A Non-invasive Blood Glucose Detection System Based on Photoplethysmogram with Multiple Near-infrared Sensors.
IEEE J Biomed Health Inform
; PP2024 Aug 14.
Article
en En
| MEDLINE
| ID: mdl-39141451
ABSTRACT
Recent advancements in non-invasive blood glucose detection have seen progress in both photoplethysmogram and multiple near-infrared methods. While the former shows better predictability of baseline glucose levels, it lacks sensitivity to daily fluctuations. Near-infrared methods respond well to short-term changes but face challenges due to individual and environmental factors. To address this, we developed a novel fingertip blood glucose detection system combining both methods. Using multiple light sensors and a lightweight deep learning model, our system achieved promising results in oral glucose tolerance tests. A total of 10 participants were involved in the study, each providing approximately 700 data segments of about 10 seconds each. With a root mean squared error of 0.242 mmol/L and 100% accuracy in zone A of the Parkes error grid, our approach demonstrates the potential of multiple near-infrared sensors for non-invasive glucose detection.
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1
Colección:
01-internacional
Base de datos:
MEDLINE
Idioma:
En
Revista:
IEEE J Biomed Health Inform
Año:
2024
Tipo del documento:
Article
Pais de publicación:
Estados Unidos