Objective: Sleep is an important physiological activity of human. It is the basis for reasonable sleep stages to study the sleep quality and diagnose sleep disorders. EEG is the most significant and most intuitive signal in describing sleep, but the EEG signal is very faint, and the amplitude of the random presence of the ECG artifacts is very large. This paper tries to use a simple method to eliminate the ECG artifacts in view of the need of the home sleep health-care on mobile. Methods: By means of R peak detection of the reference ECG signal, we make the R peak position as the reference point of the ECG artifacts in the EEG signal, and then build a template to replace the artifacts. Results: From the time-domain graph and the spectral graph of the processed EEG, we can see that the ECG artifacts have been effectively suppressed. Conclusions: After eliminating the ECG artifacts, the spectral features differences of each Sleep stage are increased, thus, it will be more conducive to the Automatic sleep stage classification.%目的:睡眠是人体重要的生理活动,对睡眠进行合理的分期,是研究睡眠质量诊断,睡眠疾病的基础.脑电是描述睡眠过程中最显著和最直观的信号,但是由于脑电信号本身比较微弱,心电干扰会随机地出现在脑电信号中,本文的主要目的就是基于手机的家庭睡眠分析的需要,设计一种简单的心电抑制算法.方法:通过参考心电信号的R波检测,提取R峰位置,作为脑电信号中的心电干扰的参考点,建立模板来替换脑电信号中的心电伪迹.结果:从处理后的脑电信号的时域图和频谱图可以看出,心电伪迹得到了有效抑制.结论:将原始脑电信号的各频带能量分布和自适应算法以及本文所提出的算法滤除心电伪迹后的能量分布加以比较,可见抑制心电干扰后,睡眠各期的分段谱特征差异性加大,从而更有利于后面的睡眠各期的自动分类.
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