Comput. Biol. Med. - ECG signal enhancement using S-Transform.

Tópicos

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Resumo

Electrocardiogram (ECG), which is a noninvasive technique, is used generally as a primary diagnostic tool for cardiovascular diseases. In real-time scenario, noises like channel noise, muscle artifacts, electrode motion and baseline wander are often embedded with ECG signals during acquisition and transmission. In this paper, an automatic ECG signal enhancement technique is proposed to remove noise components from time-frequency domain represented noisy ECG signal. Stockwell transform (S-Transform) is used in this work to represent the noisy ECG signal in time-frequency domain. Next, masking and filtering technique is applied to remove unwanted noise components from time-frequency domain. The proposed technique does not require any prior information like R-peak position or reference signal as auxiliary signal. This method is evaluated on ECG signals which are available in MIT-BIH Arrhythmia database. The experimental results demonstrate that the proposed method shows better signal to noise ratio (SNR) and lower root means square error (RMSE) compared to earlier reported wavelet transform with soft thresholding (WT-Soft) and wavelet transform with subband dependent threshold (WT-Subband) based technique. To quantify the significant difference among all methods, the performances of different ECG enhancement techniques at 1.25dB input SNR level are compared using analysis of variance (ANOVA) based statistical evaluation technique and it is seen that the proposed method yields superior performance compared to other methods. R-peak detection test is also conducted on enhanced ECG signal in addition to SNR and RMSE to evaluate the quality of biology-related information preserved in the enhanced ECG signal. The performance of R-peak detection for denoised ECG signals, in terms of sensitivity and positive predictivity using proposed enhancement method, is also better than WT-Soft, WT-Subband methods, and validates the superiority of the proposed method.

Resumo Limpo

electrocardiogram ecg noninvas techniqu use general primari diagnost tool cardiovascular diseas realtim scenario nois like channel nois muscl artifact electrod motion baselin wander often embed ecg signal acquisit transmiss paper automat ecg signal enhanc techniqu propos remov nois compon timefrequ domain repres noisi ecg signal stockwel transform stransform use work repres noisi ecg signal timefrequ domain next mask filter techniqu appli remov unwant nois compon timefrequ domain propos techniqu requir prior inform like rpeak posit refer signal auxiliari signal method evalu ecg signal avail mitbih arrhythmia databas experiment result demonstr propos method show better signal nois ratio snr lower root mean squar error rmse compar earlier report wavelet transform soft threshold wtsoft wavelet transform subband depend threshold wtsubband base techniqu quantifi signific differ among method perform differ ecg enhanc techniqu db input snr level compar use analysi varianc anova base statist evalu techniqu seen propos method yield superior perform compar method rpeak detect test also conduct enhanc ecg signal addit snr rmse evalu qualiti biologyrel inform preserv enhanc ecg signal perform rpeak detect denois ecg signal term sensit posit predict use propos enhanc method also better wtsoft wtsubband method valid superior propos method

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