心电信号采集数字滤波算法优化
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摘要
由于心电信号(ECG)检测的实际环境情况并非理想状态,因此ECG信号中总会夹杂着各种随机噪声。这些噪声的存在使得心电信号模糊而且严重地影响了医疗诊断的可靠度。因此,当前需要优化的问题是如何更好地抑制这些严重干扰ECG信号检测波形的噪声。虽然针对这方面的滤波算法有了一定的成果,但在心电信号的细节特征上做得不够细致,所以文中从数字滤波角度出发,基于分析IIR法,以提高心电信号特征点清晰度。由仿真结果可以看出,多阶反馈式整形IIR滤波器能够更加明显清晰地保留原始信号特征,有利于后期诊断。
There exist various random noises in ECG signals as the actual environmental condition of ECG signal detection is not ideal. These noises make ECG signals fuzzy and seriously affect the reliability of medical diagnosis. The current problem that needs to be optimized is how to better suppress the noises that seriously affect the ECG signal detection waveforms. Though the filtering algorithm in this respect has got a certain achievements,the detail characteristics of ECG signals are not handled carefully enough. Therefore,a design method of a multi-order feedback shaping IIR filter is researched in this paper on the basis of analyzing the IIR digital filtering and IIR direct design method from the digital filtering perspective,so as to improve the feature point definition of ECG signals. The simulation results show that the multi-order feedback shaping IIR filter can retain the characteristics of original signals more obviously and clearly,which is beneficial to the latter diagnosis.
There exist various random noises in ECG signals as the actual environmental condition of ECG signal detection is not ideal. These noises make ECG signals fuzzy and seriously affect the reliability of medical diagnosis. The current problem that needs to be optimized is how to better suppress the noises that seriously affect the ECG signal detection waveforms. Though the filtering algorithm in this respect has got a certain achievements,the detail characteristics of ECG signals are not handled carefully enough. Therefore,a design method of a multi-order feedback shaping IIR filter is researched in this paper on the basis of analyzing the IIR digital filtering and IIR direct design method from the digital filtering perspective,so as to improve the feature point definition of ECG signals. The simulation results show that the multi-order feedback shaping IIR filter can retain the characteristics of original signals more obviously and clearly,which is beneficial to the latter diagnosis.
引文
[1]蒙俊甫.基于嵌入式的医疗监护PDA无线终端设计[D].成都:成都理工大学,2010.MENG Junfu. The design of wireless medical PDA based onembedded system[D]. Chengdu:Chengdu University of Tech?nology,2010.
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[5]郑蕾.基于小波变换的心音信号分析方法的研究[D].兰州:兰州理工大学,2010.ZHENG Lei. Research of heart sound signal analysis methodbased on wavelet transform[D]. Lanzhou:Lanzhou Universityof Technology,2010.
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[10]毛玲,张国敏,孙即祥.心电图ST段形态分析方法研究[J].信号处理,2009,25(9):1360?1365.MAO Ling, ZHANG Guomin, SUN Jixiang. Research onshape analysis of ST segments in ECG signal[J]. Signal pro?cessing,2009,25(9):1360?1365.
[11]宋晋忠,严洪,姚宇华,等.基于心电图ST?T段的心肌缺血检测方法研究进展[J].航天医学与医学工程,2011,24(2):146?150.SONG Jinzhong,YAN Hong,YAO Yuhua,et al. Researchprogress in detecting methods for myocardial ischemia basedon electrocardiogram ST?T complex[J]. Space medicine&medical engineering,2011,24(2):146?150.
[12] MUKHERJEE A,GHOSH K K. An efficient wavelet analysisfor ECG signal processing[C]//Proceedings of InternationalConference on Informatics, Electronics&Vision. Dhaka:IEEE,2012:411?415.
[2]谷蓉.心电信号处理算法与应用的研究[D].南京:南京邮电大学,2014.GU Rong. Research of ECG processing algorithm and its appli?cation[D]. Nanjing:Nanjing University of Posts and Telecom?munications,2014.
[3]石进平.心电图机计量指标的临床意义[J].大众标准化,2009(z2):41?43.SHI Jinping. Clinical significance of measuring index of electro?cardiograph[J]. Popular standardization,2009(S2):41?43.
[4]欧阳绳武.便携式移动医疗心电诊断系统研究与设计[D].贵阳:贵州大学,2016.OUYANG Shengwu. Research and design of portable mobilemedical ECG diagnosis system[D]. Guiyang:Guizhou Universi?ty,2016.
[5]郑蕾.基于小波变换的心音信号分析方法的研究[D].兰州:兰州理工大学,2010.ZHENG Lei. Research of heart sound signal analysis methodbased on wavelet transform[D]. Lanzhou:Lanzhou Universityof Technology,2010.
[6]彭云.基于EEMD消除ECG基线漂移的新算法[J].信息系统工程,2014(8):128?129.PENG Yun. A new algorithm based on EEMD to eliminateECG baseline drift[J]. China CIO news,2014(8):128?129.
[7]宋春丽.怎样识读MIT?BIH中的心电信号[J].科技资讯,2010(9):27.SONG Chunli. How to read the ECG signal in MIT?BIH[J]. Sci?ence&technology information,2010(9):27.
[8]汪学东,向晋涛,熊军.利用时间RR间期散点图及逆向技术分析和诊断房性并行心律[J].中国心脏起搏与心电生理杂志,2013,27(1):79?82.WANG Xuedong,XIANG Jintao,XIONG Jun. Analysis and di?agnosis of atrial concurrent arrhythmia using time RR intervaldiagram and reverse technique[J].Chinese journal of cardiacpacing and electrophysiology,2013,27(1):79?82.
[9] KANG W S, YUN S, CHO K. ECG denoise method based onwavelet function learning[C]//Proceedings of IEEE sensors.[S.l.]:IEEE,2012:1?4.
[10]毛玲,张国敏,孙即祥.心电图ST段形态分析方法研究[J].信号处理,2009,25(9):1360?1365.MAO Ling, ZHANG Guomin, SUN Jixiang. Research onshape analysis of ST segments in ECG signal[J]. Signal pro?cessing,2009,25(9):1360?1365.
[11]宋晋忠,严洪,姚宇华,等.基于心电图ST?T段的心肌缺血检测方法研究进展[J].航天医学与医学工程,2011,24(2):146?150.SONG Jinzhong,YAN Hong,YAO Yuhua,et al. Researchprogress in detecting methods for myocardial ischemia basedon electrocardiogram ST?T complex[J]. Space medicine&medical engineering,2011,24(2):146?150.
[12] MUKHERJEE A,GHOSH K K. An efficient wavelet analysisfor ECG signal processing[C]//Proceedings of InternationalConference on Informatics, Electronics&Vision. Dhaka:IEEE,2012:411?415.