Citation

Vu, Van Huan and Do, Duc Thinh and Nguyen, Duc Manh and Nguyen, Thi Bich Ngoc (2026) Intelligent Telemedicine Systems for Contactless Heart Rate Estimation using Deep Learning-based rPPG. Journal of Informatics and Web Engineering, 5 (2). p. 405. ISSN 2821-370X

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Abstract

Over the last ten years, telemedicine has undergone significant developments, from simple communication-based healthcare to smart and data-driven solutions. The solutions are now powered by Artificial Intelligence (AI), Machine Learning (ML), and Internet of Medical Things (IoMT) technologies. Physiological monitoring is traditionally done with contact-based sensors. The sensors include Electrocardiogram (ECG) and pulse oximeters. The sensors have various disadvantages, including hardware costs, difficulty in continuous usage, and discomfort for patients. Photoplethysmography (rPPG), a remote method of physiological monitoring, is a breakthrough technology. The method is used to estimate physiological signals, including Heart Rate (HR), from video streams captured by standard RGB cameras. The paper aims to explore spatial-temporal deep learning frameworks for remote rPPG as part of a standard five-layer telemedicine architecture. We explain a general ML pipeline, along with the benefits of decomposing the spatial and temporal features of images and motion to improve signal extraction against environmental noise. Besides, the paper presents some of the deployment issues, which include motion effects, lighting, as well as bias in the algorithms, specifically with respect to melanin absorption in human skin. The research also presents some of the avenues of future research, specifically with respect to model compression, which will help move from a cloud to an edge device, thus helping to improve the privacy of users.

Item Type:	Article
Uncontrolled Keywords:	Telemedicine, Remote Photoplethysmography, Electrocardiogram, Heart Rate Estimation, Two-Stream Convolutional Network, Edge AI, Digital Health
Subjects:	R Medicine > R Medicine (General) > R858-859.7 Computer applications to medicine. Medical informatics
Divisions:	Others
Depositing User:	Ms Suzilawati Abu Samah
Date Deposited:	09 Jul 2026 04:01
Last Modified:	09 Jul 2026 04:01
URII:	http://shdl.mmu.edu.my/id/eprint/16348

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