A NEW ROBUST QRS DETECTION ALGORITHM IN ARRHYTHMIC ECG SIGNALS

Abstract

The QRS detection in electrocardiogram (ECG) signals provides significant information to help automatic diagnosis of some cardiovascular disorders. There are many studies about QRS detection in the literature. All these studies have focused on the development of QRS detection including noise, baseline wander, artifacts, small and wide QRS complexes. However, some QRS complexes cannot be detected due to their morphological and arrhythmic disorders. These types of beats are misevaluated during observation. Therefore, increasing the success and accuracy of such algorithms is of great importance for the development of wearable cardiac diagnostic devices. Arrhythmic ECG signals include different morphologic features, such as sudden, narrow, small, and negative QRS complexes, which are very difficult to automatically detect. In this study, we propose a new algorithm with higher accuracy than other studies in the literature for the detection these types of QRS complexes. The proposed method based on digital filtering and Discrete Wavelet Transform (DWT) is evaluated and tested using the two-channel ECG records obtained from 48 patients in the MIT/BIH arrhythmia database. The overall performance results of this algorithm are calculated as 99.79% of the sensitivity, 99.95% of the predictivity rate, the detection error rate of 0.26 and 99.74% of accuracy score.

Keywords

• Electrocardiogram,QRS Detection,Discrete Wavelet Transform,Digital Filters

ARİTMİK EKG SİNYALLERİNDE DAYANIKLI YENİ BİR QRS YAKALAMA ALGORİTMASI

Abstract

Elektrokardiyogram (EKG) sinyallerindeki QRS algılama, bazı kardiyovasküler bozuklukların otomatik teşhisine yardımcı olmak için önemli bilgiler sağlamaktadır. Literatürde QRS tespiti ile ilgili birçok çalışma bulunmaktadır. Tüm bu çalışmalar, elektriksel gürültü, taban hattı kayması, kas gürültüleri, küçük ve geniş QRS kompleksleri dahil olmak üzere QRS algılamanın geliştirilmesine odaklanmıştır. Bununla birlikte, bazı QRS kompleksleri morfolojik ve aritmik bozuklukları nedeniyle tespit edilemez. Bu vuruş türleri gözlem sırasında yanlış değerlendirilir. Bu nedenle, bu tür algoritmaların başarısını ve doğruluğunu arttırmak, giyilebilir kalp tanı cihazlarının geliştirilmesi için büyük önem taşımaktadır. Aritmik EKG sinyalleri, otomatik olarak algılanması çok zor olan ani, dar, küçük ve negatif QRS kompleksleri gibi farklı morfolojik özellikleri içerir. Bu çalışmada, bu tür QRS komplekslerinin saptanması için literatürdeki diğer çalışmalardan daha yüksek doğrulukta yeni bir algoritma önermekteyiz. Dijital filtrelemeye ve Ayrık Dalgacık Dönüşümüne (ADD) dayanan bu yöntem MIT / BIH aritmi veri tabanındaki 48 hastadan elde edilen iki kanallı EKG kayıtlarını kullanarak değerlendirildi ve test edildi. Bu algoritmanın genel performans sonuçlarında, duyarlılık %99,79, öngörme oranı %99,95, algılama hata oranı 0,26 ve doğruluk skoru %99,74 olarak hesaplanmaktadır.

Keywords

• Elektrokardiyogram,QRS Yakalama,Ayrık Dalgacık Dönüşümü,Sayısal Süzgeçler

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