School of Physics and Technology, Wuhan University, Wuhan 430072, China.
Sensors (Basel). 2020 Jul 18;20(14):4003. doi: 10.3390/s20144003.
As one of the important components of electrocardiogram (ECG) signals, QRS signal represents the basic characteristics of ECG signals. The detection of QRS waves is also an essential step for ECG signal analysis. In order to further meet the clinical needs for the accuracy and real-time detection of QRS waves, a simple, fast, reliable, and hardware-friendly algorithm for real-time QRS detection is proposed. The exponential transform (ET) and proportional-derivative (PD) control-based adaptive threshold are designed to detect QRS-complex. The proposed ET can effectively narrow the magnitude difference of QRS peaks, and the PD control-based method can adaptively adjust the current threshold for QRS detection according to thresholds of previous two windows and predefined minimal threshold. The ECG signals from MIT-BIH databases are used to evaluate the performance of the proposed algorithm. The overall sensitivity, positive predictivity, and accuracy for QRS detection are 99.90%, 99.92%, and 99.82%, respectively. It is also implemented on Altera Cyclone V 5CSEMA5F31C6 Field Programmable Gate Array (FPGA). The time consumed for a 30-min ECG record is approximately 1.3 s. It indicates that the proposed algorithm can be used for wearable heart rate monitoring and automatic ECG analysis.
作为心电图（ECG）信号的重要组成部分之一，QRS 信号代表了 ECG 信号的基本特征。QRS 波的检测也是 ECG 信号分析的重要步骤。为了进一步满足临床对 QRS 波精确和实时检测的需求，提出了一种简单、快速、可靠且对硬件友好的实时 QRS 检测算法。设计了基于指数变换（ET）和比例-微分（PD）控制的自适应阈值来检测 QRS 复合波。所提出的 ET 可以有效地缩小 QRS 峰值的幅度差，而基于 PD 控制的方法可以根据前两个窗口的阈值和预设的最小阈值自适应地调整当前的 QRS 检测阈值。使用 MIT-BIH 数据库中的 ECG 信号来评估所提出算法的性能。QRS 检测的整体灵敏度、阳性预测值和准确率分别为 99.90%、99.92%和 99.82%。该算法还在 Altera Cyclone V 5CSEMA5F31C6 现场可编程门阵列（FPGA）上实现。处理 30 分钟 ECG 记录的时间约为 1.3 秒。这表明所提出的算法可用于可穿戴心率监测和自动 ECG 分析。
