Fatemeh Nasr Esfahani - Department of Electrical and Biomedical Engineering, Faculty of Engineering and Technology, Shahid Ashrafi Esfahani University,Isfahan, Iran.
Elham Razm Ara - Department of Electrical and Biomedical Engineering, Faculty of Engineering and Technology, Shahid Ashrafi Esfahani University,Isfahan, Iran.
Hajar Danesh - Department of Electrical and Biomedical Engineering, Faculty of Engineering and Technology, Shahid Ashrafi Esfahani University,Isfahan, Iran.

The ECG signal plays a crucial role in the diagnosis and monitoring of heart diseases. However, this signal is susceptible to various types of noise that can significantly affect diagnostic accuracy. This study reviews and compares modern methods for noise reduction in ECG signals. First, common types of noise in ECG signals are introduced, followed by an evaluation of contemporary approaches for noise removal. The results indicate that each introduced method has its own advantages and disadvantages. The choice of an appropriate noise reduction method for ECG signals depends on factors such as the type of noise, required accuracy, and computational limitations. This study can serve as a guide for selecting the appropriate noise reduction method in applications related to ECG signals. The presented results can help improve the accuracy of diagnosing and monitoring heart diseases. Among the methods evaluated, the CNN-based approach emerged as the most effective for identifying and eliminating complex noise patterns, offering significant advantages for improved diagnostic accuracy

Electrocardiogram, Noise Reduction, Signal Processing, Heart Disease Diagnosis