LOCALLY ADAPTIVE FILTERIG OF NON-STATIONARY NOISE IN LONG-TERM ELECTROCARDIOGRAPHIC SIGNALS

The research subject of the article is the methods of locally adaptive filtering of non-stationary (from the point of view of its variance) noise in long-term electrocardiogram (ECG) signals. The goal is to develop locally adaptive algorithms for filtering noise with different a priori unknown level...

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Main Authors: Наталия Олеговна Тулякова, Александр Николаевич Трофимчук
Format: Article
Language:English
Published: National Aerospace University «Kharkiv Aviation Institute» 2020-11-01
Series:Радіоелектронні і комп'ютерні системи
Subjects:
Online Access:http://nti.khai.edu/ojs/index.php/reks/article/view/1268
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author Наталия Олеговна Тулякова
Александр Николаевич Трофимчук
author_facet Наталия Олеговна Тулякова
Александр Николаевич Трофимчук
author_sort Наталия Олеговна Тулякова
collection DOAJ
description The research subject of the article is the methods of locally adaptive filtering of non-stationary (from the point of view of its variance) noise in long-term electrocardiogram (ECG) signals. The goal is to develop locally adaptive algorithms for filtering noise with different a priori unknown levels of variance in real-time for ECG signals recorded with a standard sampling rate of 500 Hz. The tasks to be solved are: to investigate the effectiveness of the developed adaptive ECG filtering algorithms using numerical statistical estimates of processing quality in a wide range of additive Gaussian noise variance variation, to investigate the suppression of real non-stationary electromyographic (EMG) noise, and to analyze the application for normal and pathological ECG signals. The methods are integral and local indicators of the filter quality according to the criteria of the mean square error and the signal-to-noise ratio was obtained using numerical simulation (via Monte Carlo analysis). The following results were obtained: an adaptive method for real-time suppression of non-stationary noise in the ECG is proposed, the one-pass and the two-pass algorithms, and the algorithm with selective depending on the preliminary estimates of noise levels re-filtering have been developed on the method basis. Statistical estimates of the filters' efficiency and analysis of their outputs show a high degree of suppression of the noise with different levels of variance in the ECGs. The distortions absence while processing QRS-complex and high efficiency of suppression of Gaussian and real EMG noise with varying variance are demonstrated. The analysis of the output signals and plots of the local adaptation parameters and the adaptable parameters of the proposed algorithms confirms the high efficiency of filtering. The developed algorithms have been successfully tested for normal and pathological ECG signals. Conclusions. The scientific novelty of the results is the development of a locally adaptive method with noise and signal-dependent filter parameters switching and of the adaptive algorithms based on this method for non-stationary noise reduction in the ECG in real-time. This method does not require time for filter parameters adaptation and a priori information about the noise variance, and it has a high-speed performance in real-time mode.
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spelling doaj.art-82d3add7ff4e4653a9202d015e94dc5d2023-09-02T06:11:39ZengNational Aerospace University «Kharkiv Aviation Institute»Радіоелектронні і комп'ютерні системи1814-42252663-20122020-11-0104163310.32620/reks.2020.4.021284LOCALLY ADAPTIVE FILTERIG OF NON-STATIONARY NOISE IN LONG-TERM ELECTROCARDIOGRAPHIC SIGNALSНаталия Олеговна Тулякова0Александр Николаевич Трофимчук1Институт прикладной физики НАНУ, СумыИнститут телекоммуникаций и глобального информационного пространства НАНУ, КиевThe research subject of the article is the methods of locally adaptive filtering of non-stationary (from the point of view of its variance) noise in long-term electrocardiogram (ECG) signals. The goal is to develop locally adaptive algorithms for filtering noise with different a priori unknown levels of variance in real-time for ECG signals recorded with a standard sampling rate of 500 Hz. The tasks to be solved are: to investigate the effectiveness of the developed adaptive ECG filtering algorithms using numerical statistical estimates of processing quality in a wide range of additive Gaussian noise variance variation, to investigate the suppression of real non-stationary electromyographic (EMG) noise, and to analyze the application for normal and pathological ECG signals. The methods are integral and local indicators of the filter quality according to the criteria of the mean square error and the signal-to-noise ratio was obtained using numerical simulation (via Monte Carlo analysis). The following results were obtained: an adaptive method for real-time suppression of non-stationary noise in the ECG is proposed, the one-pass and the two-pass algorithms, and the algorithm with selective depending on the preliminary estimates of noise levels re-filtering have been developed on the method basis. Statistical estimates of the filters' efficiency and analysis of their outputs show a high degree of suppression of the noise with different levels of variance in the ECGs. The distortions absence while processing QRS-complex and high efficiency of suppression of Gaussian and real EMG noise with varying variance are demonstrated. The analysis of the output signals and plots of the local adaptation parameters and the adaptable parameters of the proposed algorithms confirms the high efficiency of filtering. The developed algorithms have been successfully tested for normal and pathological ECG signals. Conclusions. The scientific novelty of the results is the development of a locally adaptive method with noise and signal-dependent filter parameters switching and of the adaptive algorithms based on this method for non-stationary noise reduction in the ECG in real-time. This method does not require time for filter parameters adaptation and a priori information about the noise variance, and it has a high-speed performance in real-time mode.http://nti.khai.edu/ojs/index.php/reks/article/view/1268адаптивная фильтрация сигнала электрокардиограммы в реальном временинестационарный электромиографический шумстатистические оценки эффективности
spellingShingle Наталия Олеговна Тулякова
Александр Николаевич Трофимчук
LOCALLY ADAPTIVE FILTERIG OF NON-STATIONARY NOISE IN LONG-TERM ELECTROCARDIOGRAPHIC SIGNALS
Радіоелектронні і комп'ютерні системи
адаптивная фильтрация сигнала электрокардиограммы в реальном времени
нестационарный электромиографический шум
статистические оценки эффективности
title LOCALLY ADAPTIVE FILTERIG OF NON-STATIONARY NOISE IN LONG-TERM ELECTROCARDIOGRAPHIC SIGNALS
title_full LOCALLY ADAPTIVE FILTERIG OF NON-STATIONARY NOISE IN LONG-TERM ELECTROCARDIOGRAPHIC SIGNALS
title_fullStr LOCALLY ADAPTIVE FILTERIG OF NON-STATIONARY NOISE IN LONG-TERM ELECTROCARDIOGRAPHIC SIGNALS
title_full_unstemmed LOCALLY ADAPTIVE FILTERIG OF NON-STATIONARY NOISE IN LONG-TERM ELECTROCARDIOGRAPHIC SIGNALS
title_short LOCALLY ADAPTIVE FILTERIG OF NON-STATIONARY NOISE IN LONG-TERM ELECTROCARDIOGRAPHIC SIGNALS
title_sort locally adaptive filterig of non stationary noise in long term electrocardiographic signals
topic адаптивная фильтрация сигнала электрокардиограммы в реальном времени
нестационарный электромиографический шум
статистические оценки эффективности
url http://nti.khai.edu/ojs/index.php/reks/article/view/1268
work_keys_str_mv AT nataliâolegovnatulâkova locallyadaptivefilterigofnonstationarynoiseinlongtermelectrocardiographicsignals
AT aleksandrnikolaevičtrofimčuk locallyadaptivefilterigofnonstationarynoiseinlongtermelectrocardiographicsignals