Nakai Yozaburo, Izumi Shintaro, Nakano Masanao, Yamashita Ken, Fujii Takahide, Kawaguchi Hiroshi, Yoshimoto Masahiko
Annu Int Conf IEEE Eng Med Biol Soc. 2014;2014:34-7. doi: 10.1109/EMBC.2014.6943522.
This paper describes a robust method for heart beat detection from noisy electrocardiogram (ECG) signals. Generally, the QRS-complex of heart beat is extracted from the ECG using a threshold. However, in a noisy condition such a mobile and wearable bio-signal monitoring system, noise increases the incidence of misdetection and false detection of QRS-complex. To prevent incorrect detection, we introduce a novel template matching algorithm. The template waveform can be generated autonomously using a short-term autocorrelation method, which leverages the similarity of QRS-complex waveforms. Simulation results show the proposed method achieves state-of-the-art noise tolerance of heart beat detection.
本文描述了一种从噪声心电图（ECG）信号中进行心跳检测的稳健方法。一般来说，心跳的QRS复合波是通过阈值从心电图中提取的。然而，在诸如移动和可穿戴生物信号监测系统这样的噪声环境中，噪声会增加QRS复合波误检测和假检测的发生率。为了防止错误检测，我们引入了一种新颖的模板匹配算法。模板波形可以使用短期自相关方法自主生成，该方法利用了QRS复合波波形的相似性。仿真结果表明，该方法实现了心跳检测的最新噪声容限。
