Spirometry Modelling: A New Concept of Post Processing of Traditional Data

Ms. Prachi D. Junwale, Prof. A. W. Bhade, Dr. P. N. Chatur


Respiratory disease is a medical term that encompasses pathological conditions affecting the organs and tissues. A lungs disease affects health condition of many people. Lungs diseases can be curable in early detection. Spirometry is valuable for diagnosing specific lung disorders as well as detecting lung disease at an early stage. Spirometry (the measuring of breath) is the most common of the pulmonary function tests and uses an instrument called a spirometer to measure the amount of air entering and leaving the lungs. This test is often used to help doctors diagnose and determine the severity of various respiratory diseases. The output of spirometry is in the form of graphs i.e. flow-volume loop and volume-time curve. This graph gives various parameters that are used for spirometry modelling. Spirometry modeling gives flow–time curves. This curve is modeled using statistical data mining technique, which is used to obtain new information about breathing condition which makes distinguish between healthy and diseased subjects.

Keywords: respiratory system; lung disorders; spirometry; modelling; statistical data mining.

Full Text:


DOI: https://doi.org/10.26483/ijarcs.v3i1.1017


  • There are currently no refbacks.

Copyright (c) 2016 International Journal of Advanced Research in Computer Science