Continuous Glucose Monitoring Technology and a Workflow for Its Data Analysis

• Activity Number: 355 - Contributed Poster Presentations: Biopharmaceutical Section
• Type: Contributed
• Date/Time: Tuesday, July 30, 2019 : 10:30 AM to 12:20 PM
• Sponsor: Biopharmaceutical Section
• Author(s): Dandan Wang* and Xiaohua Douglas Zhang and Zhaozhi Zek Zhang
• Companies: Faculty of Health Sciences, Univerity of Macau and University of Macau and Washington University
• Keywords: Continuous glucose monitoring; Diabetes; Technologies; Data Analysis; R package; Wearable

Abstract

Continuous glucose monitoring (CGM) system along with its data analysis is the new “cutting edge” technology for treating diabetes. Non-invasive CGM is the fine technology to capture data of glucose dynamics and thus is considered to be the “holy grail” for treating diabetes. The information from various CGM technology needed to be revealed in order to be used in diabetes management and treatment. Thus it is critical to analyze the data from CGM technologies. That is why prestigious companies like Apple, Samsung and Google not only are taking steps to push the invention of wearables for monitoring glucose levels but also have invested heavily in platforms with strong capacity in data analysis that offer consumers the ability to track data on their own health related to diabetes. Consequently, it is critical to know the development and characteristics of various CGM technologies and then to use a workflow for analyzing CGM data from various CGM technologies. Recently, we have developed a R package for analyzing CGM data. Therefore, in this presentation, we provide a map of milestones in the development of CGM technology and present a complete workflow for analyzing CGM data.