Automatic QRS Detection and Segmentation Using Short Time Fourier Transform and Feature Fusion

Biran, Abdullah; Jeremić, Aleksandar

doi:10.1109/ccece47787.2020.9255676

Cited by 4 publications

(1 citation statement)

References 15 publications

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“…Probably, the most famous and frequently used is the rather robust and simple Pan–Tompkins algorithm ( Pan and Tompkins, 1985 ). Many other R-peak detectors, using searching in the initial ECG or ECG previously transformed to highlight the QRS complexes, have been developed (e.g., Liu et al, 2015 ; Biran and Jeremic, 2020 ; Walia and Kaul, 2020 ). However, none of them is error-free; false detections lead to false alarms and thus increase the demand on intensive care units’ staff ( Plesinger et al, 2016 ).…”

Section: Ecg Analysismentioning

confidence: 99%

Golden Standard or Obsolete Method? Review of ECG Applications in Clinical and Experimental Context

et al. 2022

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Cardiovascular system and its functions under both physiological and pathophysiological conditions have been studied for centuries. One of the most important steps in the cardiovascular research was the possibility to record cardiac electrical activity. Since then, numerous modifications and improvements have been introduced; however, an electrocardiogram still represents a golden standard in this field. This paper overviews possibilities of ECG recordings in research and clinical practice, deals with advantages and disadvantages of various approaches, and summarizes possibilities of advanced data analysis. Special emphasis is given to state-of-the-art deep learning techniques intensely expanded in a wide range of clinical applications and offering promising prospects in experimental branches. Since, according to the World Health Organization, cardiovascular diseases are the main cause of death worldwide, studying electrical activity of the heart is still of high importance for both experimental and clinical cardiology.

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