Department of Multimedia, Chonnam National University, 50 Daehak-ro, Yeosu, Jeollanamdo 59626, Republic of Korea.
Department of Software, Gachon University, 1342 Seongnam-daero, Sujeong-gu, Seongnam, Gyeonggido 13120, Republic of Korea.
J Healthc Eng. 2017;2017:4901017. doi: 10.1155/2017/4901017. Epub 2017 Jul 5.
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.
快速自动检测基准点——即 P 波、QRS 波群和 T 波——对于早期发现心血管疾病（CVD）至关重要。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 波峰检测方法，用于快速心电图分析。所提出的 WTSEE 算法对 ECG 信号进行小波变换以减小其大小并降低噪声，并在一阶微分和幅度归一化后创建 SEE。然后，从 SEE 中提取峰能量包络（PEE）。然后，从 PEE 中估计 R 波峰，并从输入 ECG 中调整估计的波峰。最后，该算法通过验证 R-R 间隔和更新提取的 R 波峰来生成最终的 R 特征。使用 MIT-BIH 心律失常数据库的 48 个第一通道 ECG 记录对所提出的 R 波峰检测方法进行了验证，其灵敏度为 99.93%，阳性预测率为 99.91%，检测误差率为 0.16%，准确率为 99.84%。考虑到在计算 SEE 之前应用小波变换可以实现高检测精度和快速处理速度，因此该方法非常适用于 CVD 早期检测的实时应用。
