针对多普勒雷达生命体征检测时强谐波干扰问题,提出一种基于连续小波变换特征提取的改进方法。首先,针对特征信号选择多组不同时间长度的数据集;然后,在小波域分别进行连续小波变换。根据频谱峰值位置是否与数据时间长度相关,识别呼吸信号、呼吸谐波和心跳信号提取心率信息,并对频率分辨率进行分析。实验结果表明:采用文中提出的方法利用4 s~5 s的数据即可检测出心率,当频率分辨率要求为0.1 Hz 时,该方法在有效消除谐波和快速识别心率方面得到了较为满意的效果。

Aiming at the problem of strong harmonic interference in vital signs detection based on Doppler radar, an improved method based on continuous wavelet transform (CWT) feature extraction is proposed. First, multiple sets of data sets with different time lengths are selected for the feature signal, and then CWT is performed in the wavelet domain. Respiratory signals, respiratory harmonics, and heartbeat signals are identified based on whether or not the spectral peak position is independent of the length of the data. On this basis, the heart rate (HR) is extracted and the frequency resolution is analyzed. Experimental result shows that the heartbeat signal can be quickly detected by using the method proposed in this paper using data from 4 s to 5 s. When the frequency resolution requirement is 0. 1 Hz, the multi-data HR extraction method has relatively satisfactory results in effectively eliminating harmonics and quickly identifying the heartbeat signal.

TN957.51

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