基于自适应滤波的心电图中呼吸信号的提取方法

目的: 利用基于递归最小二乘(recursive least-square, RLS)算法的自适应滤波器对心电图信号进行滤波,提取心电信号中的呼吸信号. 方法: 通过对常规的肢体导联心电检测设备获取的心电信号进行处理,提取心电特征信号R波幅度序列和R波间期序列作为自适应滤波器的原始输入信号和参考信号,通过RLS算法的自适应滤波,提取心电图中调制的呼吸分量. 结果: 经过时、频域分析,自适应滤波后估算出的呼吸信号与真实的呼吸信号在时域和频域都显示出了良好的相关性. 结论: 本方法设计合理,结果准确可靠,是一种简便高效、无创、低成本的呼吸监护手段.

Method for deriving respiratory signal from ECG signal based on adaptive filtering

AIM: To design a new method to extract the respiratory signal from the ECG signal by adaptive filtering based on the recursive least-square (RLS) algorithm. METHODS: After processing the ECG signal, we selected the R-wave amplitude sequence and the R-R interval sequence as the primary input and the reference input of the adaptive filter based on the recursive least-square (RLS) algorithm to estimate the respiratory signal. RESULTS: The estimated respiratory signal obtained by the adaptive filter showed well pertinence in time domain and frequency domain to the real respiratory signal. CONCLUSION: The method for deriving respiratory signal from ECG signal based on the adaptive filtering is well designed and the result is reliable. It is a highly efficient, non-invasive and low-cost approach for the respiration detection.