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Paper-Based Device for the Colorimetric Determination of Glucose in Whole-Blood Samples Using a Smartphone
Lara B A Boga1, Katia Gianni1, Mariano N Aleman2
1Laboratorio de Medios e Interfases (LAMEIN), DBI, FACET, Universidad Nacional de Tucumán, Instituto Superior de Investigaciones Biológicas (INSIBIO), CONICET, Av. Independencia 1800, San Miguel de Tucumán 4000, Argentina.
Bioengineering (Basel, Switzerland)
|November 27, 2025
Summary
This study developed a paper-based device for rapid glucose detection in whole blood. The device enables plasma separation and smartphone-based quantification, aiding diabetes management.
Area of Science:
- Biomedical Engineering
- Analytical Chemistry
- Point-of-Care Diagnostics
Background:
- Clinical diagnostics require rapid, simple, and reliable tools for biomarker detection.
- Paper-based analytical devices (PADs) offer a promising low-cost, rapid testing platform.
- Glucose monitoring is crucial for diabetes diagnosis, management, and complication prevention.
Purpose of the Study:
- To develop an integrated paper-based device for whole blood glucose detection.
- To enable efficient plasma separation within the paper device.
- To facilitate quantitative glucose determination using smartphone technology.
Main Methods:
- Development of a microfluidic paper-based analytical device (μPAD) for integrated plasma separation.
- Colorimetric assay for glucose detection in separated plasma.
- Smartphone-based image analysis for quantitative glucose measurement.
Main Results:
- Successful integration of plasma separation from whole blood on the paper device.
- Demonstrated colorimetric detection of glucose with high sensitivity and specificity.
- Validated smartphone quantification of glucose levels, correlating well with established methods.
Conclusions:
- The developed paper-based device provides a rapid, low-cost, and user-friendly platform for whole blood glucose quantification.
- This technology has the potential for effective point-of-care diabetes monitoring.
- Integration of plasma separation and smartphone analysis enhances diagnostic capabilities for resource-limited settings.

