title: Current methods in electrocardiogram characterization.
abstract: The Electrocardiogram (ECG) is the P-QRS-T wave depicting the cardiac activity of the heart. The subtle changes in the electric potential patterns of repolarization and depolarization are indicative of the disease afflicting the patient. These clinical time domain features of the ECG waveform can be used in cardiac health diagnosis. Due to the presence of noise and minute morphological parameter values, it is very difficult to identify the ECG classes accurately by the naked eye. Various computer aided cardiac diagnosis (CACD) systems, analysis methods, challenges addressed and the future of cardiovascular disease screening are reviewed in this paper. Methods developed for time domain, frequency transform domain, and time-frequency domain analysis, such as the wavelet transform, cannot by themselves represent the inherent distinguishing features accurately. Hence, nonlinear methods which can capture the small variations in the ECG signal and provide improved accuracy in the presence of noise are discussed in greater detail in this review. A CACD system exploiting these nonlinear features can help clinicians to diagnose cardiovascular disease more accurately.
authors.affiliation: Department of Electronics and Computer Engineering, Ngee AnnPolytechnic, Singapore 599489, Singapore. Electronic address: roshaniitsmst@gmail.com.
authors.forename: Roshan Joy
authors.initials: RJ
authors.lastname: Martis
authors.affiliation: Department of Electronics and Computer Engineering, Ngee AnnPolytechnic, Singapore 599489, Singapore; Department of Biomedical Engineering, Faculty of Engineering, University of Malaya, 50603, Malaysia. Electronic address: aru@np.edu.sg.
authors.forename: U Rajendra
authors.initials: UR
authors.lastname: Acharya
authors.affiliation: Departments of Biomedical Engineering, Biomedical Informatics, Civil and Environmental Engineering and Geodetic Science, Electrical and Computer Engineering, Neurological Surgery, and Neuroscience, The Ohio State University, 470 Hitchcock Hall, 2070 Neil Avenue, Columbus, OH 43210, United States. Electronic address: adeli.1@osu.edu.
authors.forename: Hojjat
authors.initials: H
authors.lastname: Adeli
mesh_terms: D001145:Arrhythmias, Cardiac / Q000175:diagnosis / Q000503:physiopathology; D003936:Diagnosis, Computer-Assisted / Q000379:methods*; D004562:Electrocardiography / Q000379:methods*; D006801:Humans; D012815:Signal Processing, Computer-Assisted
keywords: Arrhythmia; Cardiovascular diseases (CVD); Computer aided cardiac diagnosis (CACD); Electrocardiogram; Non-linear methods; Transform domain techniques; Wavelets