Performance Analysis of PPG Signal Denoising Method Using DWT and EMD for Detection of PVC and AF Arrhytmias: Analisis Performansi Metode Denoising Sinyal PPG Menggunakan DWT dan EMD untuk deteksi Aritmia PVC dan AF - Muhammad Aniq Wafa; Satria Mandala; Miftah Pramudyo (School of Computing, Telkom University, 2022)
In the cardiac arrhythmia detection system using a Photoplethysmography (PPG) sensor, noise is often found in the PPG signal due to internal and external factors in the signal retrieval process. So it is necessary to do a denoising process to remove noise before the signal is used. This study aims to test the Discrete wavelet transform (DWT) and Empirical Mode Decomposition (EMD) methods in removing noise from the PPG signal and to test the denoising signal on the Premature Arrhythmia Verticular Contractions (PVC) and Atrial Fibrillation (AF) detection systems. The parameters used to compare the performance of the denoising method are Mean Square Error (MSE), Signal to Noise Ratio (SNR), Accuracy, F1, Precision, and Recall. The method with the highest SNR, Accuracy, F1, Precision, and Recall values ​​and the lowest MSE values ​​is the best denoising method.