Detection of pathological condition of heart using texture complexity of the heart sound signals in kernel space

Abstract

The heart sound signal is produced due to the mechanical activity of cardiovascular system and hence, it carries relevant information regarding the pathological and non-pathological condition of heart. Physicians listen to heart sounds using a stethoscope device and make interpretation regarding the diseases if any. Hence, its performance depends on the medical practitioners knowledge and experience. In this study, a very simple alternative approach of auscultation technique is introduced for early detection of cardiac abnormality based on a combined framework of kernel space decomposition and textural analysis. The experimental results are validated by physician's diagnosis and statistical analysis. The proposed diagnostic tool can be used in combination with audio clue of heart sound signal to train inexperienced physicians and as an assistive device for experienced doctors. � 2018 IEEE.