由心电信号提取呼吸信息的算法及其仿真实现

为了使单纯的心电监护设备实现对多种生理信号的检测，减小设备的复杂性，根据心跳频率和呼吸频率处在不同的频段．提出2种由心电信号提取呼吸信息（ECG—derivedrespiratorysignal，EDR）的算法：离散傅里叶变换EDR算法和离散小渡变换EDR算法．利用MATLAB软件在时域和频域分别对这2种算法进行验证，并进行了相关分析比较．经过筛选比较．离散小波变换EDR算法选用coifN小波作为母小波．仿真结果表明，文中所提出的2种算法均能有效地从心电信号中提取出呼吸信息，但离散小波变换EDR算法的准确性与母小波的选取有很大关系．当选取coif3小波时．离散小波变换EDR算法比离散傅立叶变换EDR算法更为有效．

Study and Simulated Implementation of ECG-Derived Respiratory Algorithm

To realize a host of biological signal detection by a simple ECG monitoring equipment, and reduce the complexity of it, two EDR （ECG-derived Respiratory） algorithms are proposed aiming to extract respiratory informa- tion from ECG in accordance with the frequency of heartbeat and respiration in different frequency bands. They are the discrete Fourier transform EDR algorithm and the discrete Wavelet transform EDR algorithm. The simulation ex- periment, the comparison and the correlation analysis of these two algorithms were performed in time domain and fre- quency domain by the MATLAB software. For the discrete Wavelet transform EDR algorithm, coifN Wavelet was se- lected as the mother Wavelet, which has better performance. The experimental results showed that both algorithms can effectively extract respiratory information from the ECG, but the accuracy of the discrete Wavelet transform EDR al- gorithm has much to do with the mother Wavelet. When the coif3 Wavelet is selected, the discrete Wavelet transform EDR algorithm is more effective than the discrete Fourier transform EDR algorithm.