Development of a Cost-Effective Portable Diabetes Monitoring Device for Sub-Saharan Africa

Diabetes mellitus, a chronic medical condition characterized by high blood glucose levels, affects more than 24 million individuals in Sub-Saharan Africa. The lack of cost-effective glucose monitoring devices worsens this crisis. Our work introduces GlucoVision, a diabetes monitoring device for this region. GlucoVision utilizes near-infrared (NIR) spectroscopy within a durable wristwatch to non-invasively monitor glucose levels. A K-Nearest Neighbors model demonstrated an average error of $\mathbf{2. 4 5 \%}$, making the model promising for implementation. Cost analysis was performed to calculate a baseline cost of ${\$}$ 13.27. Additionally, a proof-of-concept was created and produced proper results, demonstrating the promise of using the proposed materials.

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Published
2024-10-11
DOI
https://doi.org/10.1109/urtc65039.2024.10937576
Primary Topic
Artificial Intelligence in Healthcare
Type
article
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article

Development of a Cost-Effective Portable Diabetes Monitoring Device for Sub-Saharan Africa

Senthilvel Vasudevan, Daniel Park, Sreesamhitha Bhamidipati, Sanjit Kakarla et al.
Artificial Intelligence in Healthcare
article

Development of a Cost-Effective Portable Diabetes Monitoring Device for Sub-Saharan Africa

Senthilvel Vasudevan, Daniel Park, Sreesamhitha Bhamidipati, Sanjit Kakarla, Gajan Mohan Raj, Weronika Wasniowska
article en

Abstract

Diabetes mellitus, a chronic medical condition characterized by high blood glucose levels, affects more than 24 million individuals in Sub-Saharan Africa. The lack of cost-effective glucose monitoring devices worsens this crisis. Our work introduces GlucoVision, a diabetes monitoring device for this region. GlucoVision utilizes near-infrared (NIR) spectroscopy within a durable wristwatch to non-invasively monitor glucose levels. A K-Nearest Neighbors model demonstrated an average error of $\mathbf{2. 4 5 \%}$, making the model promising for implementation. Cost analysis was performed to calculate a baseline cost of ${\$}$ 13.27. Additionally, a proof-of-concept was created and produced proper results, demonstrating the promise of using the proposed materials.

Rutgers, The State University of New Jersey (US)
Openalex Percentile: Top 61%
Artificial Intelligence in Healthcare
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