## 7 Discussion  
The main peak of the pulse and the dicrotic notch on the down slope of each cycle are the two primary characteristics for the contour of each PPG pulse. However, when PPG pulses are used to measure the heart rate and oxygen saturation, previous studies always focus on whether the main peak of the PPG pulse is clear and the baseline is drifted or not [10; 14; 16]. The reason is that the amplitude of pulsatile waveform and the baseline are used to measure the peripheral oxygen saturation [3]. Thus, they used the rule-based algorithms to determine the SQI of each PPG pulse. The quality level of each PPG pulse was defined by experts in a manual fashion. However, in the validation of their algorithms, a direct comparison of performance between two published algorithms is restricted because the cognitive abilities of experts are different. Thus, the main characteristics of the PPG pulse for the high SQI depends on the measuring physiological parameters. In our study, we adopt a kind of expert system, SoNFIN, to evaluate the quality level of each individual PPG pulse, and the SVs measured by our ICG device are compared with those (as reference) by the medis(r) CS2000. We use three levels of the error percentage (that is, less than 40%, between 40% and 45%, and larger than 45%) to define each PPG pulse belonging to high, middle, or low SQI categorization. This approach can readily quantify the quality level of individual PPG pulses. The current show that the proposed algorithm can effectively pick up PPG pulses belonging to high SQI and increase the accuracy in the SV measurement of ICG. LVET is the time interval initiated at the opening of the aortic valve and terminated at the closing of the aortic valve. During the LVET, the blood is pumped from the left ventricle to the aorta. Thus, in the ICG waveform, the starting ejection point is the first zero crossing point of its differential waveform during systole. The ending ejection point is the time for the first maximum valley of its differential waveform during systole, which happens before the dicrotic notch. According to the study by [PERSON] et al. [4], only a stable PPG signal can provide a reliable LVET. If the SQI of PPG waveform is applied to indirectly calculate LVET, the starting ejection point, dicrotic notch, and baseline drift are the main characteristics of pulse waveform. Unfortunately, a corrupted PPG signal is mainly caused by the body motions, in which an unstable differential PPG signal would provide an inaccurate LVET measurement. Moreover, it is found that the motion artifact more easily corrupts the signal baseline of the reflective PPG sensor than the transmissive PPG sensor. Therefore, in the study, we employ not only the rule-based algorithm to delete the severely corrupted pulses, but we also use the SoNFIN to help determine the SQI of individual PPG pulses. We only used 201 PPG pulses to train the SoNFIN, but a total of 1466 PPG pulses were used in the testing phase. When the SVs were measured using those PPG pulses with high SQI, we gained a relatively small mean statistic error of 6.4 \(\pm\) 12.8 mL as compared with the reference. On the other hand, when the SVs are measured using the PPG pulses with low SQI, a large statistic error of \(\sim\)39.5 \(\pm\) 17.1 mL was obtained. This method was very different for those in previous studies. The results show that the proposed algorithm could be used to the actual ICG applications, since the PPG pulses with high SQI could provide more accurate SV measurements. The number of PPG pulses in the border (moderate accuracy) region