Continuous Blood Glucose (CGM) monitors have revolutionized the ability of diabetics to manage their blood glucose, and paved the way for artificial pancreas systems. In this paper we augment CGM data with sensor input collected by a smart phone and use it to provide analytical tools for patients and clinicians. We collected GPS data, activity classifications, and blood glucose data with a custom iOS application over a 9 month period from a single free-living type-1 diabetic patient. This data set is novel in terms of it's size, the inclusion of GPS data, and the fact that it was collected non-intrusively from a free-living patient. We describe a method to measure the occurrence of lifestyle \textit{events} based on GPS and activity data, and show that they can capture instances of food consumption and are therefore correlated to changes in blood glucose. Finally, we incorporate these event representations into our system to create useful visualizations and notifications to aid patients in managing their diabetes.

翻译：连续血糖监测仪（CGM）彻底改变了糖尿病患者管理血糖的能力，并为人工胰腺系统奠定了基础。本文通过智能手机采集的传感器数据增强CGM数据，为患者和临床医生提供分析工具。我们利用定制iOS应用程序，在9个月内从一名自由生活的1型糖尿病患者处收集了GPS数据、活动分类和血糖数据。该数据集在规模、包含GPS数据以及从自由生活患者非侵入性采集等方面具有创新性。我们描述了一种基于GPS和活动数据测量生活方式“事件”发生的方法，并证明该方法能捕捉食物摄入实例，从而与血糖变化相关。最后，我们将这些事件表征融入系统，生成有用的可视化和通知，以辅助患者进行糖尿病管理。