Tekrarlamalı Gauss-Seidel Algoritması ile EKG Gürültüsünün Temizlenmesi

Yıl 2024, Cilt: 14 Sayı: 4, 2115 - 2127, 15.12.2024

Metin Hatun

https://doi.org/10.31466/kfbd.1524020

Öz

Elektrokardiyogram (EKG) sinyalleri kalp fonksiyonları ve bazı kalp hastalıkları hakkında bilgi sağlar. Ancak ölçüm ve iletim sırasında EKG dalga formlarını bozan çeşitli girişimler, hatalı analiz ve tanıya neden olabilir. Bu nedenle, bu istenmeyen bozucu sinyallerin ortadan kaldırılması ve gürültülü EKG kayıtlarından kabul edilebilir bir EKG sinyalinin çıkarılması gerekmektedir. Araştırmacılar, EKG kayıtlarına bulaşan istenmeyen gürültü ve girişimlerin üstesinden gelmek için çeşitli yöntemler geliştirdiler. Uyarlanabilir filtreleme teknikleri, istenmeyen sinyallerin zamanla değişen doğasına uyum sağlama mekanizmaları nedeniyle bilim adamlarının dikkatini çekmiştir. Sunulan uyarlanabilir filtreleme algoritmalarının çoğu eğim tabanlıdır ve basit gerçekleme avantajına sahiptir, ancak bozucu sinyallerden olumsuz etkilenirler; örneğin, yavaş yakınsama hızlarına ve zayıf kalıcı-durum özelliklerine sahip olabilirler. En küçük kareler tabanlı algoritmalar, daha hızlı yakınsama ve daha iyi kalıcı-durum yanıtları nedeniyle avantajlıdır. Bu makalede, gürültülü EKG kayıtlarından kabul edilebilir bir dalga şekli elde etmek için, Tekrarlamalı En Küçük Kareler (RLS) algoritmasına göre daha az hesaplama karmaşıklığına sahip, en küçük kareler tabanlı alternatif bir yöntem olan Tekrarlamalı Gauss-Seidel (RGS) algoritması sunulmaktadır. RGS algoritmasının gürültü temizleme performansı araştırılmış ve yaygın olarak kullanılan eğim tabanlı algoritmalar ve popüler RLS algoritması ile karşılaştırılmıştır.

Anahtar Kelimeler

EKG gürültü temizleme, Uyarlamalı filtreleme, Gauss-Seidel, Tekrarlamalı algoritma

ECG Noise Cancellation with Recursive Gauss-Seidel Algorithm

Öz

Electrocardiogram (ECG) signals provide information about heart functions and some cardiac diseases. However, various interferences distort the ECG waveforms during its measurement and transmission can cause inaccurate analysis and diagnosis. So, this unwanted disturbance signals must be eliminated and an acceptable ECG signal must be extracted the noisy ECG recordings. Researchers developed several methods to overcome the undesired noises and interferences contaminated to the ECG recordings. The adaptive filtering techniques have attracted the attention of scientists due to their adaptation mechanism to time-varying nature of undesired signals. Most of the presented adaptive filtering algorithms are gradient-based and have the advantage of simple implementation, but are affected negatively by disturbance signals; for example, they can have slow convergence rates and poor steady-state properties. Least squares-based algorithms are advantageous due to their faster convergence rates and better steady-state properties. In this paper, Recursive Gauss-Seidel (RGS) algorithm, which is an alternative least squares-based method to Recursive Least Squares (RLS) algorithm with less computational complexity, is presented to obtain an acceptable waveform from noisy ECG recordings. The denoising performance of the RGS algorithm is studied and compared to the widely used gradient-based algorithms and the popular RLS algorithm.

Anahtar Kelimeler

ECG denoising, Adaptive filtering, Gauss-Seidel, Recursive algorithm

Kaynakça

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