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Enhancement of Recorded Respiratory Sound Using Signal Processing Techniques
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Author(s): Feng Jin (Nanyang Technological University, Singapore)and Farook Sattar (Nanyang Technological University, Singapore)
Copyright: 2009
Pages: 10
Source title:
Encyclopedia of Information Communication Technology
Source Author(s)/Editor(s): Antonio Cartelli (University of Cassino and Southern Lazio, Italy)and Marco Palma (University of Cassino, Italy)
DOI: 10.4018/978-1-59904-845-1.ch039
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Abstract
Pulmonary auscultation has been the key method to detect and evaluate respiratory dysfunctions for many years. However, auscultation with a stethoscope is a subjective process that depends on the individual’s own hearing, experience, and ability to differentiate between different sounds (Sovijarvi et al, 2000). Therefore, the computerized method for recording and analysis of pulmonary auscultative signals, being an objective way, are recently playing a more and more important role in the evaluation of patients with pulmonary diseases. Noise interference is one of the most influential factors when dealing with respiratory sound recordings. By definition of (Rossi et al, 2000), any sound not directly induced by breathing is regarded as background noise (BN). BN is divided into two types: environmental noise, which consists of continuous noise and transient noise, and nonrespiratory sounds and body sounds (muscle contraction sounds, skin friction, and heart sounds). The adaptive filtering is usually used to reduce the background noise. However, the problem of existing proposed filtering methods are either not able to minimize the interference or provides distortion which is especially undesirable for biomedical signals (Donoho, 1992).
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