Official websites use. Share sensitive information only on official, secure websites. Heart rate is an essential vital sign to evaluate human health. Remote heart monitoring using cheaply available devices has become a necessity in the twenty-first century to prevent any unfortunate situation caused by the hectic pace of life.
In this paper, we propose a new method based on the transformer architecture with a multi-skip connection biLSTM decoder to estimate heart rate remotely from videos. Our method is based on the skin color variation caused by the change in blood volume in its surface. The presented heart rate estimation framework consists of three main steps: 1 the segmentation of the facial region of interest ROI based on the landmarks obtained by 3DDFA; 2 the extraction of the spatial and global features; and 3 the estimation of the heart rate value from the obtained features based on the proposed method.
This paper investigates which feature extractor performs better by captioning the change in skin color related to the heart rate as well as the optimal number of frames needed to achieve better accuracy. The experiments showed that our approach achieved better results than the previously published methods, making it the new state of the art on these datasets.
Keywords: remote heart rate estimation, vital signs, machine learning, video analysis. In recent years, there has been a noticeable surge in stress levels in our daily lives, underscoring the crucial need to proactively monitor overall human health. The assessment of vital signs, such as respiratory rate, heart rate, blood pressure, and oxygen saturation levels, has garnered increasing attention among researchers.
These vital signs serve as pivotal indicators in evaluating the holistic well-being of the human body and play crucial roles in various applications, including the detection of fatigue and stress levels [ 1 , 2 ], disease diagnosis [ 3 ], and assessments related to meditation and fitness. Various systems have been devised to measure these vital signs, encompassing devices like blood pressure monitors, oximeters, and electrocardiogram machines.
