SPIROMETER BASED LUNG DISEASE DETECTION USING MACHINE LEARNING ALGORITHM - N. Bhuvaneswari,Dr. Kirupa Ganapathy (International Journal of Advanced Science and Technology, 2020)
In today’s world lung disease is considered as one of the most common disease. It is important todetect any type of disease in the earlier stage. The effective way to detect lung disease prior is byusing spirometer. Spirometer measures the flow rate and amount of air blown into the device. Thiswork consists of two phases: In the first phase, the flow rate and amount of air blown into device iscalculated by using differential pressure transducer and microcontroller. The pressure transducerwhich senses the difference in air pressure, microcontroller transfers the data to LCD. This is toidentify the abnormality in patient. The abnormality is displayed on the LCD screen. If there existsany abnormality, the second phase is implemented by using decision tree algorithm. In second phasethe prediction of particular lung disease can be identified by entering symptoms. Pythonprogramming is used for processing the data sets through machine learning algorithm. The obtainedresults show that it is an effective method for lung disease identification.