Domazet Ervin, Gusev Marjan
Technol Health Care. 2019;27(6):623-642. doi: 10.3233/THC-181589.
We analyzed several QRS detection algorithms in order to build a quality industrial beat detector, intended for a small, wearable, one channel electrocardiogram sensor with a sampling rate of 125 Hz, and analog-to-digital conversion of 10 bits. The research was a lengthy process that included building several hundred rules to cope with the QRS detection problems and finding an optimal threshold value for several parameters. We obtained 99.90% QRS sensitivity and 99.90% QRS positive predictive rate measured on the first channel of rescaled and resampled MIT-BIH Arrhythmia ECG database. Even more so, our solution works better than the algorithms for the original signals with a sampling rate of 360 Hz and analog-to-digital conversion of 11 bits.
我们分析了几种QRS检测算法，以构建一个高质量的工业节拍检测器，该检测器适用于一个小型、可穿戴的单通道心电图传感器，其采样率为125Hz，模数转换为10位。这项研究是一个漫长的过程，包括建立数百条规则来处理QRS检测问题，并为几个参数找到最佳阈值。在重新缩放和重新采样的MIT-BIH心律失常心电图数据库的第一通道上测量，我们获得了99.90%的QRS灵敏度和99.90%的QRS阳性预测率。更重要的是，我们的解决方案比采样率为360Hz、模数转换为11位的原始信号算法效果更好。
