[1]李丹,陈兆学.基于视频信号的微血管自律运动频率测量[J].中国医学物理学杂志,2022,39(5):611-616.[doi:DOI:10.3969/j.issn.1005-202X.2022.05.015]
 LI Dan,CHEN Zhaoxue.Frequency measurement of microvascular vasomotion based on video signals[J].Chinese Journal of Medical Physics,2022,39(5):611-616.[doi:DOI:10.3969/j.issn.1005-202X.2022.05.015]
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基于视频信号的微血管自律运动频率测量()
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《中国医学物理学杂志》[ISSN:1005-202X/CN:44-1351/R]

卷:
39卷
期数:
2022年第5期
页码:
611-616
栏目:
医学信号处理与医学仪器
出版日期:
2022-05-27

文章信息/Info

Title:
Frequency measurement of microvascular vasomotion based on video signals
文章编号:
1005-202X(2022)05-0611-06
作者:
李丹陈兆学
上海理工大学健康科学与工程学院医学影像工程研究所, 上海 200093
Author(s):
LI Dan CHEN Zhaoxue
Institute of Medical Imaging Engineering, School?f?ealth?cience?nd?ngineering, University of Shanghai for Science and Technology, Shanghai 200093, China
关键词:
远程光电容积法微循环血管运动小波分解独立成分分析法
Keywords:
Keywords: remote photoplethysmograph microcirculation microvascular motion wavelet decomposition independent component analysis
分类号:
R318
DOI:
DOI:10.3969/j.issn.1005-202X.2022.05.015
文献标志码:
A
摘要:
针对目前微血管运动的检测对设备要求较高,检测时间较长的问题,提出一种简便观测微血管自律运动频率的方法。通过手机摄像头拍摄人体舌面视频,预处理后提取每帧图片中的感兴趣区域,根据每个区域中像素灰度值的变化得到血液容积变化的时序曲线;然后通过小波分解对每个感兴趣区域颜色通道的血液容积变化信号进行降噪,对降噪后的信号进行独立成分分析以降低光照和环境因素影响;提取源信号频域中主要峰值点频率进行拟合,实验结果表明本课题所提取信号频率属于微血管自律运动频率范围。
Abstract:
Abstract: Aiming at problems of high requirements for equipments and time consumption for microvascular vasomotion detection, a simple method for observing the frequency of microvascular vasomotion is proposed. The phone camera is used to capture videos of human tongue, and the regions of interest are extracted in each frame of the picture after preprocessing. The curve of the blood volume varying with time is obtained by investigating the variations of pixel gray values of each region. Then wavelet decomposition is used to denoise the blood volume varying signals of color channel in each region of interest, and independent component analysis is carried out on the noise-reduced signals to reduce the effects of light and environmental factors. Finally, the frequencies of main peak points in frequency domain of source signals are extracted for fitting. The experimental results show that the extracted signal frequency belongs to frequency range of microvascular vasomotion.

备注/Memo

备注/Memo:
【收稿日期】2021-12-16 【作者简介】李丹,硕士研究生,研究方向:医学信号处理,E-mail: 1565- 305313@qq.com
更新日期/Last Update: 2022-05-27