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1

A new approach to adaptive threshold based method for QRS detection with fuzzy clustering

Pander Tomasz

Biocybernetics and Biomedical Engineering

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2022

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Vol. 42, no. 1

404--425

EN

The most crucial requirements for a QRS complex detection algorithm are accuracy, precision and repeatability. Most methods of detecting QRS complexes use the approach based on exceeding a certain amplitude threshold. However, the presence of noise in the electro-cardiographic signal can inhibit the accuracy and precision of detection especially for low amplitude QRS-complexes. The proposed algorithm uses a new approach for the amplitude threshold determination and in the decision stage. The fuzzy c-median clustering method is used to determine the amplitude threshold values for each sliding window across the composed detection function waveform. It allows us to adjust threshold value to noise variations in the ECG signal. When a specified amplitude threshold is exceeded by the detection function and finding the peaks in its waveform, potential QRS complexes can be identified. Then the identified peaks are evaluated on the basis of the speed of rising and falling slopes of detection function peak. It enables identification of only those peaks of the detection function whose location corresponds to QRS complexes. ECG recordings taken from the standard-available eight databases are used to evaluate the performance quality of the proposed method. The proposed QRS detector achieved sensitivity of 99.82%, positive predictivity of 99.88% over the validation MIT-BIH Arrhythmia Database. The overall sensitivity and positive predictivity are respectively 99.81% and 99.67%. Advantages of the proposed method are the robustness against noise, the accuracy and the simplicity of the algorithm that evaluates the candidate peaks of the detection function which indicate the QRS complexes.

2

Introduction to wavelet based adaptive techniques in QRS complex analysis procedures

Irzmański P., Jóśko A.

Przegląd Elektrotechniczny

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2014

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R. 90, nr 6

243--245

PL

W artykule przedstawione jest wprowadzenie do zagadnienia automatycznej i adaptacyjnej detekcji oraz analizy zespołów QRS w zapisach elektrokardiograficznych. W przeprowadzonych badaniach stosowano algorytmy, w których wykorzystano transformacje falkowe. Głównym celem opisanych badań jest opracowanie wiarygodnej procedury detekcji i opisu zespołów QRS prawidłowych oraz anormalnych. Wśród tych drugich skupiono się na zespołach pochodzenia komorowego.

EN

The article discusses the problem of the automatic QRS complex detection in the electrocardiography signals. Among other approaches the wavelet based algorithms are the ones of the most promising outcomes. Authors propose introduction of elements of adaptive techniques to the original scheme. The main aim is to achieve reliable detection and analysis procedure for different morphologies of QRS complexes both normal and dysfunctional cases, with the main focus on ventricular arrhythmias.

3

QRS detector approach for on-line purposes

Figoń P., Irzmański P., Jośko A., Rak R., Staroszczyk Z.

Przegląd Elektrotechniczny

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2013

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R. 89, nr 4

248-250

EN

The problem of real time restrictions and effectiveness requirements of the QRS detection algorithm is presented in the paper. Several approaches were taken into account and were tested during the research. CSE ECG databases were used as test signal set. FIR and IIR filters were investigated as well as different filter coefficients floating point data types. The paper summarises Authors’ investigations in the field of QRS detector application to the contemporary market platform.

PL

W artykule przedstawione zostały zagadnienia dotyczące wymagań stawianych algorytmom do detekcji zespołów QRS, przeznaczonych do pracy w czasie rzeczywistym. Szczególnie ważne są przeciwstawne problemy, które dotyczą skuteczności pracy algorytmu i szybkości jego działania. W trakcie testów wykorzystano wiele rozwiązań bazujących na filtrach SOI oraz NOI oraz różnych formatach współczynników filtrów.

4

Detekcja zespołów QRS w zakłóconym sygnale EKG

Ćmielowski Ł., Wilk B.

Zeszyty Naukowe Politechniki Rzeszowskiej. Elektrotechnika

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2005

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z. 28 [223]

45-53

PL

W artykule omówiono i porównano kilka metod przeznaczonych do detekcji zespołów QRS o prawidłowej morfologii, które są najczęściej implementowane w systemach przetwarzających zakłócony sygnał EKG. Ponadto zaprezentowano cyfrowy detektor QRS bazujący na ciągłej transformacie falkowej (ang. CWT), który zapewnia dużą dokładność detekcji w przypadku zakłóconego sygnału EKG.

EN

In this paper. the most popular QRS detection methods implemented usually for noisy ECG signal are described and compared. A new QRS detector based on the wavelet transform (CWT) is presented. This algorithm gives a good accuracy of QRS complexes detection, specially for noisy ECG signal.

5

Evaluation of the shape-varying structuring element in QRS detection for ECG compression

Tadejko P., Rakowski W.

Image Processing & Communications

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2005

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Vol. 10, no 2

27-38

EN

Morphological operations are simple mathematical constructs, which have led to effective solution for many problems in signal and image processing. These solutions employ discrete operators (structuring element) and are applied to digitized signals. The paper presents the mathematical morphology approach to the recognition and classification of heart rhythms on the basis of electrocardiogram (EGG) waveforms. The main part in recognition is based on the morphological niters characterization of the QRS complexes. In this work, we present morphological filtering as a preliminary step for compression of ECG data using image compression algorithms. To corn-press the ECG data using for example JPEG2000, SPITH or other codec, the one-dimensional ECG sequence needs to be processed to produce a two-dimensional matrix. Detecting operator designed for creating sequence is controlled by the shape and size of the structuring element. We compare how shape and length of this element can affects sensitivity detection algorithm based on amplitude and slope. The performance of the algorithm is evaluated with standard MIT/BIll arrythmia database.

6

Digital signal processing in ECG recorder with Python-based software

Kosiński W., Owczarek A., Jarocki B., Momot M., Płaczek M., Zegartowski G., Gacek A.

Journal of Medical Informatics & Technologies

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2003

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Vol. 6

IT61--68

EN

The aim of the paper is to present the possibilities and the advantages of using open source solution like Python and Linux in medical application development. An implementation of the QRS detection and classification is described as an example of integration of C++ and DSP toolkit in a Python application.