Background:
In recent years cardiac problems found proportional to technology development. Cardiac signal (Electrocardiogram) relates to the electrical activity of the heart of a living being and it is an important tool for diagnosis of heart diseases.
Method:
Accurate analysis of ECG signal can provide support for detection, classification, and diagnosis. Physicians can detect the disease and start the diagnosis at an early stage. Apart from cardiac disease diagnosis ECG can be used for emotion recognition, heart rate detection, and biometric identification.
Objective:
The objective of this paper is to provide a short review of earlier techniques used for ECG analysis. It can provide support to the researchers in a new direction. The review is based on preprocessing, feature extraction, classification, and different measuring parameters for accuracy proof. Also, different data sources for getting the cardiac signal is presented and various application area of the ECG analysis is presented. It explains the work from 2008 to 2018.
Conclusion:
Proper analysis of the cardiac signal is essential for better diagnosis. In automated ECG analysis, it is essential to get an accurate result. Numerous techniques were addressed by the researchers for the analysis of ECG. It is important to know different steps related to ECG analysis. A review is done based on different stages of ECG analysis and its applications in society.
SPECTRO-TEMPORAL ECG ANALYSIS FOR ATRIAL FIBRILLATION DETECTION
