کد مقاله کد نشریه سال انتشار مقاله انگلیسی ترجمه فارسی نسخه تمام متن
4973486 1451641 2018 10 صفحه PDF سفارش دهید دانلود کنید
عنوان انگلیسی مقاله ISI
Periodicity-based nonlocal-means denoising method for electrocardiography in low SNR non-white noisy conditions
موضوعات مرتبط
مهندسی و علوم پایه مهندسی کامپیوتر پردازش سیگنال
پیش نمایش صفحه اول مقاله
Periodicity-based nonlocal-means denoising method for electrocardiography in low SNR non-white noisy conditions
چکیده انگلیسی


- Advanced nonlocal-means filtering method is proposed for ECG noise reduction.
- Search windows can be efficiently set based on the periodic propertyof ECG.
- The influence of dissimilar patches on denoising was substantially reduced.
- This algorithm can be effectively applied to pink and electromyogram noise.

Nonlocal means (NLM) denoising, originally developed for non-neighborhood image filtering, might be appropriate for denoising electrocardiography (ECG). It was applied to ECG signals and achieved results comparable to those of other state-of-the-art filters. This study proposed periodic NLM filtering (pNLM) for ECG and tested it in various noise environments. To increase the original NLM denoising performance for ECG, pNLM search windows were selected based on ECG periodicity, reducing dissimilar patch effects and leading to better denoising performance. The algorithm was evaluated using the MIT-BIH arrhythmia database and quantitative metrics, such as signal-to-noise ratio (SNR) improvement, mean squared error (MSE), and percent root mean square difference (PRD). Experimental results showed that this novel denoising method increased denoising performance compared to the NLM method by 23.8%, 28.8% and 97.9% for white, pink, and electromyogram (EMG) noise, respectively, especially for low SNR input. In summary, the pNLM algorithm is effective for denoising three types of ECG noise.

ناشر
Database: Elsevier - ScienceDirect (ساینس دایرکت)
Journal: Biomedical Signal Processing and Control - Volume 39, January 2018, Pages 284-293
نویسندگان
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