SPIROMETER BASED LUNG DISEASE DETECTION USING MACHINE LEARNING ALGORITHM

  • N. Bhuvaneswari,Dr. Kirupa Ganapathy

Abstract

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.

Published
2020-04-13
How to Cite
N. Bhuvaneswari,Dr. Kirupa Ganapathy. (2020). SPIROMETER BASED LUNG DISEASE DETECTION USING MACHINE LEARNING ALGORITHM. International Journal of Advanced Science and Technology, 29(6s), 2447-2451. Retrieved from http://sersc.org/journals/index.php/IJAST/article/view/11910