Noise Reduction in ECG Signal Using an Effective Hybrid Scheme

IEEE Access

卷:8

Pingping Bing¹  Zhihua Zhang²  Wei Liu²  Zhong Wang³ 

[1] Academician Workstation, Changsha Medical University, Changsha, China;

[2] College of Mechanical and Electrical Engineering, Beijing University of Chemical Technology, Beijing, China;

[3] Institute of Applied Technology, Hunan Vocational College of Electronic and Technology, Changsha, China;

关键词: Electrocardiogram signal;    noise reduction;    high-order synchrosqueezing transform;    detrended fluctuation analysis;    non-local means;   

DOI  :  10.1109/ACCESS.2020.3021068

来源: DOAJ

【 摘 要 】

Electrocardiogram (ECG) is a critical biological signal, which usually carries a great deal of essential information about patients. The high quality ECG signals are always required for a proper diagnosis of cardiac disorders. However, the raw ECG signals are highly noisy in nature. In the paper, we propose a hybrid denoising scheme to enhance ECG signals by combining high-order synchrosqueezing transform (FSSTH) with non-local means (NLM). With this method, a noisy ECG signal is first decomposed into an ensemble of intrinsic mode functions (IMFs) by FSSTH. Then, some noise is removed by eliminating a set of noisy IMFs that are determined by a scaling exponent obtained by the detrended fluctuation analysis (DFA); while the remaining IMFs are filtered by NLM. Finally, the denoised ECG signal is obtained by reconstructing the processed IMFs. Experiments are carried out using the simulated ECG signals and real ones from the MIT-BIH database, and the denoising performances are evaluated in terms of signal to noise ratio (SNR), root mean squared error (RMSE) and percent root mean square difference (PRD). Results show that the hybrid denoising scheme involving both FSSTH and NLM is able to suppress complex noise from ECG signals more effectively while preserving the details well.

【 授权许可】

Unknown