A Wireless Electronic Stethoscope to Classify Children Heart Sound Abnormalities

In this research paper, a wireless stethoscope has introduced that can communicate with a smartphone to receive children's heart sound. Along with an automated method that recognizes children heart sound abnormalities. That isolation of heart sound is based on time-frequency characteristics. Where it is preceded using Mel-frequency Cepstral Coefficients (MFCCs) signal processing method. The processed sounds are extracted using five feature extraction algorithms. Then it is classified using four support vector machines (SVM) kernel. Total 60 heart sounds were collected, where 30 sounds having abnormalities and rest 30 sounds containing normal heart sound. Though massive measures of action have already been done in this area, still necessity of more bearable cost device and accurate method is present. Here, the submitted apparatus cost is approximately 18 USD, which is the cheapest than most other device used in previous work. Simultaneously it is lightweight and bearable to use in rural and underprivileged area. With RBF kernel of SVM, the proposed method shows 94.12% accuracy which is the highest.