Simultaneously Concentrated PSWF-based Synchrosqueezing S-transform and its application to R peak detection in ECG signal

Neha Singh, Puneesh Deora, P. M. Pradhan
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引用次数: 2

Abstract

Time-frequency (TF) analysis through well-known TF tool namely S-transform (ST) has been extensively used for QRS detection in Electrocardiogram (ECG) signals. However, Gaussian window-based conventional ST suffers from poor TF resolution due to the fixed scaling criterion and the long taper of the Gaussian window. Many variants of ST using different scaling criteria have been reported in literature for improving the accuracy in the detection of QRS complexes. This paper presents the usefulness of zero-order prolate spheroidal wave function (PSWF) as a window kernel in ST. PSWF has ability to concentrate maximum energy in narrow and finite time and frequency intervals, and provides more flexibility in changing window characteristics. Synchrosqueezing transform is a post processing method that improves the energy concentration in a TFR remarkably. This paper proposes a PSWF-based synchrosqueezing ST for detection of R peaks in ECG signals. The results show that the proposed method accurately detects R peaks with a sensitivity, positive predictivity and accuracy of 99.96 %, 99. 96% and 99. 92% respectively. It also improves upon on existing techniques in terms of the aforementioned metrics and the search back range.
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基于集中pswf的同步压缩s变换及其在心电信号R峰检测中的应用
通过著名的时频分析工具s变换(ST)进行时频分析已广泛应用于心电图信号的QRS检测。然而,基于高斯窗的传统ST由于固定的标度准则和高斯窗的较长锥度而导致TF分辨率较差。文献报道了许多使用不同标度标准的ST变体,以提高QRS复合物检测的准确性。本文介绍了零阶球面波函数(PSWF)作为st窗口核的作用。PSWF能够在狭窄和有限的时间和频率区间内集中最大能量,并且在改变窗口特性方面具有更大的灵活性。同步压缩变换是一种显著提高TFR能量集中的后处理方法。本文提出了一种基于pswf的同步压缩ST,用于心电信号R峰的检测。结果表明,该方法能准确地检测出R峰,灵敏度、正预测率和正确率分别为99.96%、99。96%和99。92%。它还在上述指标和搜索返回范围方面改进了现有技术。
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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