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Article

Non-Contact Monitoring of Breathing Pattern and Respiratory Rate via RGB Signal Measurement

1
Unit of Measurements and Biomedical Instrumentation, Department of Engineering, Università Campus Bio-Medico di Roma, 00128 Rome, Italy
2
Unit of Neurophysiology and Neuroengineering of Human-Technology Interaction, Department of Engineering, Università Campus Bio-Medico di Roma, 00128 Rome, Italy
*
Author to whom correspondence should be addressed.
Sensors 2019, 19(12), 2758; https://doi.org/10.3390/s19122758
Received: 12 April 2019 / Revised: 10 June 2019 / Accepted: 18 June 2019 / Published: 19 June 2019
(This article belongs to the Special Issue Smart Sensors for Healthcare and Medical Applications)
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 breaths · min 1 , with respiratory rate values between 10 and 43 breaths · min 1 . Promising performance has been found in the preliminary tests simulating tachypnea. View Full-Text
Keywords: measuring system; measurements; contactless; respiratory rate; breathing pattern measuring system; measurements; contactless; respiratory rate; breathing pattern
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MDPI and ACS Style

Massaroni, C.; Lo Presti, D.; Formica, D.; Silvestri, S.; Schena, E. Non-Contact Monitoring of Breathing Pattern and Respiratory Rate via RGB Signal Measurement. Sensors 2019, 19, 2758. https://doi.org/10.3390/s19122758

AMA Style

Massaroni C, Lo Presti D, Formica D, Silvestri S, Schena E. Non-Contact Monitoring of Breathing Pattern and Respiratory Rate via RGB Signal Measurement. Sensors. 2019; 19(12):2758. https://doi.org/10.3390/s19122758

Chicago/Turabian Style

Massaroni, Carlo; Lo Presti, Daniela; Formica, Domenico; Silvestri, Sergio; Schena, Emiliano. 2019. "Non-Contact Monitoring of Breathing Pattern and Respiratory Rate via RGB Signal Measurement" Sensors 19, no. 12: 2758. https://doi.org/10.3390/s19122758

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