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Automatic phonocardiograph signal analysis for detecting heart valve disorders

机译:自动心音图信号分析,可检测出心脏瓣膜疾病

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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.
机译:熟练的心脏病专家会通过电子听诊器通过人耳探测心音,但是对心音的解释是一项非常特殊的技能,很难以结构化的方式进行讲授。因此,计算机系统中的自动心音分析对医务人员将非常有帮助。本文提出了一个完整的心音分析系统,涵盖了从心跳周期的分割到心脏状况的最终确定。心跳周期分割的过程包括用于预测心跳周期的自相关。特征提取管线包括短时傅立叶变换,离散余弦变换和自适应特征选择的阶段。提取了许多特征,但是基于系统的方法,仅选择了几个特定的​​特征用于每个超平面的分类。实验由德克萨斯心脏研究所发布的公共心音数据库完成。已经实现了非常有希望的识别率。

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