Key result
An electronic stethoscope using an AR-model with noise artifact removal considerably improved diagnostic performance for detecting coronary artery disease in a test of 50 subjects.
Why the study?
Does an electronic stethoscope with a noise reduction method improve the diagnostic performance for detecting coronary artery disease?
Cross-Sectional (n=50)
Does an electronic stethoscope with a noise reduction method improve the diagnostic performance for detecting coronary artery disease?
A novel noise reduction method for electronic stethoscopes improves the diagnostic performance of acoustic detection of coronary artery disease.
Hypothesis-generating for acoustic CAD detection; larger prospective validation required before clinical adoption.
A noninvasive method for detection of coronary artery disease (CAD) with an electronic stethoscope is proposed. Heart sounds recorded in clinical settings are often contaminated with background noise and noise caused by friction between the skin and the stethoscope. A method was developed to reduce the influence of the noise artifacts. The diastolic parts of the heart sounds were divided into multiple sub-segments, where noisy sub-segments were indentified as sub-segments with a low degree of stationarity or with a high energy level. The sub-segments not identified as noisy were analyzed with an Autoregressive (AR) model, where the pole-magnitude of the 1st pole was used as a discriminating parameter. A test on 50 subjects showed that removal of the noisy sub-segments before analyses improved the diagnostic performance of the AR-model considerably, thereby reducing the influence of noise related to the use of a handhold stethoscope.
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Schmidt et al. (2007) conducted a cross-sectional in Coronary artery disease (n=50). Electronic stethoscope with noise reduction method was evaluated on Diagnostic performance. An electronic stethoscope using an AR-model with noise artifact removal considerably improved diagnostic performance for detecting coronary artery disease in a test of 50 subjects.
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