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 to detect any type of disease in the earlier stage. The effective way to detect lung disease prior is by using spirometer. Spirometer measures the flow rate and amount of air blown into the device. This work consists of two phases: In the first phase, the flow rate and amount of air blown into device is calculated by using differential pressure transducer and microcontroller. The pressure transducer which senses the difference in air pressure, microcontroller transfers the data to LCD. This is to identify the abnormality in patient. The abnormality is displayed on the LCD screen. If there exists any abnormality, the second phase is implemented by using decision tree algorithm. In second phase the prediction of particular lung disease can be identified by entering symptoms. Python programming is used for processing the data sets through machine learning algorithm. The obtained results show that it is an effective method for lung disease identification.