This paper introduces a mathematical model that incorporates the optical and physiological properties of skin reflections to better understand the algorithmic principles behind remote photoplethysmography (rPPG). The model is used to explain the different choices made in existing rPPG methods for pulse extraction. The understanding gained from the model can be used to design robust or application-specific rPPG solutions. The paper illustrates this by designing an alternative rPPG method where a projection plane orthogonal to the skin-tone is used for pulse extraction. A large benchmark on various rPPG methods shows that their relative merits can indeed be understood from the proposed model. The paper discusses the algorithmic principles of rPPG in a mathematical context with optical and physiological reasoning. The study shows that different characteristic properties of rPPG can be used to design algorithmic solutions for pulse extraction. The new method defines a plane orthogonal to the skin-tone in the temporally normalized RGB space for pulse extraction, referred to as the "Plane-Orthogonal-to-Skin" (POS). The main contribution of this paper is its in-depth analysis of the working principles of rPPG (in a mathematical context), which benefits the development of novel rPPG methods. The paper presents a skin reflection model that considers the optical and physiological properties of skin reflections. It then analyzes existing rPPG methods in the model and describes a new method to demonstrate the understanding. The paper uses a benchmark to verify the analysis and concludes with a summary of the findings. The paper discusses the differences between existing rPPG methods and the new POS method, highlighting the advantages of the new method in terms of accuracy and robustness. The POS method is shown to be more tolerant to distortions and requires less accurate knowledge of the blood volume pulse signature compared to other methods. The paper concludes that the POS method is a promising approach for rPPG and has the potential to improve the accuracy and robustness of future rPPG methods.This paper introduces a mathematical model that incorporates the optical and physiological properties of skin reflections to better understand the algorithmic principles behind remote photoplethysmography (rPPG). The model is used to explain the different choices made in existing rPPG methods for pulse extraction. The understanding gained from the model can be used to design robust or application-specific rPPG solutions. The paper illustrates this by designing an alternative rPPG method where a projection plane orthogonal to the skin-tone is used for pulse extraction. A large benchmark on various rPPG methods shows that their relative merits can indeed be understood from the proposed model. The paper discusses the algorithmic principles of rPPG in a mathematical context with optical and physiological reasoning. The study shows that different characteristic properties of rPPG can be used to design algorithmic solutions for pulse extraction. The new method defines a plane orthogonal to the skin-tone in the temporally normalized RGB space for pulse extraction, referred to as the "Plane-Orthogonal-to-Skin" (POS). The main contribution of this paper is its in-depth analysis of the working principles of rPPG (in a mathematical context), which benefits the development of novel rPPG methods. The paper presents a skin reflection model that considers the optical and physiological properties of skin reflections. It then analyzes existing rPPG methods in the model and describes a new method to demonstrate the understanding. The paper uses a benchmark to verify the analysis and concludes with a summary of the findings. The paper discusses the differences between existing rPPG methods and the new POS method, highlighting the advantages of the new method in terms of accuracy and robustness. The POS method is shown to be more tolerant to distortions and requires less accurate knowledge of the blood volume pulse signature compared to other methods. The paper concludes that the POS method is a promising approach for rPPG and has the potential to improve the accuracy and robustness of future rPPG methods.