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Information 2019, 10(1), 9; https://doi.org/10.3390/info10010009

Contact-Less Real-Time Monitoring of Cardiovascular Risk Using Video Imaging and Fuzzy Inference Rules

1
Department of Computer Science, University of Bari Aldo Moro, Via Orabona, 4-70125 Bari, Italy
2
INDAM Research Group GNCS, 00185 Roma, Italy
*
Author to whom correspondence should be addressed.
Received: 30 October 2018 / Revised: 12 December 2018 / Accepted: 24 December 2018 / Published: 29 December 2018
(This article belongs to the Special Issue eHealth and Artificial Intelligence)
Full-Text   |   PDF [2592 KB, uploaded 29 December 2018]   |  

Abstract

Conventional methods for measuring cardiovascular parameters use skin contact techniques requiring a measuring device to be worn by the user. To avoid discomfort of contact devices, camera-based techniques using photoplethysmography have been recently introduced. Nevertheless, these solutions are typically expensive and difficult to be used daily at home. In this work, we propose an innovative solution for monitoring cardiovascular parameters that is low cost and can be easily integrated within any common home environment. The proposed system is a contact-less device composed of a see-through mirror equipped with a camera that detects the person’s face and processes video frames using photoplethysmography in order to estimate the heart rate, the breath rate and the blood oxygen saturation. In addition, the color of lips is automatically detected via clustering-based color quantization. The estimated parameters are used to predict a risk of cardiovascular disease by means of fuzzy inference rules integrated in the mirror-based monitoring system. Comparing our system to a contact device in measuring vital parameters on still or slightly moving subjects, we achieve measurement errors that are within acceptable margins according to the literature. Moreover, in most cases, the response of the fuzzy rule-based system is comparable with that of the clinician in assessing a risk level of cardiovascular disease. View Full-Text
Keywords: contact-less monitoring; photoplethysmography; signal processing; video imaging; personal health care; fuzzy inference system; diagnosis; cardiovascular disease contact-less monitoring; photoplethysmography; signal processing; video imaging; personal health care; fuzzy inference system; diagnosis; cardiovascular disease
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This is an open access article distributed under the Creative Commons Attribution License which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited (CC BY 4.0).
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Casalino, G.; Castellano, G.; Pasquadibisceglie, V.; Zaza, G. Contact-Less Real-Time Monitoring of Cardiovascular Risk Using Video Imaging and Fuzzy Inference Rules. Information 2019, 10, 9.

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