Application of multipoint auscultation for heart sound diagnostic system (MAHDS)

• Published in: 2012 11th International Conference on Information Science, Signal Processing and their Applications, ISSPA 2012
• Main Author: Sh-Hussain H.; Salleh S.-H.; Ariff A.K.; Alhamdani O.; Tian-Swee T.; Noor A.M.; Oemar H.; Yusoff K.
• Format: Conference paper
• Language: English
• Published: 2012
• Online Access: https://www.scopus.com/inward/record.uri?eid=2-s2.0-84868581516&doi=10.1109%2fISSPA.2012.6310669&partnerID=40&md5=bb22e21645bc35298b04043613b0075f

Humans are different in many ways: fat or thin, young or old, sick or healthy; they may differ in auscultation sites which may vary according to the patient's anatomy. Emphasis must be placed on the characteristics of heart sound based on its intensity which greatly depends on the location of the stethoscope to its pericardium. Each one of these areas will emphasize certain characteristics components of the heart sound. Grouping of the first heart sound (lub) is called the S 1 features while the second heart sound (dub) is called the S 2 features, the systolic or diastolic features are important factor to determine the types of murmurs. To this end, studies have been limited to reflect on the development and evaluation methods in order to detect the various components constituting signal of the heart sound at one specific auscultation point. The principle area of interest in this paper is, however placing the stethoscope at the semi lunar valve called aortic as position one and pulmonary as position two which will provide better quality of the S 2 sound. The S 1 heart sound can be heard more clearly in the atroventricle (AV) where the mitral valve as position three and tricuspid valve as position four. Comparative experiments with respect to MFCC feature, different number of HMM states and different number of gaussian mixtures were investigated to measure the influence of these factors on the classification performance at the four locations of auscultation of the heart sound. Interestingly, a five-state model outperformed the four-state model which was supposed to model the four basic components of the heart sounds. It can be said, a five-state average over all Gaussian mixtures model and at the four locations provide the best overall performance of 90.1% accuracy. © 2012 IEEE.