首页> 外文期刊>Biomedical Engineering: Applications, Basis and Communications >ASSESSMENT OF CARDIAC HEART FAILURE AND CARDIAC ARTERY DISEASE BY THE HIGHER ORDER SPECTRA
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ASSESSMENT OF CARDIAC HEART FAILURE AND CARDIAC ARTERY DISEASE BY THE HIGHER ORDER SPECTRA

机译:高阶光谱评估心脏心脏衰竭和心动脉疾病

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Cardiac diseases are major reason of death in the world populace and the numeral of cases is upsurging every year. Due to cardiac artery disease (CAD), the strength of heart muscles becomes weak and heart pumping is disturbed which may eventually lead to abnormal heart beat and heart failure. Therefore, the beginning stage detection of CAD and cardiac heart failure (CHF) are of prime importance. In this work, we have used a non-invasive diagnosis method as higher order spectra (HOS) for assessment of cardiac diseases. The method indicates whether or not a cardiac heart disease is present, by assessing the cardiac health of subjects using extracted features from heart rate variability (HRV) signals. This assessment is based on 10 spectra nonlinear features. These features were extracted from HRV signals by using the HOS method. For this study, the R-R interval data (i.e. HRV signals) were taken from the standard database of cardiac heart failure (CHF), CAD patients, healthy young (YNG) and Self recorded of healthy young (SELF_YNG) subjects. Statistical assessments were performed on the group of database sets as YNG-CAD, YNG-CHF, SELF_YNG-CAD and Self_YNG-CHF subjects. A Wilcoxon rank sum test (p-value) was used to statistically compare the features extracted by HOS for group of data sets. It indicates whether or not the same features of individual classes of HRV data sets are dissimilar. The results depicted that the all features are very significant (p<0.0001) except the phase entropy (PHE) feature which is not significant for CAD-CHF, SELF_YNG-CAD and SELF_YNG-CHF group of subjects. While in the case of YNG-CAD group of subjects, features like first-order spectral moment of amplitudes of diagonal elements (H3), PHE and logarithmic amplitudes of diagonal elements (H2) are significant (p<0.001) and excluding these features, the remaining features are very significant except MM and H1 which are not significant. The results also depicted that the mean value of sum of logarithmic amplitude (H1), H2, normalized entropy (P1), normalized squared entropy (P2) and PHE features of healthy YNG subjects are having higher values than that of CAD and CHF patients. While weighted center of bi-spectrum (WCOB2) and FLAT spectrum features are lower than CAD and CHF patients compared to YNG subjects. In case of CAD and CHF patients, all the features of CAD patients are having higher values compared to CHF except P1, P2 and WCOB1.
机译:心脏病是世界群体死亡的主要原因,每年案件的数字都是令人满应的。由于心动疾病(CAD),心肌的强度变得薄弱,心脏泵送受到干扰,可能最终导致心跳异常和心力衰竭。因此,开始阶段检测CAD和心脏心脏衰竭(CHF)是主要的重要性。在这项工作中,我们使用非侵入性诊断方法作为高阶谱(HOS)进行心脏病评估。该方法通过评估来自心率变异性(HRV)信号的提取特征的受试者的心脏健康,指示是否存在心脏病疾病。该评估基于10个光谱非线性特征。通过使用HOS方法从HRV信号中提取这些特征。对于该研究,R-R间隔数据(即HRV信号)是从心脏病(CHF),CAD患者,健康年轻(YNG)和自我记录的健康年轻(Self_yng)科目的自我记录的标准数据库中。统计评估是在数据库组中进行的,作为yng-cad,yng-chf,self_yng-cad和self_yng-chf科目。 Wilcoxon等级和测试(P值)用于统计地比较HOS用于数据集组的功能。它指示单个类别的HRV数据集的相同功能是否不同。结果描绘了除相位熵(PHE)特征外,所有特征都非常显着(P <0.0001),对于CAD-CHF,SELF_YNG-CAD和SELF_YNG-CHF组对象不显着。虽然在YNG-CAD组对象的情况下,但对角线元素(H3)的一阶光谱力矩(H3),PHE和对角线元素的对数振幅(H2)的特征是显着的(P <0.001)并且不包括这些特征,除MM和H1不显着之外,剩余的特征是非常重要的。结果还描绘了对数幅度(H1),H 2,归一化熵(P1),归一化平方熵(P2)和健康YNG受试者的归一化平方熵(P2)和PHE特征的平均值具有比CAD和CHF患者更高的值。与YNG受试者相比,双谱(WCOB2)和平面谱特征的加权中心低于CAD和CHF患者。在CAD和CHF患者的情况下,与P1,P2和WCOB1之外的CHF相比,CAD患者的所有特征都具有更高的值。

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