一种光电容积脉搏信号的峰值点自动识别方法
发布时间：2018-09-07 10:02
【摘要】：光电容积脉搏信号的峰值点自动识别直接关系到无创血氧饱和度测量与脉搏波峰-峰间期提取的准确率。提出一种小波联合识别方法:基于小波多分辨率分析原理校正影响脉搏波峰值点幅值的基线干扰,再利用二次样条小波模极大算法自动识别峰值点。将该方法应用到自行研制的光电容积脉搏波测量系统中,对采集的信号进行了校正与峰值点识别,通过在信号中增加随机噪声以评价方法的稳定性与可靠性,然后利用10组实测数据,对比本方法与传统差分阈值法的峰值点识别准确率,进一步评价方法的有效性。结果表明:本方法在较好地消除了基线干扰的基础上,在染噪的信号中仍然会较精确地检测出脉搏波主波峰,具有较好的抗干扰能力,有利于提高血氧饱和度检测及峰-峰间期提取的准确性,从而有助于后期人体呼吸功能评价与心率变异性分析。
[Abstract]:The automatic recognition of the peak point of the photoelectric volumetric pulse signal is directly related to the accuracy of the measurement of non-invasive oxygen saturation and the extraction of the peak and interpeak phase of the pulse wave. A wavelet joint recognition method is proposed: based on the principle of wavelet multi-resolution analysis, the baseline interference which affects the pulse peak amplitude is corrected, and the peak point is automatically identified by using the quadratic spline wavelet modulus maximum algorithm. The method is applied to the photoelectric volumetric pulse wave measurement system, and the collected signal is corrected and the peak point is identified. The stability and reliability of the method are evaluated by adding random noise to the signal. Then 10 groups of measured data are used to compare the accuracy of peak recognition between this method and the traditional difference threshold method to further evaluate the effectiveness of the method. The results show that on the basis of eliminating the baseline interference, the method can detect the main wave peak of pulse wave accurately in the noisy signal, and has good anti-jamming ability. It is helpful to improve the accuracy of oxygen saturation detection and peak-peak interval extraction, which is helpful to the evaluation of human respiratory function and the analysis of heart rate variability.
【作者单位】： 吉林大学仪器科学与电气工程学院;吉林大学第一医院;
【基金】：国家自然科学基金项目(41674108) 吉林省自然科学基金项目(20140101063JC) 吉林大学研究生创新基金项目(2016211)资助
【分类号】：R318;TN911.7
，
本文编号：2227935
[Abstract]:The automatic recognition of the peak point of the photoelectric volumetric pulse signal is directly related to the accuracy of the measurement of non-invasive oxygen saturation and the extraction of the peak and interpeak phase of the pulse wave. A wavelet joint recognition method is proposed: based on the principle of wavelet multi-resolution analysis, the baseline interference which affects the pulse peak amplitude is corrected, and the peak point is automatically identified by using the quadratic spline wavelet modulus maximum algorithm. The method is applied to the photoelectric volumetric pulse wave measurement system, and the collected signal is corrected and the peak point is identified. The stability and reliability of the method are evaluated by adding random noise to the signal. Then 10 groups of measured data are used to compare the accuracy of peak recognition between this method and the traditional difference threshold method to further evaluate the effectiveness of the method. The results show that on the basis of eliminating the baseline interference, the method can detect the main wave peak of pulse wave accurately in the noisy signal, and has good anti-jamming ability. It is helpful to improve the accuracy of oxygen saturation detection and peak-peak interval extraction, which is helpful to the evaluation of human respiratory function and the analysis of heart rate variability.
【作者单位】： 吉林大学仪器科学与电气工程学院;吉林大学第一医院;
【基金】：国家自然科学基金项目(41674108) 吉林省自然科学基金项目(20140101063JC) 吉林大学研究生创新基金项目(2016211)资助
【分类号】：R318;TN911.7
，
本文编号：2227935
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