Abstract

Among all the vital signs, respiratory rate remains the least measured in several scenarios, mainly due to the intrusiveness of the sensors usually adopted. For this reason, all contactless monitoring systems are gaining increasing attention in this field. In this paper, we present a measuring system for contactless measurement of the respiratory pattern and the extraction of breath-by-breath respiratory rate. The system consists of a laptop’s built-in RGB camera and an algorithm for post-processing of acquired video data. From the recording of the chest movements of a subject, the analysis of the pixel intensity changes yields a waveform indicating respiratory pattern. The proposed system has been tested on 12 volunteers, both males and females seated in front of the webcam, wearing both slim-fit and loose-fit t-shirts. The pressure-drop signal recorded at the level of nostrils with a head-mounted wearable device was used as reference respiratory pattern. The two methods have been compared in terms of mean of absolute error, standard error, and percentage error. Additionally, a Bland–Altman plot was used to investigate the bias between methods. Results show the ability of the system to record accurate values of respiratory rate, with both slim-fit and loose-fit clothing. The measuring system shows better performance on females. Bland–Altman analysis showed a bias of −0.01 breathsmin, with respiratory rate values between 10 and 43 breathsmin. Promising performance has been found in the preliminary tests simulating tachypnea.

Highlights

  • Accurate measurement of vital signs and physiological parameters, such as body temperature, pulse rate, blood pressure, and respiratory rate, plays a pivotal role in the healthcare sector and management of patients

  • We present a measuring system capable of non-contact monitoring of respiratory pattern by using RGB video signal acquired from a single built-in high-definition webcam

  • mean absolute error (MAE) value was always lower than 0.78 bpm, while standard error was

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Summary

Introduction

Accurate measurement of vital signs and physiological parameters, such as body temperature, pulse rate, blood pressure, and respiratory rate, plays a pivotal role in the healthcare sector and management of patients. The respiratory rate is an early indicator of physiological deterioration [3]. Respiratory rate is an important predictor of cardiac arrest and of unplanned intensive care unit admission [1], as well as an independent prognostic marker for risk assessment after acute myocardial infarction [4]. It is fundamental in the early detection and diagnosis of dangerous conditions such as sleep apnea [5], sudden infant

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