@inproceedings{ffc0bcbbd6224569acca737834ad6d45,
title = "The Diabetic Buddy: A Diet Regulator and Tracking System for Diabetics",
abstract = "The prevalence of Diabetes mellitus (DM) in the Middle East is exceptionally high as compared to the rest of the world. In fact, the prevalence of diabetes in the Middle East is 17-20\%, which is well above the global average of 8-9\%. Research has shown that food intake has strong connections with the blood glucose levels of a patient. In this regard, there is a need to build automatic tools to monitor the blood glucose levels of diabetics and their daily food intake. This paper presents an automatic way of tracking continuous glucose and food intake of diabetics using off-the-shelf sensors and machine learning, respectively. Our system not only helps diabetics to track their daily food intake but also assists doctors to analyze the impact of the food in-take on blood glucose in real-time. For food recognition, we collected a large-scale Middle-Eastern food dataset and proposed a fusion-based framework incorporating several existing pre-trained deep models for Middle-Eastern food recognition.",
keywords = "Diabetes management, continuous glucose monitoring, food recognition, middle-eastern food",
author = "Muhammad Usman and Kashif Ahmad and Amir Sohail and Marwa Qaraqe",
note = "Publisher Copyright: {\textcopyright} 2021 IEEE.; 18th International Conference on Content-Based Multimedia Indexing, CBMI 2021 ; Conference date: 28-06-2021 Through 30-06-2021",
year = "2021",
month = jun,
day = "28",
doi = "10.1109/CBMI50038.2021.9461897",
language = "English",
series = "Proceedings - International Workshop on Content-Based Multimedia Indexing",
publisher = "IEEE Computer Society",
booktitle = "2021 International Conference on Content-Based Multimedia Indexing, CBMI 2021",
address = "United States",
}