Cluster analysis framework for novel acoustic catheter stethoscope

P. C. Adithya, S. Pandey, R. Sankar, S. Hart, W. Moreno
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引用次数: 1

Abstract

This study presents a cluster analysis framework for acoustic signals of the novel catheter stethoscope. The objective of the current study is to collect the blood flow sounds from a body site of a Yorkshire pig using the novel acoustic catheter stethoscope and further recognize any changes in the sinus rhythm patterns. Initially the collected blood flow sounds are preprocessed with noise cancellation and wavelet source separation to result in acoustic heart and respiratory pulses. Then, the extracted acoustic heart pulses are post processed to recognize the patterns of the sinus rhythm based on a novel feature extraction technique and cluster analysis. Finally, the developed framework is qualitatively and quantitatively validated by providing visual results of the clustering and by computing the clustering accuracy, sensitivity and specificity. The cross validation results show that the developed framework consistently recognizes the patterns of the sinus rhythms with an accuracy rate of 94.37%.
新型导管听诊器的聚类分析框架
本研究提出一种新型导管听诊器声信号的聚类分析框架。当前研究的目的是使用新型听诊器从约克郡猪的身体部位收集血流声音,并进一步识别窦性节律模式的任何变化。首先对采集到的血流声进行噪声消除和小波源分离预处理,得到心、呼吸声脉冲。然后,基于一种新的特征提取技术和聚类分析,对提取的心电脉冲进行后处理,识别窦性心律模式。最后,通过提供聚类的可视化结果以及计算聚类的准确性、灵敏度和特异性,对所开发的框架进行定性和定量验证。交叉验证结果表明,该框架对窦性心律模式的识别准确率为94.37%。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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