[1]张浩强,安蒙蒙,卜朝晖,等.基于超声回波信号的指端脉搏波提取[J].中国医学物理学杂志,2020,37(10):1306-1311.[doi:DOI:10.3969/j.issn.1005-202X.2020.10.016]
　ZHANG Haoqiang,AN Mengmeng,BU Zhaohui,et al.Fingertip pulse wave extraction based on ultrasonic echo signal[J].Chinese Journal of Medical Physics,2020,37(10):1306-1311.[doi:DOI:10.3969/j.issn.1005-202X.2020.10.016]
点击复制

基于超声回波信号的指端脉搏波提取()
分享到：

《中国医学物理学杂志》[ISSN:1005-202X/CN:44-1351/R]

卷:
37
期数:
2020年第10期
页码:
1306-1311
栏目:
医学信号处理与医学仪器
出版日期:
2020-10-29

文章信息/Info

Title:
Fingertip pulse wave extraction based on ultrasonic echo signal
文章编号:
1005-202X（2020）10-1306-06
作者:
张浩强; 安蒙蒙; 卜朝晖; 郑政
上海理工大学医疗器械与食品学院， 上海 200093
Author(s):
ZHANG Haoqiang;  AN Mengmeng;  BU Zhaohui;  ZHENG Zheng
School of Medical Instrument and Food Engineering, University of Shanghai for Science and Technology, Shanghai 200093, China
关键词:
脉搏波; 超声回波信号; 超声传感器; 光电容积脉搏波; 小波去噪
Keywords:
Keywords: pulse wave ultrasonic echo signal ultrasonic sensor photoplethysmography wavelet denoising
分类号:
R318
DOI:
DOI:10.3969/j.issn.1005-202X.2020.10.016
文献标志码:
A
摘要:
脉搏波可作为检测人体心血管系统生理病理状态的重要依据。为了验证用超声波测量脉搏波的可能、解决脉搏波的测量部位受限的问题，本研究提出一种从超声回波信号中提取脉搏波的方法。设计一种跟随式超声传感器，用数据采集系统采集指端超声回波信号，经过滤波、选点及小波去噪等处理后得到较为纯净的脉搏波信号；同时采集心电信号以及光电容积脉搏波信号作为参考信号。结果表明，可以从提取的指端脉搏波中准确地获取心率；与同步测得的光电容积脉搏波数据相关系数大部分在0.8以上；波形中的重搏前波、重搏波等细节部分也能明显地表现出来。本研究提出的方法实现了从指端超声回波信号中获取完整可靠的脉搏波信号，为日后获取不同部位的脉搏信号提供了基础。
Abstract:
Abstract: The pulse wave can be used as an important basis for detecting the physiological and pathological states of the human cardiovascular system. In order to verify the possibility of detecting pulse waves with ultrasound and to solve the problem of restricted sites for pulse wave detection, a method of extracting pulse waves from ultrasonic echo signal is proposed. A following ultrasonic sensor was designed, and a data acquisition system was used to collect the ultrasonic echo signals at the fingertips. Pure pulse wave signals were obtained after filtering, point selection and wavelet denoising. Meanwhile, the electrocardiogram signals and the photoplethysmography signals were collected as reference signals. The results show that the heart rate can be accurately obtained from the extracted fingertip pulse wave, and that the correlation coefficient between the pulse wave signals and the photoplethysmography data measured at the same time is mainly above 0.8. Such details as dicrotic wave and dicrotic wavefront can also be displayed clearly. By the proposed method, a complete and reliable pulse wave signal can be obtained from the ultrasonic echo signals at the fingertips, which lays significant foundations for obtaining pulse signals from different sites in the future.

相似文献/References:

[1]郭垚垚,陈兆学.一种脉搏波和心电信号时域基线漂移消除方法[J].中国医学物理学杂志,2016,33(2):167.[doi:10.3969/j.issn.1005-202X.2016.02.012]
　[J].Chinese Journal of Medical Physics,2016,33(10):167.[doi:10.3969/j.issn.1005-202X.2016.02.012]
[2]苏志刚,朱海玲,郝敬堂. 基于高斯混合模型的脉搏波特征提取方法[J].中国医学物理学杂志,2018,35(1):76.[doi:DOI:10.3969/j.issn.1005-202X.2018.01.014]
　SU Zhigang,ZHU Hailing,HAO Jingtang. Gaussian mixture model-based method for extracting the features of pulse wave[J].Chinese Journal of Medical Physics,2018,35(10):76.[doi:DOI:10.3969/j.issn.1005-202X.2018.01.014]
[3]苏志刚,吕江波,郝敬堂. 基于平滑先验法去除脉搏波基线漂移[J].中国医学物理学杂志,2018,35(10):1197.[doi:DOI:10.3969/j.issn.1005-202X.2018.10.017]
　SU Zhigang,LÜ,Jiangbo,et al. Removal of baseline drift of pulse wave based on smoothness prior[J].Chinese Journal of Medical Physics,2018,35(10):1197.[doi:DOI:10.3969/j.issn.1005-202X.2018.10.017]
[4]陈倩蓉,梁永波,赵飞骏,等. 基于心电-脉搏波的心血管疾病识别研究[J].中国医学物理学杂志,2019,36(2):210.[doi:DOI:10.3969/j.issn.1005-202X.2019.02.017]
　CHEN Qianrong,LIANG Yongbo,ZHAO Feijun,et al. Cardiovascular disease recognition based on electrocardiogram data and pulse wave[J].Chinese Journal of Medical Physics,2019,36(10):210.[doi:DOI:10.3969/j.issn.1005-202X.2019.02.017]
[5]程敏,陈兆学. 基于指端脉搏波视频信号的心率稳定检测算法[J].中国医学物理学杂志,2019,36(2):215.[doi:DOI:10.3969/j.issn.1005-202X.2019.02.018]
　CHENG Min,CHEN Zhaoxue. An algorithm based on video signals of pulse waves on the finger tip for stable detection of heart rates[J].Chinese Journal of Medical Physics,2019,36(10):215.[doi:DOI:10.3969/j.issn.1005-202X.2019.02.018]
[6]鲍凯林,陈兆学.基于多尺度样本熵方法分析欧拉视频放大技术在非接触式测量的作用[J].中国医学物理学杂志,2020,37(5):635.[doi:10.3969/j.issn.1005-202X.2020.05.020]
　BAO Kailin,CHEN Zhaoxue.Application of Euler video amplification technology in non-contact measurement: an analysis basedon multi-scale sample entropy[J].Chinese Journal of Medical Physics,2020,37(10):635.[doi:10.3969/j.issn.1005-202X.2020.05.020]
[7]郑嘉强,程云章,边俊杰.基于脉搏波特征参数的无创连续血压测量研究进展[J].中国医学物理学杂志,2020,37(6):749.[doi:DOI:10.3969/j.issn.1005-202X.2020.06.017]
　ZHENG Jiaqiang,CHENG Yunzhang,BIAN Junjie.Advances in non-invasive continuous blood pressure measurement based on characteristic parameters of pulse wave[J].Chinese Journal of Medical Physics,2020,37(10):749.[doi:DOI:10.3969/j.issn.1005-202X.2020.06.017]
[8]王一飞,刘光浚,刘轩吉,等.基于神经网络的脉搏波信号血压检测算法[J].中国医学物理学杂志,2022,39(8):998.[doi:DOI:10.3969/j.issn.1005-202X.2022.08.014]
　WANG Yifei,LIU Guangjun,LIU Xuanji,et al.Neural network-based blood pressure detection algorithms for pulse wave signals[J].Chinese Journal of Medical Physics,2022,39(10):998.[doi:DOI:10.3969/j.issn.1005-202X.2022.08.014]
[9]周韡鼎,陈兆学.基于深度学习的指-桡端脉搏波信号转换方法[J].中国医学物理学杂志,2023,40(2):202.[doi:DOI:10.3969/j.issn.1005-202X.2023.02.013]
　ZHOU Weiding,CHEN Zhaoxue.Deep learning-based method for finger-radial PPG signal transferring[J].Chinese Journal of Medical Physics,2023,40(10):202.[doi:DOI:10.3969/j.issn.1005-202X.2023.02.013]
[10]张瑞芳,梁永波,崔谋,等.结合多模态融合方式的脉搏波房颤识别[J].中国医学物理学杂志,2023,40(10):1260.[doi:DOI:10.3969/j.issn.1005-202X.2023.10.013]
　ZHANG Ruifang,LIANG Yongbo,,et al.Multimodal fusion approach to detect atrial fibrillation using PPG[J].Chinese Journal of Medical Physics,2023,40(10):1260.[doi:DOI:10.3969/j.issn.1005-202X.2023.10.013]

备注/Memo

备注/Memo:
【收稿日期】2020-03-28 【作者简介】张浩强，硕士研究生，研究方向：医学超声、生物医学电子学，E-mail: 1456712437@qq.com 【通信作者】郑政，研究员，研究方向：医学超声、生物医学电子学，E-mail: 2697818504@qq.com
更新日期/Last Update: 2020-10-29