文章基本信息

标题：ECG Enhancement and R-Peak Detection Based on Window Variability
本地全文：下载
作者：Lu Wu ; Xiaoyun Xie ; Yinglong Wang 等
期刊名称：Healthcare
电子版ISSN：2227-9032
出版年度：2021
卷号：9
期号：2
页码：227
DOI：10.3390/healthcare9020227
出版社：MDPI Publishing
摘要：In ECG applications, the correct recognition of R-peaks is extremely important for detecting abnormalities, such as arrhythmia and ventricular hypertrophy. In this work, a novel ECG enhancement and R-peak detection method based on window variability is presented, and abbreviated as SQRS. Firstly, the ECG signal corrupted by various high or low-frequency noises is denoised by moving-average filtering. Secondly, the window variance transform technique is used to enhance the QRS complex and suppress the other components in the ECG, such as P/T waves and noise. Finally, the signal, converted by window variance transform, is applied to generate the R-peaks candidates, and the decision rules, including amplitude and kurtosis adaptive thresholds, are applied to determine the R-peaks. A special squared window variance transform (SWVT) is proposed to measure the signal variability in a certain time window, and this technique reduces false detection rate caused by the various types of interference presented in ECG signals. For the MIT-BIH arrhythmia database, the sensitivity of R-peak detection can reach 99.6% using the proposed method.
关键词：ECG; enhancement; R-peaks; squared window variance transform (SWVT); adaptive thresholds ECG ; enhancement ; R-peaks ; squared window variance transform (SWVT) ; adaptive thresholds