Key result
Review summarizes a decade of ECG analysis techniques including preprocessing, feature extraction, and classification.
Why the study?
Accurate analysis of ECG signals is essential for detection, classification, and diagnosis of cardiac problems, but a concise summary of earlier techniques is needed to guide future research.
This review provides an overview of ECG signal processing and classification techniques to support further research in automated diagnosis.
May aid ECG technique selection in research; leaves open clinical validation of automated diagnosis.
In recent years, cardiac problems have been found proportional to technology development. As the cardiac signal (Electrocardiogram) relates to the electrical activity of the heart of a living being, the technology develops accordingly day-by-day to support physicians and diagnosis. It has many applications along with medical applications. Accurate analysis of electrocardiogram (ECG) signal can information for detection, classification, and diagnosis. This paper insight towards a short review of earlier techniques. It will support the researchers in a new direction. The review is based on preprocessing, feature extraction, classification, and different measures for accuracy proof and the related work reported during the last decade is summarized.
No takes yet. Share an insight, caveat, or question.
Mohapatra et al. (2019) conducted a review in Cardiac problems. ECG analysis techniques was evaluated. A brief review summarizes ECG analysis techniques, including preprocessing, feature extraction, and classification methods reported during the last decade.
Synapse has enriched 5 closely related papers on similar clinical questions. Consider them for comparative context: