Investigating the preprocessing methods in ECG analysis

Date

2021-07-19

Author

Ekinci, Göktuğ
Kardeş, Ege
Güvenkaya, Hazal
Karagöz, Pınar

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The electrocardiogram (ECG) signals are basically the combination of sequential electrical impulses generated by tissues in the heart. In the last decades, by using ECG signals, various studies such as heart beat classification, arrhythmia analysis, anomaly detection, and diagnosis of heart-related diseases have been conducted with various neural network (NN), and machine learning (ML) approaches. Regardless of the approach to obtain more accurate results, various preprocessing methods are applied to data. It is observed that performing preprocessing is crucial for the sake of the related analysis. In this paper, focused on studies in the last decade, ECG analysis steps are briefly explained and mentioned approaches are reviewed on their preprocessing methods in detail.

URI

http://dx.doi.org/10.1109/siu53274.2021.9477702
https://hdl.handle.net/11511/95405

DOI

https://doi.org/10.1109/siu53274.2021.9477702

Conference Name

29th Signal Processing and Communications Applications Conference (SIU)

Collections

Department of Computer Engineering, Conference / Seminar

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Citation Formats

G. Ekinci, E. Kardeş, H. Güvenkaya, and P. Karagöz, “Investigating the preprocessing methods in ECG analysis,” presented at the 29th Signal Processing and Communications Applications Conference (SIU), 2021, Accessed: 00, 2022. [Online]. Available: http://dx.doi.org/10.1109/siu53274.2021.9477702.