摘要
人体生理活动和随机噪声都会对脑血氧检测数据精度产生影响,为提高测量精度,需解决信号采集时遇到的噪声干扰。文中提出一种利用改进的具备自适应噪声的完全集成经验模态分解(Improved Complete Empirical Mode Decomposition with Adaptive Noise,ICEEMDAN)与样本熵(Sample Entropy,SampEn)相结合的脑血氧信号去噪方法。利用ICEEMDAN对脑血氧信号进行模态分解,从而获得不同时间复杂度的固有模态函数(Intrinsic Mode Function,IMF)分量。通过样本熵值判断各IMF分量的时间复杂度,依据IMF分量的样本熵值选择合适的分量重构信号,从而去除原始信号的噪声。实验结果表明,所提方法可以有效去除原始脑血氧信号中的噪声,实现采集数据的精度提升,进而提高脑血氧检测精度。
Both human physiological activity and random noise have an impact on the accuracy of cerebral blood oxygen measurement data.It is necessary to solve some noise interference encountered during signal acquisition to improve the measurement accuracy of cerebral blood oxygen detection.This study proposes a denoising method of cerebral oximetry signals by combining ICEEMDAN(Improved Complete Empirical Mode Decomposition with Adaptive Noise)and SampEn(Sample Entropy).Specifically,the modal decomposition of the cerebral blood oxygen signal is performed using ICEEMDAN to obtain the IMF components with different time complexity.The time complexity of each IMF(Intrinsic Mode Function)component is judged by the sample entropy value,and the appropriate component is selected to reconstruct the signal according to the sample entropy value of each IMF component,thus realizing the noise removal of the original signal.Experimental results show that the proposed method can effectively remove the original cerebral blood oxygen signal and realize the accuracy improvement of the collected data,thus improving the accuracy of cerebral blood oxygen detection.
作者
曹焱
赵斌
邢志明
金子豪
董祥美
高秀敏
CAO Yan;ZHAO Bin;XING Zhiming;JIN Zihao;DONG Xiangmei;GAO Xiumin(School of Optical-Electrical and Computer Engineering,University of Shanghai for Science and Technology,Shanghai 200093,China)
出处
《电子科技》
2024年第6期44-50,共7页
Electronic Science and Technology
基金
国家重点研发计划(2018YFC1313803)。
关键词
脑血氧
精度
ICEEMDAN
样本熵
固有模态函数
重构信号
血氧信号
噪声去除
cerebral blood oxygen
accuracy
ICEEMDAN
sample entropy
intrinsic mode function
reconstructed signal
blood oxygen signal
noise removal
作者简介
曹焱(1997-),男,硕士研究生。研究方向:光电检测;高秀敏(1978-),男,博士,教授。研究方向:仪器仪表、智能传感技术等。
