ArticleSensors (Basel, Switzerland)2019
Patient-Generated Health Data Integration and Advanced Analytics for Diabetes Management: The AID-GM Platform.
Article in Sensors (Basel, Switzerland), 2019. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 7 papers.
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Who cites it
7 citing papers in PubMed.
- Caregiver experiences of an integrative patient-centered digital health application for pediatric type 1 diabetes care: Findings from a pilot clinical trial.PLOS digital health · 2025Article
- Attributes, Methods, and Frameworks Used to Evaluate Wearables and Their Companion mHealth Apps: Scoping Review.JMIR mHealth and uHealth · 2024Article
- Patient Information Summarization in Clinical Settings: Scoping Review.JMIR medical informatics · 2023Article
- Visualization of Patient-Generated Health Data: A Scoping Review of Dashboard Designs.Applied clinical informatics · 2023Article
- Continuous Glucose and Heart Rate Monitoring in Young People with Type 1 Diabetes: An Exploratory Study about Perspectives in Nocturnal Hypoglycemia Detection.Metabolites · 2020Article
- Emerging Wireless Sensor Networks and Internet of Things Technologies-Foundations of Smart Healthcare.Sensors (Basel, Switzerland) · 2020Article
- Sensor technology for nursing research.Nursing outlookReview
Corrections and comments
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Authors and funding
8 authors.
Funding
No grant is acknowledged in the PubMed record.
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.
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