Analyn N. Yumang
ABSTRACT
Azotemia is a disease that is easy to be treated, but when left undiagnosed and untreated could lead to more fatal diseases like those of Kidney failure or Renal Diseases. Azotemia is a common disease; however, the lack of information from urinalysis showed to be one of the problems, detecting Azotemia thru urinalysis could prevent more hazardous diseases to develop. This study aims to gather more information about Azotemia through urinalysis using Electronic Nose and help diagnose Azotemia faster using urinalysis. Based from the result, The Electronic Nose system proved that there is a difference on the odor of a Healthy Urine sample and an Azotemic Urine sample. The Electronic Nose is made of common MQ Gas sensors and Raspberry Pi for its hardware, while for its software the system used Principal Component Analysis. Using the E-Nose chamber the system gathers data from the pre-classified urine sample provided by the hospital to test and differentiate the Azotemic urine and Healthy urine. The result shows that there are four sensors that are very responsive to the system namely: Combustible Gas, Carbon Monoxide, Hydrogen Gas and Air Quality. Based from the result the system has an accuracy of 90% and an error rate of 10%. In conclusion, the researches successfully developed a system that can differentiate Healthy Urine to an Azotemic Urine sample using Electronic Nose System with Principal Component Analysis.
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Index Terms
- Application of Electronic Nose for Diagnosing Azotemia from Urinalysis Using Principal Component Analysis
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