The bare ear and the stethoscope were until recently of great help in classifying most heart diseases especially those related to valve problems. The newly developed electronic stethoscope and phonocardiography represent useful tools for recording heart sound signals. In this paper a diagnostic technique for heart diseases using heart sounds is suggested. Wavelet decomposition and mel cepstrum are used for feature extraction. Classification of the different heart diseases is then done using hidden Markov models (HMM). Three different techniques have been used and compared. The obtained recognition rates (RR) were 97.3%, 98.2%, and 99.1%
Despite advancement in medical technology throughout the years, cardiovascular diseases remain the l...
Accurate and reliable recognition of fundamental heart sounds (FHSs) plays a significant role in aut...
Digital stethoscopes offer new opportunities for computerized analysis of heart sounds. Segmentation...
This study presents a Computerised Heart Diagnostic System (CHDS) for classifying the different type...
Phonocardiographic signals contain bioacoustic information reflecting the operation of the heart. No...
The work embodied in this dissertation reports the development of an automatic diagnostic system for...
Cardiac disorders are critical and must be diagnosed in the early stage using routine auscultation e...
Cardiac auscultation can be perceived as method of determining the human heart condition by listenin...
Human heart is one of the most important organ in the body and one of the most common diagnosis for...
Heart sound signals are the important asset for heart examination in primary healthcare centers to a...
The future of quick and efficient disease diagnosis lays in the development of reliable non-invasive...
Many heart diseases cause changes in heart sounds and additional murmurs before other signs and symp...
The future of quick and efficient disease diagnosis lays in the development of reliable non-invasive...
This paper is concerned to the segmentation of heart sounds by using state of art Hidden Markov Mode...
The future of quick and efficient disease diagnosis lays in the development of reliable non-invasive...
Despite advancement in medical technology throughout the years, cardiovascular diseases remain the l...
Accurate and reliable recognition of fundamental heart sounds (FHSs) plays a significant role in aut...
Digital stethoscopes offer new opportunities for computerized analysis of heart sounds. Segmentation...
This study presents a Computerised Heart Diagnostic System (CHDS) for classifying the different type...
Phonocardiographic signals contain bioacoustic information reflecting the operation of the heart. No...
The work embodied in this dissertation reports the development of an automatic diagnostic system for...
Cardiac disorders are critical and must be diagnosed in the early stage using routine auscultation e...
Cardiac auscultation can be perceived as method of determining the human heart condition by listenin...
Human heart is one of the most important organ in the body and one of the most common diagnosis for...
Heart sound signals are the important asset for heart examination in primary healthcare centers to a...
The future of quick and efficient disease diagnosis lays in the development of reliable non-invasive...
Many heart diseases cause changes in heart sounds and additional murmurs before other signs and symp...
The future of quick and efficient disease diagnosis lays in the development of reliable non-invasive...
This paper is concerned to the segmentation of heart sounds by using state of art Hidden Markov Mode...
The future of quick and efficient disease diagnosis lays in the development of reliable non-invasive...
Despite advancement in medical technology throughout the years, cardiovascular diseases remain the l...
Accurate and reliable recognition of fundamental heart sounds (FHSs) plays a significant role in aut...
Digital stethoscopes offer new opportunities for computerized analysis of heart sounds. Segmentation...