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Evaluation of Energy Power Spectral Distribution of QRS Complex for Detection of Cardiac Arrhythmia

机译:评估QRS复合物检测心律失常的能量功率谱分布

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The proposed approach involves detection of QRS complex and energy power spectral distribution analysis of the segmented QRS complex to establish the presence of arrhythmic beats in Electrocardiogram (ECG). The methods consist of three steps: (ⅰ) the baseline drift and high-frequency artifacts could seriously affect the detection performance, so Moving Average Filtering (MAF) and Stationary Wavelet Transform (SWT) are implemented at preprocessing stage, (ⅱ) Localization of R-peaks by implementing FFT-based windowing and thresholding techniques. Then Q and S points are detected using search interval method based on the medical definition, (ⅲ) The segmented QRS complex is analyzed with period-gram and Continuous Wavelet Transform using FFT (CWTFT) to obtain time-frequency domain power and energy of the complex, (ⅳ) Statistical analysis has been proposed using one-way ANOVA to differentiate the healthy and arrhythmic QRS complex. The proposed QRS detection and analysis methodologies are evaluated with MIT-BIH Arrhythmia Database (MITDB) and FANTASIA database. The detection performance, i.e., Sensitivity S_e(%) and the Specificity S_p(%) for FANTASIA 100% each respectively, where as S_e = 100% and S_p = 98.18% for MITD. The failed detection percentage, F_d(%) = 0 for FANTASIA and F_d(%) = 1.85% for MITDB. The energy power distributed parameters obtained from PSD and CWTFT are statistically analyzed with one-way ANOVA and the p-value are found to be <0.05 (i.e., CI = 95%) for healthy and arrhythmia QRS complex which certainly signifies that the energy power features of the arrhythmic QRS complex are different than the normal QRS complex.
机译:该方法涉及检测分段QRS复合物的QRS复合物和能量功率谱分布分析,以建立心电图(ECG)中心律失常节拍的存在。该方法包括三个步骤:(Ⅰ)基线漂移和高频工件可能会严重影响检测性能,因此在预处理阶段实现移动平均滤波(MAF)和固定小波变换(SWT),(Ⅱ)定位通过实现基于FFT的窗口和阈值化技术来峰值。然后使用基于医学定义的搜索间隔方法检测Q和S点,(Ⅲ)使用FFT(CWTFT)与周期克和连续小波变换分析分段QRS复合物,以获得时间频域功率和能量复杂,(ⅳ)使用单向ANOVA提出了统计分析,以区分健康和心律失常的QRS复合物。所提出的QRS检测和分析方法评估了MIT-BIH心律失常数据库(MITDB)和Fantasia数据库。分别为幻想100%的检测性能,即敏感性S_E(%)和特异性S_P(%),其中MIT的S_E = 100%和S_P = 98.18%。对于幻想的检测百分比,f_d(%)= 0,用于MITDB的F_D(%)= 1.85%。从PSD和CWTFT获得的能量分布式参数用单向ANOVA统计分析,并且发现p值为健康和心律失常QRS复合物的<0.05(即,CI = 95%),这肯定意味着能量力量心律失常QRS复合物的特征与正常QRS复合物不同。

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