|RMJ. 2022; 47(3): 741-745
An improved Kalman Filter in Photoplethysmography DC Component Denoising for cardiorespiratory analysis
Muhammad Kashif, Muhammad Fahmi, Dita Aprilia Hariyani, Akif Rahmatilah, Khusnul Ain, Yunus Susilo, Ardiyansyah Syahrom, Suryani Dyah Astuti.
|Cited by 0 Articles|
Objective: To design an improved accuracy filter for photoplethysmography Direct Current (DC) component denoising and clinically applicable measurement design.
Methodology: The data source for this study was obtained from Physionet. The obtained PPG signal was mixed with seven different types of noises. The seven different derivates of PPG signals were denoised using 4 types of denoisers that were designed using Infinite impulse response (IIR), finite impulse response (FIR), Kalman, and improved Kalman filters. The difference can be measured by the SNR value, the lower signal to noise ratio (SNR) value shows higher noise in the signal.
Results: SNR value achieved on FIR filter was 7.54dB, IIR 9.08dB, Kalman 18.96dB and the maximum SNR achieved on the improved Kalman filter which is 24.76 dB.
Conclusion: It can be said that the Improved Kalman Filter is more appropriate for DC signal denoising in PPG signals rather than the FIR filter, IIR filter, and Kalman filter.
Key words: PPG signal, motion artifact, Kalman filter, Health care.