# Noise-Assessment-Based Screening Method for Remote Photoplethysmography Estimation  
[PERSON]  
1 Department of Computer Science, Graduate School, Sangmyung University, Seoul 03016, Republic of Korea; [EMAIL_ADDRESS]  
[PERSON]  
2 Department of AI & Informatics, Graduate School, Sangmyung University, Seoul 03016, Republic of Korea; [EMAIL_ADDRESS] (S.K. ); [EMAIL_ADDRESS] (B.A. ); 2022320308 sangmyung.kr (B.A. ); [EMAIL_ADDRESS] (S.P)  
[PERSON]  
2 Department of Human-Centered Artificial Intelligence, Graduate School, Sangmyung University, Seoul 03016, Republic of Korea  
[EMAIL_ADDRESS]  
[PERSON]  
2 Department of AI & Informatics, Graduate School, Sangmyung University, Seoul 03016, Republic of Korea; [EMAIL_ADDRESS] (S.K. ); [EMAIL_ADDRESS] (B.A. ); 2022320308 sangmyung.kr (H.S. ); [EMAIL_ADDRESS] (S.P)  
[PERSON]  
2 Department of Human-Centered Artificial Intelligence, Graduate School, Sangmyung University, Seoul 03016, Republic of Korea  
[EMAIL_ADDRESS]  
[PERSON]  
2 Department of AI & Informatics, Graduate School, Sangmyung University, Seoul 03016, Republic of Korea; [EMAIL_ADDRESS] (B.A. ); 2022320308 sangmyung.kr (H.S. ); [EMAIL_ADDRESS] (S.P)  
[PERSON]  
3 Department of Human-Centered Artificial Intelligence, Graduate School, Sangmyung University, Seoul 03016, Republic of Korea  
35C20  
enhance the accuracy of remote sensing pulse signal measurements, methods based on remote photoplethysmography (rPPG) still exhibit limitations that render them susceptible to motion and illumination noise. This vulnerability arises due to the propensity for skin color changes resulting from cardiac activity to be easily contaminated by noise on a significantly larger scale [4]. Particularly in driving environments, remote heart rate measurements frequently contend with variations in external lighting conditions, encompassing factors such as solar light (both during daytime and night-time), traffic lights, and headlights. To address these challenges, related works within vehicular settings have explored the application of infrared cameras as an alternative to RGB cameras. Figure 1 illustrates the intensity of light across different wavelength bands, corresponding to various light sources. Notably, within the 940 nm wavelength band, the influence of sunlight diminishes considerably compared to other bands, owing to the impact of H\({}_{2}\)O in the atmosphere [5]. Consequently, by implementing bandpass filtering within the 940 nm wavelength band, the adverse effects of sunlight can be substantially mitigated, thereby alleviating noise caused by this specific light source. However, it is important to acknowledge that an infrared camera operating at a wavelength of 940 nm remains susceptible to the subject's motion as well as other light sources emitting light within the same wavelength range. In this paper, we present a novel rPPG screening method that facilitates remote photoplethysmography (rPPG) measurements within complex environments, especially for driving situations, without the need for additional attachment equipment. Our proposed method works within an infrared-camera-based measurement environment that can detect light within the 940 nm wavelength band. The proposed method introduces a noise-assessment-based pulse signal screening algorithm aimed at enhancing the accuracy of remote heart rate measurement. This algorithm defines metrics for noise assessment, including motion noise, illumination noise, and signal-to-noise ratio (SNR) indicators of the heart rate signal. By evaluating video clips that are susceptible to errors in pulse signal measurement, the algorithm selects high-quality clips for pulse signal extraction based on noise assessment. Figure 2 below depicts the overall flow of this research. Figure 1: Spectrum of solar radiation according to the wavelength range. Existing studies have primarily focused on steps 2 through 6 from Figure 2, which are the parts of the process that remove noise or extract signal from the image itself.