The diabetic buddy: a diet regulator and tracking system for diabetics

Muhammad Usman, Kashif Ahmad, Amir Sohail, Marwa Qaraqe

Research output: Chapter in Book/Report/Conference proceedingConference contribution

1 Citation (Scopus)

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.
Original languageEnglish
Title of host publication2021 International Conference on Content-Based Multimedia Indexing (CBMI)
PublisherIEEE
Number of pages4
ISBN (Electronic)9781665442206
ISBN (Print)9781665442213
DOIs
Publication statusPublished - 24 Jun 2021
Event18th International Conference on Content-Based Multimedia Indexing - Online
Duration: 28 Jun 202130 Jun 2021
https://cbmi2021.univ-lille.fr/ (Link to conference website)

Publication series

Name
ISSN (Print)1949-3983
ISSN (Electronic)1949-3991

Conference

Conference18th International Conference on Content-Based Multimedia Indexing
Abbreviated titleCBMI 2021
Period28/06/2130/06/21
Internet address

Keywords

  • Diabetes management
  • food recognition
  • continuous glucose monitoring
  • middle-eastern food

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