本文關(guān)鍵詞：基于形態(tài)分量分析和集合經(jīng)驗(yàn)?zāi)B(tài)分解的心電信號(hào)工頻干擾消除法　出處：《生物醫(yī)學(xué)工程學(xué)雜志》2015年06期 　論文類型：期刊論文

  更多相關(guān)文章： 工頻干擾 心電信號(hào) 形態(tài)分量分析 集合經(jīng)驗(yàn)?zāi)B(tài)分解

【摘要】：針對(duì)心電信號(hào)(ECG)在采集和轉(zhuǎn)換的過程中容易受到工頻干擾(PLI)的問題,提出了一種基于形態(tài)分量分析(MCA)和集合經(jīng)驗(yàn)?zāi)B(tài)分解(EEMD)的PLI消除新算法。首先根據(jù)ECG特征波形的形態(tài)差異性,利用MCA將其分解為突變成分、平滑成分和殘余白噪聲成分,然后對(duì)含PLI的平滑成分進(jìn)行EEMD,再濾除PLI的本征模態(tài)函數(shù)(IMF),最后重構(gòu)ECG信號(hào)。文中采用噪聲抑制率(NSR)和信號(hào)失真率(SDR)來評(píng)價(jià)算法的降噪效果。通過實(shí)驗(yàn)發(fā)現(xiàn),該算法不僅能夠有效地濾除工頻干擾,而且SDR值較小,濾波效果優(yōu)于改進(jìn)的Levkov算法。
[Abstract]:In order to solve the problem that electrocardiogram (ECG) is easy to be interfered with by power frequency in the process of acquisition and conversion. A new PLI cancellation algorithm based on morphological component analysis (MCA) and set empirical mode decomposition (EEMD) is proposed. Firstly, according to the morphological differences of ECG characteristic waveforms, a new algorithm is proposed. It is decomposed into mutants, smooth components and residual white noise components by MCA, then the smooth components containing PLI are processed by EEMD, and then the intrinsic mode function of PLI is filtered. Finally, the ECG signal is reconstructed. The noise suppression rate (NSRR) and the signal distortion rate (SDR) are used to evaluate the noise reduction effect of the algorithm. The experimental results show that the algorithm can not only filter the power frequency interference effectively. Moreover, the SDR value is small and the filtering effect is better than the improved Levkov algorithm.
【作者單位】： 集美大學(xué)誠毅學(xué)院;集美大學(xué)理學(xué)院;
【基金】：福建省自然科學(xué)基金項(xiàng)目資助(2012J01280) 福建省中青年教師教育科研基金資助(JA13373,JA15653)
【分類號(hào)】：R540.4;TN911.7
【正文快照】： 引言心電信號(hào)(electrocardiogram,ECG)在診斷心血管疾病、評(píng)估各種治療方法的有效性等臨床應(yīng)用中有重要意義[1-3]。體表采集到的ECG是一種非線性非平穩(wěn)的微弱信號(hào),易受到來自外界的各種干擾,主要有工頻干擾(power line interference,PLI)、肌電干擾和基線漂移等,降低了正常診，

本文編號(hào)：1431667