuous glucose monitors were especially valuable for self-discovery, particularly when establishing links between glucose levels and nutritional intake. Challenges associated with using wearable sensors data for self-discovery in GDM included: (1) Separation of glucose and physical activity data in different applications, (2) Missing key trackable features, such as light physical activity and non-walking activities, (3) Discrepancies in data, and (4) Differences in perceived versus measured physical activity. The placement of sensors on the body emerged as a critical factor influencing data quality and personal preferences. To conclude, an app where glucose, nutrition, and physical activity data are combined is needed to support self-discovery. This app should enable tracking of essential features for women with GDM, including light physical activity, with data originating from a single sensor to ensure consistency and eliminate redundancy.

翻译：妊娠期糖尿病（GDM）对孕妇及其后代构成日益增长的健康风险。尽管针对GDM管理的远程医疗干预已被证实有效，但传统上依赖医疗专业人员进行指导和反馈。本研究旨在从自我发现（即探索血糖水平与生活方式之间的关联）和用户体验两个维度，探究使用可穿戴传感器进行GDM自我追踪的可行性。我们采用混合方法对确诊GDM的女性开展研究，使用连续血糖监测仪及三种身体活动传感器（活动手环、髋部佩戴传感器和心电图传感器）进行为期一周的数据收集。在收集传感器数据后，对参与者进行关于可穿戴传感器使用体验的访谈。此外，通过为期3天的饮食日记收集产妇营养数据，并利用日志记录自我报告的身体活动。研究发现，连续血糖监测仪在建立血糖水平与营养摄入之间的关联方面特别有助于自我发现。使用可穿戴传感器数据进行GDM自我发现时面临的挑战包括：（1）血糖与身体活动数据分散于不同应用程序；（2）缺失关键可追踪特征，如轻度身体活动和非行走活动；（3）数据存在偏差；（4）感知身体活动与实际测量身体活动之间存在差异。传感器在身体上的佩戴位置成为影响数据质量和个人偏好的关键因素。结论认为，需要开发集成血糖、营养和身体活动数据的应用程序以支持自我发现。该应用程序应能追踪GDM女性的关键特征（包括轻度身体活动），且数据应源自单一传感器以确保一致性并消除冗余。