听诊器
噪音(视频)
冠状动脉疾病
自回归模型
计算机科学
心脏病学
医学
人工智能
数学
放射科
统计
图像(数学)
作者
Samuel Emil Schmidt,Claus Holst‐Hansen,Claus Graff,Egon Toft,Johannes J. Struijk
标识
DOI:10.1109/cic.2007.4745596
摘要
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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