Smart Devices for Self-Diagnosing of Lung Condition Based on Body Temperature and Fingernail Color

The aim of this research is to design a smart medical device that is able to provide an initial diagnosis of lung condition based on body temperature and fingernail color. The presence of smart device is needed because the current lung examination is expensive and requires help from medical personnel. Due to the vital function of the lungs, it is necessary to check the lung condition which can be done independently, real-time and at an affordable cost. So if there is a problem in the lungs, it can be detected early and can be treated immediately before the disease becomes more serious. Based on the WHO, there are two lung diseases that cause millions of deaths, that is pneumonia and tuberculosis. The symptoms of both diseases can be known from the body temperature and fingernail color which indicates the oxygen levels in the blood. Temperature and color sensor was used to acquire data from these two parameters. Classification of lung condition based on the data from both sensors was designed using the Naïve Bayes method. There are three classification classes designed, healthy lung, pneumonia and TB. From the test result, the system provides an accuracy of 84.21% in classifying lung condition.