Applying Fourier series analysis on a cycle-by-cycle basis to photoplethysmographic signals provided 35 dB reduction in motion artifacts and achieved a data compression factor of 12.
Applying Fourier series analysis to PPG signals effectively reduces motion artifacts by 35 dB and compresses data by a factor of 12 without losing morphological features.
Pulse oximeters require artifact-free clean photoplethysmograph (PPG) signals obtained at red and infrared (IR) wavelengths for the estimation of the level of oxygen saturation (SpO₂) in the arterial blood of a patient. Movement of a patient corrupts a PPG signal with motion artifacts and introduces large errors in the computation of SpO₂. A novel method for removing motion artifacts from corrupted PPG signals by applying Fourier series analysis on a cycle-by-cycle basis is presented in this paper. Aside from artifact reduction, the proposed method also provides data compression. Experimental results indicate that the proposed method is insensitive to heart rate variation, introduces negligible error in the processed PPG signals due to the additional processing, preserves all the morphological features of the PPG, provides 35 dB reduction in motion artifacts, and achieves a data compression factor of 12.
Reddy et al. (Thu,) conducted a other in Motion artifacts in photoplethysmographic (PPG) signals. Fourier series analysis on a cycle-by-cycle basis was evaluated on Motion artifact reduction and data compression. Applying Fourier series analysis on a cycle-by-cycle basis to photoplethysmographic signals provided 35 dB reduction in motion artifacts and achieved a data compression factor of 12.