Work

Detection of cardiac abnormalities in ECG signal using time-based signal processing algorithm

Year: 2024

Type: article

Abstract: Electrocardiograms are bioelectrical signals that provide information regarding the normal and abnormal physiology of the heart.Early detection of cardiac irregularities in cardiac patients prevents strokes and sudden deaths.The effective functioning of the heart in each individual is dependent on the amplitude and interval values of the P-QRS-T segment.In this work, a modified Pan-Tompkins algorithm is used for identifying the characteristic points.Various signal characteristics, including R-R interval, T-amplitude, and QRS duration, were meticulously quantified and compared with NSR to determine ECG cardiac problems.Further, different cardiac abnormalities such as atrial fibrillation (AF), right bundle branch block (RBBB), cardiac ischemia (CI), left bundle branch block (LBBB), bradycardia, and tachycardia are detected using the time and amplitude features of the ECG.The suggested method was evaluated on three major online Physionet ECG databases (the AFDB, NSR, and MIT-BIH Arrhythmia databases) to assess its generalisability.

Source: International Journal of Computational Vision and Robotics

DOI: 10.1504/ijcvr.2025.143052

Authors: Kiran Kumar Patro, Allam Jaya Prakash, Geetamma Tummalapalli, P. Lalitha Kumari, M. Jaya Manmadha Rao

Institutions: Jawaharlal Nehru Technological University, Kakinada, GMR Institute of Technology

Language: English

Topic: ECG Monitoring and Analysis

Subfield: Cardiology and Cardiovascular Medicine

Field: Medicine

Domain: Health Sciences

SDG: Good health and well-being

Open Access status: bronze

OpenAlex ID: W4404966366

FWCI: 0.544

Cites:

Cited by: 2

Related to: 10