| Summary: | Glucose serves as the primary energy source for the human body, derived predominantly
from carbohydrates in our daily diet. It plays a crucial role in fuelling various physiological
processes, including cellular metabolism and brain function. Maintaining optimal glucose
levels is vital for health, as both high and low levels can lead to serious consequences.
However, in today's market, adulterated foods often contain hidden sugars and harmful
additives, complicating efforts to manage daily sugar intake effectively. This study aims to
explore the potential of using smartphones for self-monitoring glucose sensing using nearinfrared
(NIR) light emitting diodes (LEDs) at 940 (nanometres) nm as a light source, coupled
with ImageJ for RGB colorimetric analysis. Samples with varying glucose concentrations were
prepared across two ranges: high (0-100 g/dL, increment of 10 g/dL) and low (0-300 mg/dL,
increment of 50 mg/dL). The images of each sample, placed in a small enclosed black
container, were captured using a CMOS smartphone camera with fixed camera settings. The
sensitivity of the method is evaluated by analysing the slope and the regression coefficient (R²)
of the calibration curve. The calibration curves consistently confirm that the proposed method
aligns with the Beer-Lambert law, in accordance with expectations with previous studies. A
high sensitivity in detecting high concentrations of glucose can be demonstrated well compared
to low concentrations range, potentially due to inconsistencies during sample preparation,
minor motions of the instruments, or fluctuations in ambient light throughout each take
affecting the fluctuation of the data points. The study underscores the applicability and
feasibility of quantitative glucose analysis using ImageJ and smartphones as cost-effective
alternatives to traditional methods involving expensive reagents and enzymes. The developed
workflow, involving image processing and analysis, offers simplicity and speed in glucose
concentration assays. In conclusion, this study highlights the possibility of using smartphone
technology as an affordable colorimetry detector for precise and convenient glucose
monitoring. Through the removal of costly colorimetric compounds, this method tackles the
issues associated with contemporary eating habits and enhances methods for managing health.
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