Abstract
Skilled cardiologists probe heart sounds by electronic stethoscope through human ears, but interpretations of heart sounds is a very special skill which is quite difficult to teach in a structured way. Because of this reason, automatic heart sound analysis in computer systems would be very helpful for medical staffs. This paper presents a complete heart sound analysis system covering from the segmentation of beat cycles to the final determination of heart conditions. The process of heart beat cycle segmentation includes autocorrelation for predicting the cycle time of a heart beat. The feature extraction pipeline includes stages of the short-time Fourier transform, the discrete cosine transform, and the adaptive feature selection. Many features are extracted, but only a few specific ones are selected for the classification of each hyperplane based on a systematic approach. The experiments are done by a public heart sound database released by Texas Heart Institute. A very promising recognition rate has been achieved.
| Original language | English |
|---|---|
| Pages (from-to) | 6458-6468 |
| Number of pages | 11 |
| Journal | Expert Systems with Applications |
| Volume | 38 |
| Issue number | 6 |
| DOIs | |
| Publication status | Published - 2011 Jun |
Keywords
- 2-D discrete cosine transform
- Adaptive feature extraction
- Phonocardiogram (PCG)
- Short-time Fourier transform
- Support vector machines (SVMs)
ASJC Scopus subject areas
- General Engineering
- Computer Science Applications
- Artificial Intelligence
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