利用ECG信号检测睡眠呼吸暂停的小波包分析方法

Detection of sleep apnea from ECG using wavelet packet transform

文章根据睡眠呼吸暂停与心率变化的关系,阐述了从心电图中检测睡眠呼吸暂停的方法。该方法首先通过对心率信号进行小波包变换,提取特征向量,然后根据特征向量的变化检测出睡眠呼吸暂停的位置和分布。结果表明,该方法物理意义明确,诊断结果精度高,为睡眠呼吸暂停综合症的早期诊断、监护及预后评估提供了新的分析工具。

The article introduces a new method to diagnose sleep apnea from electrocardiograms based on the heart rate signal that are often associated with cycles of sleep apnea. This technique employs wavelet packet transformation of heart rate signal to derive the eigenvector-while the place and the distribution of sleep apnea can be successfully detected according to the change of the eigenvector.The results verify that this method has a clear physical meaning and is of relatively high diagnosing accuracy.It is a new tool of analysis for early diagnosis-monitoring and prognostic assessment of sleep apnea syndrome.