Improving Photoplethysmograph Signal Quality using Butterworth Filters: Denoising and SNR Evaluation Analysis - Nashichah, Roichatun; Lusiana; Dinda Trisakti Wahyuningtya (Medika Teknika : Jurnal Teknik Elektromedik Indonesia, 2025)
The photoplethysmography (PPG) signal is a physiological signal vulnerable to noise disorders, especially from environmental movements and interference artifacts. This noise can reduce the accuracy of signal analysis, disrupt the feature extraction, and cause errors in interpreting physiological conditions. This study aims to improve the quality of PPG signals through denoising using Butterworth filters and evaluate signal accuracy increases based on amplitude statistics and signal-to-noise ratio (SNR). The main contribution of this study is to disclose the effectiveness of the Butterworth filter configurations (low-pass and band-pass) with various orders in raising the PPG signal SNR and strengthening the stability of signal amplitude as a basis for more accurate physiological analysis. The Butterworth filters were applied with the order variations (2, 4, 6) and the configuration of low-pass or band-pass. Evaluation was carried out based on changes in the SNR value, statistical parameters, and amplitude (mean, median, standard deviation). The results revealed a significant increase in SNR from an average of 8.26 dB to 18.8 dB after filtering, with the highest increase of +12.1 dB using the band-pass order 4. Amplitude statistics unveiled a rise in stability, where the mean increased from 0.398 MV to 0.409 MV, the median rose from 0.400 MV to 0.415 MV, and the standard deviation escalated from 0.053 MV to 0.078 MV, resulting in a more consistent signal distribution post-filtering. The Butterworth filters improved the quality of PPG signals by reducing noise significantly and maintaining the integrity of the main signal. These results highlight the significance of this approach as an essential initial step in the PPG signal-based health analysis system, such as heart rate detection or vascular variability.