Noor O. Abdul-Kareem,
- Research Scholar University of Thi-Qar Nasiriyah Iraq
Abstract
Recent advancements in non-invasive Near-Infrared (NIR) spectroscopy techniques have significantly improved the detection and measurement of gout, a common form of inflammatory arthritis. Traditional diagnostic methods for gout, such as joint aspiration and crystal analysis, are invasive and can be uncomfortable for patients. In contrast, NIR spectroscopy offers a promising alternative by enabling real-time, non-invasive assessment of uric acid levels and related biomarkers associated with gout. The integration of portable NIR devices and advanced data analytics is paving the way for improved patient outcomes through more accessible and convenient diagnostic options. Spectroscopy and spectral sensing are employed in laboratories to identify and quantify various chemicals present in blood serum. Nevertheless, these techniques are primarily employed with extracted samples, such as blood and urine. This study aims to create a non-invasive method for measuring blood uric acid using a spectral sensor and spectroscopy. The Raspberry Pi 3 B+ is employed to convert the detected light intensity into the concentration of uric acid in this prototype. The light reflected on the individual’s wrist is quantified using a spectral sensor AS7263. The study’s limitations include using spectral sensors to detect light reflectance instead of blood uric acid concentration in mg/dL and relying on linear regression analysis to construct the conversion model. During testing, the prototype demonstrated an average percent difference of 6.61% from the uric acid meter, indicating that a spectral sensor can detect uric acid levels without requiring invasive procedures.
Keywords: NIR, Raspberry, Uric acid, spectroscopy, Spectral sensing device (SSD)
References
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International Journal of Toxins and Toxics
| Volume | |
| Received | August 1, 2024 |
| Accepted | August 14, 2024 |
| Published | September 2, 2024 |