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Meal-time Detection by Means of Long Periods Blood Glucose Level Monitoring via IoT Technology by Ahmed, Hassan M.; Maraoui, Souhail; Sadek, Muhammed Abd Elnaby; Abdulrazak, Bessam; Vandenberghe, Camille; Cunnane, Stephen C.; Blanchet, F. Guillaume is a scholarly article available to read on EtoBox.

What is Meal-time Detection by Means of Long Periods Blood Glucose Level Monitoring via IoT Technology about?

Blood glucose level monitoring is of great importance, especially for subjects experiencing type 1 diabetes. Accurate monitoring of their blood glucose level prevents dangerous and life-threatening situations that might be experienced by those subjects. In addition, precise monitoring of blood glucose levels over long periods of time helps establishing knowledge about the daily mealtime routine which aids the medical staff to monitor subjects and properly intervene in hazardous cases such as hypo- or hyperglycemia. Establishing such knowledge will play a potential role when designing proper treatment intervention plan. In this research, we present a complete IoT framework, starting from hardware acquisition system to data analysis approaches that gives a hand for medical staff when long periods of blood glucose monitoring are essential for subjects. Also, this framework is validated with real-time data collection from 7 subjects over 10 successive days with temporal resolution of 5 minutes allowing for near real-time monitoring and analysis. Our results show the precisely estimated daily mealtime routines for 4 subjects out of the 7 with discard of 3 subjects due to huge data loss

Author

Ahmed, Hassan M.; Maraoui, Souhail; Sadek, Muhammed Abd Elnaby; Abdulrazak, Bessam; Vandenberghe, Camille; Cunnane, Stephen C.; Blanchet, F. Guillaume

Published

2023

Language

EN