# Noise-Assessment-Based Screening Method for Remote Photoplethysmography Estimation
## 6 Conclusions  
The performance enhancement of an algorithm itself has inherent limitations. Therefore, it is often necessary to refine and extract essential data through pre-processing or rPPG screening techniques to achieve improved performance. For instance, research focused on enhancing the performance of remote photoplethysmography (rPPG) includes methods such as skin segmentation or pre-processing approaches that identify regions with prominent blood flow changes. In this paper, we propose an rPPG screening method for selecting reliable data from the extracted rPPG signals. Our proposed method has demonstrated significant performance improvements in most cases compared to the absence of rPPG screening. Notably, when applied to the total dataset, which contains not only still videos but also videos with motion, the method yields a remarkable \(23.47\%\) (\(=\frac{62.27\%-50.43\%}{50.43\%}\times 100\%\)) _PTE6_ performance increase, particularly when SVR is utilized (from Table 3). Furthermore, the proposed method exhibits a low computational complexity, enabling real-time application and integration with existing rPPG extraction methods. Future work can involve  
Figure 11: Detailed analysis of the motion with talk scenario in Subject 02. (**a**) Ground truth MAE presented in a bar graph, where red bars represent accepted regions and black bars represent abandoned regions, alongside the predicted MAE displayed in a dotted-line graph. (**b**) Comparison of cPPG and rPPG signals within the accepted area. (**c**) Comparison of cPPG and rPPG signals within the abandoned area.  
investigating data in more challenging scenarios with frequent interferences, such as in vehicular environments or under various light movements. Additionally, the effectiveness of the algorithm in RGB camera environments warrants further exploration. Furthermore, we anticipate that the rPPG screening method will find applications not only in rPPG enhancement but also in other vital sign measurements, such as remote respiration and blood pressure measurement [31; 32; 33].  
Conceptualization, K.L. and E.C.L.; methodology, K.L.; software, K.L. and S.K.; validation, K.L., S.K., B.A., H.S. and S.P.; formal analysis, K.L. and S.K.; investigation, K.L., B.A., H.S. and S.P.; resources, S.K., B.A., H.S. and S.P.; data curation, B.A., H.S. and S.P.; writing--original draft preparation, K.L. and S.K.; writing--review and editing, E.C.L.; visualization, K.L., B.A., H.S. and S.P.; supervision, E.C.L.; project administration, E.C.L. All authors have read and agreed to the published version of the manuscript.  
This paper was supported by the Field-Oriented Technology Development Project for Customs Administration through National Research Foundation of Korea (NRF) funded by the Ministry of Science & ICT and Korea Customs Service (2022M31A1095155).  
Based on the 13-1-3 of the Enforcement Regulations of the Act on Bioetitics and Safety of the Republic of Korea, ethical review and approval were waived (IRB-SMU-C-2023-1-008) for this study by Sangmyung University Institutional Review Board, because this study uses only simple contact-measuring equipment or observation equipment that does not follow physical changes.  
Informed Consent Statement: Informed consent was obtained from all subjects involved in the study.  
The obtained data cannot be shared because it was agreed that it could be used only for this study.  
The authors declare no conflict of interest.