Lung sound classification using multiresolution Higuchi fractal dimension measurement

<span lang="EN-GB">Lung sound is one indicator of abnormalities in the lungs and respiratory tract. Research for automatic lung classification has become interests researchers because disease diseases with most sufferers world. The use sounds as a source information ease data acquisition auscultation standard method examining pulmonary function. This study simulated potential Higuchi fractal dimension (HFD) feature extraction classification. HFD calculations were run on series </span><em><span lang="EN-GB">k</span></em><span lang="EN-GB"> values to generate some features. According simulation results, proposed could produce an accuracy up 97.98% five classes data. results also suggested that shift over selection time interval can be used classification.</span>