# A Survey of Photoplethysmography and Imaging Photoplethysmography Quality Assessment Methods
## 1 Introduction  
A photoplethysmograph (also known as photoelectric plethysmograph, or PPG) is an instrument using light to measure blood volume changes in tissues [1, 2]. A PPG signal can be extracted from several parts of the body (e.g., finger, ear, forehead, wrist) [2, 3]. The conventional principle is called contact PPG (cPPG) and consists of a device in contact with the skin, emitting a controlled light beam. According to the Beer-Lambert law, this light will be transmitted, absorbed, or dispersed by the different elements constituting the tissues (e.g., blood components in capillaries or arterioles, keratin and melanin in epidermis [4, 5]). Then, the output light is received by a photoreceptor [6]. The evolution with time of the light received by the receptor allows one to visualize the blood flow in a specific portion of tissue. The measurement of PPG can be based on the transmittance or reflectance mode. In transmittance mode, the source of light and the photoreceptor face each other and the receptor measures the light that has not been absorbed by the tissue. In reflectance mode, the light source and receptor are side by side and the receptor measures the light that is reflected from the tissue. PPG signals have applications in the monitoring of patients and extraction of vital signs [7]. The simplicity and low cost of the technology allow its integration in various devices, such as oximeters, smartwatches, or smartphones. It can be used in applications such as home monitoring, or in measurements performed during physical activities such as running. Furthermore, the emergence of imaging photoplethysmography (iPPG) potentially allows the same applications using only the ambient light modulated and reflected by the blood from the skin and captured by a camera. The development of iPPG could allow physiological measurement during telemedicine, by using a webcam or a smartphone camera, to support the diagnosis of a clinician. However, during a measurement, the signal obtained from a device can be corrupted by perturbations called artifacts. Consequently, the interpretation of the output signal is impossible or erroneous, which could lead to false diagnosis or to the rising of false alarms. Thus, the discrimination between signals of high and low quality can help to detect the presence of perturbations. To avoid asking the opinion of an expert for each occurrence of an artifact and to maintain the high performance of the monitoring device, the field of quality assessment algorithms has been developed. Many algorithms have been suggested, evolving with the possibilities offered by devices, and depending on the application that the PPG signal is used for. Several reviews have been presented on the topic of quality assessment of contact PPG signals. [PERSON] et al. [8] reviewed papers suggesting artifact detection algorithms for critical care units between 1989 and 2012. [PERSON] published a book [9] in 2018 addressing the quality assessment of contact PPG signals for rule-based and machine learning-based methods. Two smaller reviews have been recently published by [PERSON] et al. [10] and [PERSON] et al. [11]. [PERSON] et al. provided a definition of PPG signal quality and discussed methods used for its assessment. [PERSON] et al. published a review on PPG signal features, applications, and processing methods, including a section on signal quality indexes, in which they presented an overview of quality assessment algorithms oriented around feature-based methods and machine learning/deep learning-based methods. However, to the best of our knowledge, no survey has been done on the topic of quality assessment applied to iPPG. In this review, we try to provide an exhaustive view on the latest methods dedicated to quality assessment and discuss the methodology used for the creation of those algorithms for both cPPG and iPPG. This paper presents an overview of the different methods used to assess the quality of a PPG signal and discuss the methodology in the design of those methods.