| 基于经验小波变换的BCG信号提取方法研究 |
投稿时间：2021-04-17 修订日期：2021-05-12  点此下载全文 |
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| 基金项目:北京市教委科研计划资助项目 |
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| 中文摘要:为解决非接触式睡眠监测系统中呼吸和心跳信号的有效分离和准确提取问题，采用经验小波变换手段，根据信号频谱特征利用尺度空间变换实现频域的自适应划分，然后依据频谱划分的边界构造正交小波滤波器组，实现了从所获取的混合压力信号中有效提取出心冲击和呼吸信号等单模态分量。初步实验结果表明，与常规滤波方法相比，该方法具有较高的自适应性和可重复性，且提取出的心冲击信号波形特征更为明显，有利于对心跳时刻进行精确定位。 |
| 中文关键词:睡眠监测 心冲击 经验小波变换 自适应划分 |
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| Research on BCG Signal Extraction Method Based on Expirical Wavelet Transformation |
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| Abstract:Abstract In order to solve the problem of effective separation and accurate extraction of respiratory and heartbeat signals in non-contact sleep monitoring system, the empirical wavelet transform is used to realize the adaptive division of frequency domain by using scale space transform according to the signal spectrum characteristics, and then the orthogonal wavelet filter bank is constructed according to the boundary of spectrum division. In this way the single-mode components such as ballistocardiogram and respiration can be extracted from the mixed pressure signals. The results of the preliminary experiments show that, compared with the conventional filtering method, this method has higher adaptability and repeatability, and the extracted waveform characteristics of cardiac impulse signal are more obvious, which is conducive to accurate positioning of heart beat time. |
| keywords:Sleep Monitoring ballistocardiogram Empirical Wavelet Transformation adaptive division |
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