多谱自适应小波和盲源分离耦合的生理信号降噪方法  

Physiological signal denoising method based on multi-spectrum adaptive wavelet and blind source separation

作　　者：王振宇[1,2] 向泽锐 支锦亦[1,3] 丁铁成[1] 邹瑞 WANG Zhenyu;XIANG Zerui;ZHI Jinyi;DING Tiecheng;ZOU Rui(School of Design,Southwest Jiaotong University,Chengdu 610031,China;College of Design and Innovation,Tongji University,Shanghai 200092;Institute of Design and Research for Man-Machine-Environment Engineering System,Southwest Jiaotong University,Chengdu,611730,China)

机构地区：[1]西南交通大学设计艺术学院,成都610031 [2]同济大学设计创意学院,上海200092 [3]西南交通大学人机环境系统设计研究所,成都611730

出　　处：《北京航空航天大学学报》2025年第3期910-921,共12页Journal of Beijing University of Aeronautics and Astronautics

基　　金：教育部2022年第二批产学合作协同育人项目(220705329291641);西南交通大学新型交叉学科培育基金(YG2022006)。

摘　　要：为提高生理信号的质量和可靠性,将盲源分离和小波阈值方法进行耦合研究,提出了多谱自适应小波信号增强方法并与改进的盲源分离方法相结合进行降噪处理。为评估所提方法的有效性,使用小波变换中软阈值、硬阈值、自适应阈值3种方法计算信噪比(SNR)和均方根误差(RMSE)。结果表明:所提方法在软阈值下具有较强的适用性,增强后的信号软阈值相比硬阈值,SNR提升约44.2%,RMSE下降约28.8%,处理时间减少约1.4%。软阈值相比自适应阈值,SNR提升约706%,RMSE下降约16.7%,处理时间减少约3.0%。为对比软阈值下各参数差异,使用软阈值对原始信号、加噪信号和增强信号进行对比分析及归一化处理。结果显示增强后的信号具有较好的SNR、较低的RMSE和较短的处理时间,软阈值下增强后的信号与原始信号相比,SNR提升约0.12%,RMSE下降约2.5%,处理时间减少约3.9%,进一步验证了所提方法的有效性,并提高了信号质量。In order to improve the quality and reliability of physiological signals,blind source separation and wavelet threshold methods were coupled to propose a multi-spectrum adaptive wavelet signal enhancement method,which was combined with an improved blind source separation method for denoising.To evaluate the effectiveness of the proposed method,the signal-to-noise ratio(SNR)and root mean square error(RMSE)indicators were calculated by using three wavelet transform methods:soft threshold,hard threshold,and adaptive threshold.The results show that the proposed method has strong applicability under the soft threshold,and compared with that under a hard threshold,the enhanced signal under a soft threshold has an SNR improvement of about 44.2%,RMSE reduction of about 28.8%,and a time reduction of about 1.4%.Compared with the adaptive threshold,SNR is improved by about 706%;RMSE is reduced by about 16.7%,and time is reduced by about 3.0%.The original,noisy,and enhanced signals are analyzed and normalized by using a soft threshold to compare the differences in various parameters under a soft threshold.The results show that the enhanced signal has a better SNR,lower RMSE,and shorter processing time.Compared with the original signal under the soft threshold,SNR is improved by about 0.12%;RMSE is reduced by about 2.5%,and time is reduced by about 3.9%,which further verifies the effectiveness of the proposed algorithm and improves the signal quality.

关 键 词：多谱自适应小波 盲源分离 小波变换 降噪方法 生理信号 

分 类 号：TP391.41[自动化与计算机技术—计算机应用技术]