An improved cardiac arrhythmia classification using an RR interval-based approach

• Autorzy: Rahul Jagdeep , Sora Marpe , Sharma Lakhan Dev , Bohat Vijay Kumar

Identyfikatory

DOI

10.1016/j.bbe.2021.04.004

• Języki publikacji: EN

Abstrakty

EN

Accurate and early detection of cardiac arrhythmia present in an electrocardiogram (ECG) can prevent many premature deaths. Cardiac arrhythmia arises due to the improper conduction of electrical impulses throughout the heart. In this paper, we propose an improved RR interval-based cardiac arrhythmia classification approach. The Discrete Wavelet Transform (DWT) and median filters were used to remove high-frequency noise and baseline wander from the raw ECG. Next, the processed ECG was segmented after the determination of the QRS region. We extracted the primary feature RR interval and other statistical features from the beats to classify the Normal, Premature Ventricular Contraction (PVC), and Premature Atrial Contraction (PAC). The K-Nearest Neighbour (k-NN), Support Vector Machine (SVM), Decision Tree (DT), Naı¨ve Bayes (NB), and Random Forest (RF) classifier were utilised for classification. Overall performance of SVM with Gaussian kernel achieved Se % = 99.28, Sp % = 99.63, +P % = 99.28, and Acc % = 99.51, which is better than the other classifiers used in this method. The obtained results of the proposed method are significantly better and more accurate.

Słowa kluczowe

EN

ECG; electrocardiogram; cardiac arrhythmia; RR interval; PVC; premature ventricular contraction; PAC; premature atrial contraction

PL

EKG; elektrokardiogram; arytmia serca; odstęp RR; interwał RR; PVC; PAC

• Wydawca: Nałęcz Institute of Biocybernetics and Biomedical Engineering of the Polish Academy of Sciences ; Elsevier
• Czasopismo: Biocybernetics and Biomedical Engineering
• Rocznik: 2021
• Tom: Vol. 41, no. 2
• Strony: 656--666
• Opis fizyczny: Bibliogr. 77 poz., rys., tab., wykr.

Twórcy

autor

Rahul Jagdeep

• Department of Electronics & Communication Engineering, Rajiv Gandhi University, India

autor

Sora Marpe

• Department of Computer Science & Engineering, Rajiv Gandhi University, India

autor

Sharma Lakhan Dev

• School of Electronics Engineering VIT-AP University, India

autor

Bohat Vijay Kumar

• Department of Computer Science and Engineering, Bennett University, India

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Uwagi

Opracowanie rekordu ze środków MNiSW, umowa Nr 461252 w ramach programu "Społeczna odpowiedzialność nauki" - moduł: Popularyzacja nauki i promocja sportu (2021).