Patient-Generated Health Data Integration and Advanced Analytics for Diabetes Management: The AID-GM Platform

Abstract

Diabetes is a high-prevalence disease that leads to an alteration in the patient’s blood glucose (BG) values. Several factors influence the subject’s BG profile over the day, including meals, physical activity, and sleep. Wearable devices are available for monitoring the patient’s BG value around the clock, while activity trackers can be used to record his/her sleep and physical activity. However, few tools are available to jointly analyze the collected data, and only a minority of them provide functionalities for performing advanced and personalized analyses. In this paper, we present AID-GM, a web application that enables the patient to share with his/her diabetologist both the raw BG data collected by a flash glucose monitoring device, and the information collected by activity trackers, including physical activity, heart rate, and sleep. AID-GM provides several data views for summarizing the subject’s metabolic control over time, and for complementing the BG profile with the information given by the activity tracker. AID-GM also allows the identification of complex temporal patterns in the collected heterogeneous data. In this paper, we also present the results of a real-world pilot study aimed to assess the usability of the proposed system. The study involved 30 pediatric patients receiving care at the Fondazione IRCCS Policlinico San Matteo Hospital in Pavia, Italy.

Continuous Glucose and Heart Rate Monitoring in Young People with Type 1 Diabetes: An Exploratory Study about Perspectives in Nocturnal Hypoglycemia Detection

“…AID-GM is a web application developed at the Department of Electrical, Computer and Biomedical Engineering of the University of Pavia, Italy, in collaboration with the Pediatric Diabetology outpatient service of the Fondazione IRCCS Policlinico San Matteo Hospital in Pavia [ 15 ]. The AID-GM platform has been designed for the integration of heterogeneous data coming from FGM sensors, PFTs, and vocal messages provided by subjects reporting daily diary information, useful for monitoring both lifestyle and metabolic control of diabetic subjects.…”

“…This study aims to investigate the HR changes during nocturnal hypoglycemic episodes in children and adolescents with T1D, examining whether such signals could improve the detection and prevention of NH. For this purpose, blood glucose (BG) levels were monitored by a flash glucose monitoring (FGM) device, and HR was recorded by a wrist-worn personal fitness tracker (PFT), both connected to the Advanced Intelligent Distant-Glucose Monitoring (AID-GM) web-based platform [ 15 ]. Results from this study will provide important knowledge for the development of a potential NH alert.…”

Newest Diabetes-Related Technologies for Pediatric Type 1 Diabetes and Its Impact on Routine Care: a Narrative Synthesis of the Literature

“…Technology also allows the integration of care that goes beyond glycemic control, as demonstrated by the AID-GM (Advanced Intelligent Distant-Glucose Monitoring) webbased program for integration of blood glucose profile and other data (sleep patterns, physical activity, food intake, and other inputs), which may announce the dawn of what is called "e-Health" in diabetes care [76]. Remote monitoring in children with DM1 resulted in significant improvements in glycemic control (HbA1c, glycemic variability, and hypoglycemic frequency) [65].…”

Emerging Wireless Sensor Networks and Internet of Things Technologies—Foundations of Smart Healthcare

“…• Healthcare IoT for Patients provides patients with personalized healthcare utilizing different wearable devices such as activity trackers [79], inertial sensors [80] heart-rate and blood pressure monitoring sensors [81], glucose-level meters [82]. These devices are used to track patient's healthcare parameters in real-time and even perform local data analysis in addition to storing the historical data in the cloud.…”

“…In particular, the application of IoT in healthcare can bring many benefits to all involved parties. Depending on the target end-user, the IoT healthcare applications can be grouped as follows: Healthcare IoT for Patients provides patients with personalized healthcare utilizing different wearable devices such as activity trackers [ 79 ], inertial sensors [ 80 ] heart-rate and blood pressure monitoring sensors [ 81 ], glucose-level meters [ 82 ]. These devices are used to track patient’s healthcare parameters in real-time and even perform local data analysis in addition to storing the historical data in the cloud.…”