目的:设计并实现一种适用于便携式心电监护系统的心电波形实时动态检测和分析的方法.方法:作者首先应用5点平滑滤波消除信号的高频噪声和50 Hz干扰,然后通过对分段心电信号的长度变换来增强R波,并用长度阈值检测到R波位置,再通过去错检和查漏检算法提高R波检测准确率;正确检测到R波后,利用区域极值和斜率突变特点从R波开始向前、向后搜索找出Q、S波,然后从已开始的Q、S波位置再分别向前向后找到Q波起点和S波终点;最后根据已检测到的QRS波群计算了心率和ST段参数.结果:通过对包含各种噪声的心电信号的分析证明该算法能准确地检测到QRS波群,不受基线漂移和高频噪声的影响;算法用C语言实现后在嵌入式心电监护系统中的应用也表明其处理速度完全满足移动设备的实时动态分析要求.结论:本文设计的心电波形识别方法算法简单、速度快、抗干扰能力强、准确率高,并成功应用于基于32位嵌入式系统的心电监护仪.相信能给便携式心电监护设备研发中心电信号自动检测和分析功能的实现带来一些启发.%To design and implement a real-time ECG detection method for portable ECG monitoring system. Methods: At first, we applied a smooth filter to eliminate the noises of high frequency and power-line interference at 50 Hz. Then we applied a length transform method on ECG sections to strengthen R waves and R positions were detected with a length threshold. We also used improved algorithms to remove the false R positions and find back the leaked ones. To detect S point, a search was made for negative peak in a range of 30 ms after R point. And the offset of QRS wave is the first inflection after S point The Q point and the onset of QRS were detected with same methods. Finally, we calculated the heart rate and ST segment level with those characteristic points. Results: The method could detect QRS waves accurately form noisy ECG signals. The detection reduced the effect of baseline drift and high frequency noises. The algorithm had been implemented on a portable ECG monitor base on embedded technology. It provided on-line real-time analysis and display smoothly. Conclusions: The method for QRS wave detection introduced in this paper is simple, fast and with great anti-interference performance. It is adapted for portable ECG monitoring instruments.
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