Application of smartphone-based biophotonic instrumentation for glucose sensing using colorimetric method
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...
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| Format: | Monograph |
| Language: | English |
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Universiti Sains Malaysia
2024
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| Online Access: | http://eprints.usm.my/61363/1/Nur%20Ainin%20Sofhia%20Nurul%20Azlan-E.pdf |
| _version_ | 1824451890260213760 |
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| author | Azlan, Nur Ainin Sofhia Nurul |
| author_facet | Azlan, Nur Ainin Sofhia Nurul |
| author_sort | Azlan, Nur Ainin Sofhia Nurul |
| collection | USM |
| description | 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. |
| first_indexed | 2025-02-19T02:41:49Z |
| format | Monograph |
| id | usm.eprints-61363 |
| institution | Universiti Sains Malaysia |
| language | English |
| last_indexed | 2025-02-19T02:41:49Z |
| publishDate | 2024 |
| publisher | Universiti Sains Malaysia |
| record_format | dspace |
| spelling | usm.eprints-613632025-01-06T07:46:27Z http://eprints.usm.my/61363/ Application of smartphone-based biophotonic instrumentation for glucose sensing using colorimetric method Azlan, Nur Ainin Sofhia Nurul R Medicine RC71-78.7 Examination. Diagnosis Including raiography 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. Universiti Sains Malaysia 2024-06 Monograph NonPeerReviewed application/pdf en http://eprints.usm.my/61363/1/Nur%20Ainin%20Sofhia%20Nurul%20Azlan-E.pdf Azlan, Nur Ainin Sofhia Nurul (2024) Application of smartphone-based biophotonic instrumentation for glucose sensing using colorimetric method. Project Report. Universiti Sains Malaysia. (Submitted) |
| spellingShingle | R Medicine RC71-78.7 Examination. Diagnosis Including raiography Azlan, Nur Ainin Sofhia Nurul Application of smartphone-based biophotonic instrumentation for glucose sensing using colorimetric method |
| title | Application of smartphone-based biophotonic instrumentation
for glucose sensing using colorimetric method |
| title_full | Application of smartphone-based biophotonic instrumentation
for glucose sensing using colorimetric method |
| title_fullStr | Application of smartphone-based biophotonic instrumentation
for glucose sensing using colorimetric method |
| title_full_unstemmed | Application of smartphone-based biophotonic instrumentation
for glucose sensing using colorimetric method |
| title_short | Application of smartphone-based biophotonic instrumentation
for glucose sensing using colorimetric method |
| title_sort | application of smartphone based biophotonic instrumentation for glucose sensing using colorimetric method |
| topic | R Medicine RC71-78.7 Examination. Diagnosis Including raiography |
| url | http://eprints.usm.my/61363/1/Nur%20Ainin%20Sofhia%20Nurul%20Azlan-E.pdf |
| work_keys_str_mv | AT azlannuraininsofhianurul applicationofsmartphonebasedbiophotonicinstrumentationforglucosesensingusingcolorimetricmethod |