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R Peak Detection Method Using Wavelet Transform and Modified Shannon Energy Envelope

机译:小波变换和改进的香农能量包络的R峰值检测方法

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Rapid automatic detection of the fiducial points—namely, the P wave, QRS complex, and T wave—is necessary for early detection of cardiovascular diseases (CVDs). In this paper, we present an R peak detection method using the wavelet transform (WT) and a modified Shannon energy envelope (SEE) for rapid ECG analysis. The proposed WTSEE algorithm performs a wavelet transform to reduce the size and noise of ECG signals and creates SEE after first-order differentiation and amplitude normalization. Subsequently, the peak energy envelope (PEE) is extracted from the SEE. Then, R peaks are estimated from the PEE, and the estimated peaks are adjusted from the input ECG. Finally, the algorithm generates the final R features by validating R-R intervals and updating the extracted R peaks. The proposed R peak detection method was validated using 48 first-channel ECG records of the MIT-BIH arrhythmia database with a sensitivity of 99.93%, positive predictability of 99.91%, detection error rate of 0.16%, and accuracy of 99.84%. Considering the high detection accuracy and fast processing speed due to the wavelet transform applied before calculating SEE, the proposed method is highly effective for real-time applications in early detection of CVDs.
机译:快速自动检测基准点(即P波,QRS络合物和T波)对于早期检测心血管疾病(CVD)是必需的。在本文中,我们提出了一种使用小波变换(WT)和改​​进的Shannon能量包络(SEE)的R峰检测方法,用于快速ECG分析。提出的WTSEE算法执行小波变换以减小ECG信号的大小和噪声,并在一阶微分和幅度归一化后创建SEE。随后,从SEE中提取峰能包络(PEE)。然后,从PEE估计R个峰值,并从输入ECG调整估计的峰值。最后,该算法通过验证R-R间隔并更新提取的R峰值来生成最终的R特征。利用MIT-BIH心律失常数据库的48条第一通道ECG记录验证了所提出的R峰检测方法,灵敏度为99.93%,阳性可预测性为99.91%,检测错误率为0.16%,准确度为99.84%。考虑到在计算SEE之前应用小波变换具有较高的检测精度和较快的处理速度,因此该方法对于CVD的早期检测中的实时应用非常有效。

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