Atrial Fibrillation Denoise Using Wavelet Adaptive Filter

This study assesses the efficacy of a descrete wavelet transform (DWT) which combines with adaptive filters (Af) in reducing noise in electrocardiogram (ECG) signals.Noise can compromise the accuracy of ECG signals, which are crucial for diagnosing heart diseases.Typical types of noise in signal processing include powerline interference (PLI), motion artefacts (MA), baseline wander (BW), and electromyogram (EMG) interference.These noise types as either correlated or uncorrelated and removing noises from ECG signal is crucial for achieving precise diagnoses.The research proposes the use combinations of Af-WT-based filters for the filtering process.The performance of the Af-WT-based filter will be compared to tWT and Af filters, with the Af-WT filter demonstrating the acceptable signal-to-noise ratio (SNR) measurement, denoisng the PLI, MA, BW and EMG form ECG signal.