A review of different ECG classification/detection techniques for improved medical applications

Varun Gupta (), Nitin Kumar Saxena (), Abhas Kanungo (), Anmol Gupta (), Parvin Kumar () and Salim ()
Additional contact information
Varun Gupta: KIET Group of Institutions
Nitin Kumar Saxena: KIET Group of Institutions
Abhas Kanungo: KIET Group of Institutions
Anmol Gupta: KIET Group of Institutions
Parvin Kumar: KIET Group of Institutions
Salim: KIET Group of Institutions

International Journal of System Assurance Engineering and Management, 2022, vol. 13, issue 3, No 1, 1037-1051

Abstract: Abstract Electrocardiogram (ECG) is an important diagnostic tool in medical engineering, presented in the form of electrical signal. Its complete analysis requires three stages viz. pre-processing, feature extraction, and classification/detection. The last stage provides the final outcome; hence, its careful selection is very important. Unfortunately, due to diverse and widely varied data management practices, no single technique is absolutely preferred over others. Therefore, an extensive literature survey of various classification/detection techniques is presented, and their effects are summarized. Also, different techniques related to ECG arrhythmia classification and detection are proposed and evaluated on-the-basis-of figure-of-merits (FoMs) for improved medical applications. This proposed technique is important to extract important clinical/pathological attributes of the ECG signals. It ensures the novelty in the biomedical signal processing (BSP). In this article different existing techniques are compared in the light of proposed techniques for various ECG arrhythmias classification and detection.

Keywords: Electrocardiogram (ECG); Detection/classification; Clinical/pathological; Figure-of-merits (FoMs) (search for similar items in EconPapers)
Date: 2022
References: View complete reference list from CitEc
Citations: View citations in EconPapers (1)

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DOI: 10.1007/s13198-021-01548-3

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