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Intelligent diagnosis method of cardiovascular anomalies using medical signal processing

机译:医疗信号处理心血管异常智能诊断方法

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Several studies have been performed on medical signal processing with the aim of enriching the table in diagnosis of heart disease. These signals include the ECG signal (electrocardiogram), ICG signal (impedance cardiogram), Doppler signal, phonocardiogram signal... However, the majority of the work in this area remains targeted on a specific signal type and are often reduced to limited or incomplete analysis methods. The objective of this work is to perform an intelligent method of non invasive and automatic diagnosis based on the processing of the ICG corresponding to the aorta impedance variation and the ECG signal during the heart cycle activity. Our method permits to perform automatic diagnosis of the cardiovascular anomalies via a graphical interface using Matlab. Automatic diagnosis method consists on preparing, first, a data base with a set of temporal spectral and cepstral parameters of different ICG and ECG according to different cardiac diseases. This data base is composed from n classes Yk corresponding to n diseases. The classification of anonymous individuals is based on the use of Fischer formula. The major interest of this method is its especially useful for the exploration of cardiovascular system anomalies for emergency cases, children, elderly and pregnant women who can't support surgical operations especially at the level of the heart.
机译:对医学信号处理进行了几项研究,目的是富集表患者心脏病的诊断。这些信号包括ECG信号(心电图),ICG信号(阻抗心电图),多普勒信号,语音心动图信号......然而,该区域的大部分工作仍然在特定信号类型上持有,并且通常减少到有限或不完整分析方法。本作作品的目的是基于对应于心脏循环活动期间对应于主动脉阻抗变化和ECG信号的ICG的处理来执行非侵入性和自动诊断的智能方法。我们的方法允许通过使用MATLAB的图形界面来对心血管异常进行自动诊断。自动诊断方法在于制备,首先是具有不同ICG和ECG的一组时间谱和倒谱参数的数据库,根据不同的心脏病。此数据库由与N疾病对应的N类YK组成。匿名个人的分类基于使用费舍公式。这种方法的主要兴趣是其对急诊病例,儿童,老年人和孕妇的心血管系统异常探索特别有用,特别是在内心的水平上。

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