|本期目录/Table of Contents|

[1]朱翔宇,姜馨儿,田兆红,等.基于高频中值滤波的小波滤波在脑动脉色素浓度谱特征信号提取中的应用*[J].生物医学工程研究,2020,01:11-17.
　ZHU Xiangyu,JIANG Xiner,TIAN Zhaohong,et al.Application of wavelet filtering based on high frequency median filtering in extracting characteristic signals of pigment concentration spectrum of cerebral artery[J].Journal of Biomedical Engineering Research,2020,01:11-17.
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基于高频中值滤波的小波滤波在脑动脉色素浓度谱特征信号提取中的应用*(PDF)

《生物医学工程研究》[ISSN:1006-6977/CN:61-1281/TN]

期数:
2020年01期
页码:
11-17
栏目:
出版日期:
2020-03-25

文章信息/Info

Title:
Application of wavelet filtering based on high frequency median filtering in extracting characteristic signals of pigment concentration spectrum of cerebral artery
文章编号:
1672-6278 (2020)01-0011 -07
作者:
朱翔宇; 姜馨儿; 田兆红; 修采; 查雨彤△
上海健康医学院 上海穿戴式医疗技术与器械工程研究中心，上海 201318
Author(s):
ZHU Xiangyu;  JIANG Xiner;  TIAN Zhaohong;  XIU Cai;  ZHA Yutong
Shanghai University of Medicine & Health Sciences, Shanghai Wearable Medical Technology and Instrument Engineering Research Center,Shanghai 201318,China
关键词:
近红外光谱技术; 脑动脉色素浓度谱; 光电容积脉搏波; 小波滤波; 中值滤波
Keywords:
Near infrared spectroscopy; Pulse-dye densitometry; Photoplethysmography; Wavelet domain denoising; Median filtering
分类号:
R318
DOI:
10.19529/j.cnki.1672-6278.2020.01.03
文献标识码:
A
摘要:
近年来，近红外光谱技术(mear infrared spectrometry, NIRS)在脑科学研究领域倍受青睐。为了更好地满足参数的后续使用并提取出有效特征信号，前期尝试了多种常用滤波方法，为了解决滤后信号易失真以及不能有效滤除低频或者高频噪声的问题，提出了基于高频中值滤波的小波滤波，并采用高度还原真实信号特点的仿真信号以及利用脑血流动力学参数采集系统获得的真实光电容积脉搏波(photoplethysmography, PPG)信号，基于中值滤波的小波滤波进行分析。将实验测试数据与其他滤波方法的特征信号提取效果进行对比，并对处理数据进行信噪比和频谱分析。结果表明，采用中值滤波与小波滤波相结合的滤波方式，对脑动脉色素浓度谱特征信号进行滤波处理，能获得有效、精准的脑血流动力学参数，为后续的测量精度打下基础。该方法有效结合了中值滤波能够剔除粗差的特性和小波滤波在光电容积脉搏波中有效滤除高斯信号的特性，改善了采用单一方式的局限性，提供了一种新的PPG滤波的思路，对比传统方法更加优化。
Abstract:
Near infrared spectrometry (NIRS) has been widely used in the field of brain science in recent years.In order to better satisfy the follow-up use of parameters and extract the effective characteristic signals, we tried several common filtering methods to solve the problem of easily distorted filtered signals and unable to effectively filter low-frequency or high-frequency noise, a wavelet filtering method based on high-frequency median filtering was proposed, and the simulation signals with high-degree restoration of real signal characteristics and the use of cerebral blood flow were used. The real photoplethysmography (PPG) signal obtained by the mechanical parameter acquisition system was analyzed based on the wavelet filter of median filter. The experimental data were compared with other filtering methods in extracting characteristic signals. The signal-to-noise ratio and spectrum analysis of the processed data were carried out. The results showed that this filtering method combined median filtering with wavelet filtering could filter the characteristic signals of cerebral artery pigmentation spectrum, obtained effective and accurate cerebral hemodynamic parameters, which could be used for subsequent measurement accuracy.This method effectively combined the characteristics of median filtering can eliminate gross errors the filtration of Gauss signal by wavelet filtering in PPG, improves the limitation of using a single method and provides a new idea of PPG filtering, which is more optimized than traditional methods.

参考文献/References

备注/Memo

备注/Memo:
（收稿日期：2019-08-28）2018年教育部产学合作协同育人项目;上海高校青年教师培养资助计划项目（A1-2601-19-311124）;上海健康医学院2019年教学改革专项资助项目。△通信作者Email：zhayt@sumhs.edu.cn
更新日期/Last Update: 2020-04-14