Effectiveness of Remote PPG Construction Methods: A Preliminary Analysis

Abstract

The contactless recording of a photoplethysmography (PPG) signal with a Red-Green-Blue (RGB) camera is known as remote photoplethysmography (rPPG). Studies have reported on the positive impact of using this technique, particularly in heart rate estimation, which has led to increased research on this topic among scientists. Therefore, converting from RGB signals to constructing an rPPG signal is an important step. Eight rPPG methods (plant-orthogonal-to-skin (POS), local group invariance (LGI), the chrominance-based method (CHROM), orthogonal matrix image transformation (OMIT), GREEN, independent component analysis (ICA), principal component analysis (PCA), and blood volume pulse (PBV) methods) were assessed using dynamic time warping, power spectrum analysis, and Pearson’s correlation coefficient, with different activities (at rest, during exercising in the gym, during talking, and while head rotating) and four regions of interest (ROI) : the forehead, the left cheek, the right cheek, and a combination of all three ROIs. The best performing rPPG methods in all categories were the POS, LGI, and OMI methods; each performed well in all activities. Recommendations for future work are provided.

Evaluating RGB channels in remote photoplethysmography: a comparative study with contact-based PPG

“…The choice was based on a combination of ROIs from the right cheek, left cheek, and forehead, as proposed by other authors (Kwon et al, 2015;Kim et al, 2021). Specifically, the landmarks were (107,66,69,109,10,338,299,296,336,9) from the forehead, (118,119,100,126,209,49,129,203,205,50) from the left cheek, and (347,348,329,355,429,279,358,423,425,280) from the right cheek (Haugg et al, 2022). After extracting the ROIs, the average of each color was calculated for each frame.…”

“…We hypothesize that the green channel is ideal for rPPG signal extraction. This is explored through algorithms like PCA (Lewandowska et al, 2011), CHROM-based rPPG 10.3389/fphys.2023.1296277 (De Haan and Jeanne, 2013), LGI (Pilz et al, 2018), POS (Wang et al, 2016), and emerging deep learning methods (Yu et al, 2019;Schrumpf et al, 2021), over diverse datasets (Haugg et al, 2022;van Es et al, 2023). Understanding the reliability of RGB signals, influenced by recording settings and subject factors, is crucial when compared to cPPG for robust signal transformation (Charlton et al, 2023).…”

A Novel Non-Contact Detection and Identification Method for the Post-Disaster Compression State of Injured Individuals Using UWB Bio-Radar

“…In severe cases, diffuse intravascular coagulation or acute respiratory distress syndrome may also occur, leading to multiple organ failure, and ultimately shock and death of the injured person [ 5 , 6 ]. Compared with traditional non-contact post-disaster search and rescue devices, such as visible light or thermal imaging [ 7 ], bio-radar can detect vital signs, such as breathing and a heartbeat, caused by human cardiopulmonary activity at longer distances and behind obstacles [ 8 , 9 ]. It has become one of the most promising technologies for disaster rescue detection [ 10 , 11 , 12 , 13 , 14 , 15 , 16 , 17 ].…”

The Use of Photoplethysmography in the Assessment of Mental Health: Scoping Review

“…Photoplethysmography (PPG) is an emerging technology that uses light to measure microvascular blood changes to assess various cardiovascular parameters that are useful in clinical settings [ 1 , 2 ], including blood pressure [ 3 , 4 ] and heart rate (HR) [ 5 ]. This technology can quickly and easily assess vasoconstriction and dilation in the skin, autonomic function changes, and vascular functions [ 6 ].…”

“…This technology can quickly and easily assess vasoconstriction and dilation in the skin, autonomic function changes, and vascular functions [ 6 ]. PPG assesses these physiological changes through a clip placed on a body part, such as the finger or ear [ 7 , 8 ], and smartphone apps [ 5 , 9 ].…”