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Heart rate variability and motion artifact are two major obstacles to the Photoplethysmographic (PPG) signal analysis, which is a very promising tool to derive useful information about the hemodynamics as well as autonomic nerve system. This paper suggests employing a truncation/extrapolation method on the PPG signal or its first order derivative to overcome the heart rate variability problem while extract a refined mean PPG pulse waveform. Meanwhile, the cross-correlation detection method is employed to remove the motion artifacts. Test results indicate that the proposed approach can effectively enhance the signal to noise ratio of PPG waveform and therefore verify the effectiveness of the proposed preprocessing scheme.

the fitting error (RMSE) was 1.07 +/- 0.48 mmHg. The time constant of the model shown significant difference between the highest and the lowest saturation group.

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