Why the study?
The study was designed to develop contactless technology for monitoring blood pressure and vital signs using machine learning to eliminate the need for cuff-based measurements.
Does a contactless facial recognition framework accurately estimate body vital signs compared to cuff-based measurement in patients with blood pressure disorders?
Does a contactless facial recognition framework accurately estimate body vital signs compared to cuff-based measurement in patients with blood pressure disorders?
A novel framework using facial recognition and machine learning is proposed for contactless monitoring of vital signs, potentially replacing cuff-based blood pressure measurements.
As one of the consequences of COVID-19 pandemic, a lot of new technologies are developing in fast-track pace in clinical practices. The main idea of our project is to design contactless technology for the support of patients who suffer from blood pressure disorders and coronary heart diseases using machine learning approach. This may intend people to monitor their heart rate, pulse rate, respiratory life and oxygen saturation levels at an ease. The orientation of this paper is to monitor the blood pressure considering the facial changes and movements in a video to get rid of cuff-based measurement of blood pressure. We analyzed whether blood pressure can be obtained in a contactless way utilizing a novel technologies like image processing and machine learning techniques. This innovation estimates vague facial blood stream changes from video recordings captured by camera with the help of machine learning and image processing techniques.
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Sridhar et al. (2021) studied this question.
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