Spirometry Data Analysis and Classification Using Data Mining: An Approach
Kamlesh A. Waghmare, Prashant N. Chatur · 2013
milind.btk gmail.com Abstract- In this paper, the acquisition of Spirometry data such as Forced Expiratory Volume in 1 second (FEV1), Force Vital Capacity (FVC) and Small Vital Capacity will be carried out using Spirometer. At current, numbers of lung diseases are main hazard to the human health due to air pollution, smoking and other infections. The various Artificial Neural Network methods for the taxonomy of Spirometry data are Back Propagation Network (BPN), Radial Basis Function (RBF) and Multilayer Perceptron Neural Network (MLPNN). The aim of the present study is to acquire parameter such as FVC, FEV1 and SVC data and use Data Mining Algorithm for classification of the Spirometer data into Normal, Obstructive and Restrictive dataset. This approach is used to increase the efficiency of classification