{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,6,24]],"date-time":"2026-06-24T18:57:03Z","timestamp":1782327423807,"version":"3.54.5"},"reference-count":37,"publisher":"MDPI AG","issue":"12","license":[{"start":{"date-parts":[[2019,6,19]],"date-time":"2019-06-19T00:00:00Z","timestamp":1560902400000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0\/"}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["Sensors"],"abstract":"<jats:p>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\u2019s 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\u2013Altman 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\u2013Altman analysis showed a bias of \u22120.01 breaths     \u00b7     min      \u2212 1     , with respiratory rate values between 10 and 43 breaths     \u00b7     min      \u2212 1     . Promising performance has been found in the preliminary tests simulating tachypnea.<\/jats:p>","DOI":"10.3390\/s19122758","type":"journal-article","created":{"date-parts":[[2019,6,19]],"date-time":"2019-06-19T10:43:32Z","timestamp":1560941012000},"page":"2758","update-policy":"https:\/\/doi.org\/10.3390\/mdpi_crossmark_policy","source":"Crossref","is-referenced-by-count":100,"title":["Non-Contact Monitoring of Breathing Pattern and Respiratory Rate via RGB Signal Measurement"],"prefix":"10.3390","volume":"19","author":[{"ORCID":"https:\/\/orcid.org\/0000-0002-3090-5623","authenticated-orcid":false,"given":"Carlo","family":"Massaroni","sequence":"first","affiliation":[{"name":"Unit of Measurements and Biomedical Instrumentation, Department of Engineering, Universit\u00e0 Campus Bio-Medico di Roma, 00128 Rome, Italy"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-1507-231X","authenticated-orcid":false,"given":"Daniela","family":"Lo Presti","sequence":"additional","affiliation":[{"name":"Unit of Measurements and Biomedical Instrumentation, Department of Engineering, Universit\u00e0 Campus Bio-Medico di Roma, 00128 Rome, Italy"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0003-0240-1265","authenticated-orcid":false,"given":"Domenico","family":"Formica","sequence":"additional","affiliation":[{"name":"Unit of Neurophysiology and Neuroengineering of Human-Technology Interaction, Department of Engineering, Universit\u00e0 Campus Bio-Medico di Roma, 00128 Rome, Italy"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-5863-8336","authenticated-orcid":false,"given":"Sergio","family":"Silvestri","sequence":"additional","affiliation":[{"name":"Unit of Measurements and Biomedical Instrumentation, Department of Engineering, Universit\u00e0 Campus Bio-Medico di Roma, 00128 Rome, Italy"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-9696-1265","authenticated-orcid":false,"given":"Emiliano","family":"Schena","sequence":"additional","affiliation":[{"name":"Unit of Measurements and Biomedical Instrumentation, Department of Engineering, Universit\u00e0 Campus Bio-Medico di Roma, 00128 Rome, Italy"}],"role":[{"vocabulary":"crossref","role":"author"}]}],"member":"1968","published-online":{"date-parts":[[2019,6,19]]},"reference":[{"key":"ref_1","doi-asserted-by":"crossref","first-page":"657","DOI":"10.5694\/j.1326-5377.2008.tb01825.x","article-title":"Respiratory rate: The neglected vital sign","volume":"188","author":"Cretikos","year":"2008","journal-title":"Med. J. Aust."},{"key":"ref_2","doi-asserted-by":"crossref","unstructured":"Nicol\u00f2, A., Massaroni, C., and Passfield, L. (2017). Respiratory frequency during exercise: The neglected physiological measure. Front. Physiol.","DOI":"10.3389\/fphys.2017.00922"},{"key":"ref_3","doi-asserted-by":"crossref","first-page":"18","DOI":"10.12968\/bjha.2011.5.1.18","article-title":"Respiratory rate measurement: A comparison of methods","volume":"5","author":"Smith","year":"2011","journal-title":"Br. J. Healthc. Assist."},{"key":"ref_4","doi-asserted-by":"crossref","first-page":"1644","DOI":"10.1093\/eurheartj\/ehs420","article-title":"Respiratory rate predicts outcome after acute myocardial infarction: A prospective cohort study","volume":"34","author":"Barthel","year":"2012","journal-title":"Eur. Heart J."},{"key":"ref_5","doi-asserted-by":"crossref","first-page":"1389","DOI":"10.1152\/japplphysiol.90408.2008","article-title":"Role of respiratory control mechanisms in the pathogenesis of obstructive sleep disorders","volume":"105","author":"Younes","year":"2008","journal-title":"J. Appl. Physiol."},{"key":"ref_6","doi-asserted-by":"crossref","first-page":"53","DOI":"10.1016\/S0378-3782(98)00039-5","article-title":"Increased amplitude modulation of continuous respiration precedes sudden infant death syndrome: Detection by spectral estimation of respirogram","volume":"53","author":"Rantonen","year":"1998","journal-title":"Early Hum. Dev."},{"key":"ref_7","doi-asserted-by":"crossref","first-page":"257","DOI":"10.1016\/j.medengphy.2015.01.010","article-title":"Flow measurement in mechanical ventilation: A review","volume":"37","author":"Schena","year":"2015","journal-title":"Med. Eng. Phys."},{"key":"ref_8","doi-asserted-by":"crossref","first-page":"219","DOI":"10.1186\/cc11146","article-title":"Clinical review: Respiratory monitoring in the ICU-a consensus of 16","volume":"16","author":"Brochard","year":"2012","journal-title":"Crit. Care"},{"key":"ref_9","doi-asserted-by":"crossref","unstructured":"Massaroni, C., Nicol\u00f2, A., Lo Presti, D., Sacchetti, M., Silvestri, S., and Schena, E. (2019). Contact-based methods for measuring respiratory rate. Sensors, 19.","DOI":"10.3390\/s19040908"},{"key":"ref_10","doi-asserted-by":"crossref","unstructured":"Massaroni, C., Di Tocco, J., Presti, D.L., Longo, U.G., Miccinilli, S., Sterzi, S., Formica, D., Saccomandi, P., and Schena, E. (2019). Smart textile based on piezoresistive sensing elements for respiratory monitoring. IEEE Sens. J.","DOI":"10.1109\/JSEN.2019.2917617"},{"key":"ref_11","doi-asserted-by":"crossref","first-page":"1423","DOI":"10.1109\/TIM.2016.2519779","article-title":"Autonomous wearable system for vital signs measurement with energy-harvesting module","volume":"65","author":"Dionisi","year":"2016","journal-title":"IEEE Trans. Instrum. Meas."},{"key":"ref_12","doi-asserted-by":"crossref","first-page":"252","DOI":"10.1152\/jappl.1972.33.2.252","article-title":"Changes in tidal volume, frequency, and ventilation induced by their measurement","volume":"33","author":"Gilbert","year":"1972","journal-title":"J. Appl. Physiol."},{"key":"ref_13","doi-asserted-by":"crossref","first-page":"15776","DOI":"10.1109\/ACCESS.2017.2735419","article-title":"Monitoring of cardiorespiratory signal: Principles of remote measurements and review of methods","volume":"5","author":"Gibson","year":"2017","journal-title":"IEEE Access"},{"key":"ref_14","doi-asserted-by":"crossref","first-page":"1555","DOI":"10.1109\/TIM.2017.2779358","article-title":"Design and Implementation of a Noncontact Sleep Monitoring System Using Infrared Cameras and Motion Sensor","volume":"67","author":"Deng","year":"2018","journal-title":"IEEE Trans. Instrum. Meas."},{"key":"ref_15","doi-asserted-by":"crossref","first-page":"928","DOI":"10.1109\/TIM.2010.2064370","article-title":"Wireless Sensing of Human Respiratory Parameters by Low-Power Ultrawideband Impulse Radio Radar","volume":"60","author":"Lai","year":"2011","journal-title":"IEEE Trans. Instrum. Meas."},{"key":"ref_16","doi-asserted-by":"crossref","unstructured":"Bernacchia, N., Scalise, L., Casacanditella, L., Ercoli, I., Marchionni, P., and Tomasini, E.P. (2014, January 11\u201312). Non contact measurement of heart and respiration rates based on Kinect\u2122. Proceedings of the 2014 IEEE International Symposium on Medical Measurements and Applications (MeMeA), Lisbon, Portugal.","DOI":"10.1109\/MeMeA.2014.6860065"},{"key":"ref_17","doi-asserted-by":"crossref","first-page":"121705","DOI":"10.1063\/1.4845635","article-title":"An optical measurement method for the simultaneous assessment of respiration and heart rates in preterm infants","volume":"84","author":"Marchionni","year":"2013","journal-title":"Rev. Sci. Instrum."},{"key":"ref_18","doi-asserted-by":"crossref","unstructured":"Scalise, L., Ercoli, I., Marchionni, P., and Tomasini, E.P. (2011, January 30\u201331). Measurement of respiration rate in preterm infants by laser Doppler vibrometry. Proceedings of the 2011 IEEE International Workshop on Medical Measurements and Applications Proceedings (MeMeA), Bari, Italy.","DOI":"10.1109\/MeMeA.2011.5966740"},{"key":"ref_19","doi-asserted-by":"crossref","first-page":"847","DOI":"10.1111\/psyp.12638","article-title":"Cardiorespiratory interactions: Noncontact assessment using laser Doppler vibrometry","volume":"53","author":"Sirevaag","year":"2016","journal-title":"Psychophysiology"},{"key":"ref_20","doi-asserted-by":"crossref","unstructured":"Lin, K.Y., Chen, D.Y., and Tsai, W.J. (2016). Image-Based Motion-Tolerant Remote Respiratory Rate Evaluation. IEEE Sens. J.","DOI":"10.1109\/JSEN.2016.2526627"},{"key":"ref_21","doi-asserted-by":"crossref","first-page":"4567213","DOI":"10.1155\/2018\/4567213","article-title":"Contactless Monitoring of Breathing Patterns and Respiratory Rate at the Pit of the Neck: A Single Camera Approach","volume":"2018","author":"Massaroni","year":"2018","journal-title":"J. Sens."},{"key":"ref_22","doi-asserted-by":"crossref","unstructured":"Bartula, M., Tigges, T., and Muehlsteff, J. (2013, January 3\u20137). Camera-based system for contactless monitoring of respiration. Proceedings of the 2013 35th Annual International Conference of the IEEE Engineering in Medicine and Biology Society (EMBC), Osaka, Japan.","DOI":"10.1109\/EMBC.2013.6610090"},{"key":"ref_23","doi-asserted-by":"crossref","unstructured":"Koolen, N., Decroupet, O., Dereymaeker, A., Jansen, K., Vervisch, J., Matic, V., Vanrumste, B., Naulaers, G., Van Huffel, S., and De Vos, M. (2015, January 10\u201312). Automated Respiration Detection from Neonatal Video Data. Proceedings of the International Conference on Pattern Recognition Applications and Methods ICPRAM, Lisbon, Portugal.","DOI":"10.5220\/0005187901640169"},{"key":"ref_24","doi-asserted-by":"crossref","unstructured":"Antognoli, L., Marchionni, P., Nobile, S., Carnielli, V., and Scalise, L. (2018, January 11\u201313). Assessment of cardio-respiratory rates by non-invasive measurement methods in hospitalized preterm neonates. Proceedings of the 2018 IEEE International Symposium on Medical Measurements and Applications (MeMeA), Rome, Italy.","DOI":"10.1109\/MeMeA.2018.8438772"},{"key":"ref_25","doi-asserted-by":"crossref","unstructured":"Bernacchia, N., Marchionni, P., Ercoli, I., and Scalise, L. (2015). Non-contact measurement of the heart rate by a image sensor. Sensors, Springer.","DOI":"10.1007\/978-3-319-09617-9_65"},{"key":"ref_26","doi-asserted-by":"crossref","unstructured":"Bai, Y.W., Li, W.T., and Chen, Y.W. (2010, January 1\u20133). Design and implementation of an embedded monitor system for detection of a patient\u2019s breath by double Webcams in the dark. Proceedings of the 12th IEEE International Conference on e-Health Networking Applications and Services (Healthcom), Lyon, France.","DOI":"10.1109\/HEALTH.2010.5556526"},{"key":"ref_27","doi-asserted-by":"crossref","unstructured":"Janssen, R., Wang, W., Mo\u00e7o, A., and De Haan, G. (2015). Video-based respiration monitoring with automatic region of interest detection. Physiol. Meas.","DOI":"10.1088\/0967-3334\/37\/1\/100"},{"key":"ref_28","doi-asserted-by":"crossref","first-page":"7","DOI":"10.1109\/TBME.2010.2086456","article-title":"Advancements in noncontact, multiparameter physiological measurements using a webcam","volume":"58","author":"Poh","year":"2011","journal-title":"IEEE Trans. Biomed. Eng."},{"key":"ref_29","doi-asserted-by":"crossref","unstructured":"Massaroni, C., Schena, E., Silvestri, S., Taffoni, F., and Merone, M. (2018, January 11\u201313). Measurement system based on RBG camera signal for contactless breathing pattern and respiratory rate monitoring. Proceedings of the 2018 IEEE International Symposium on Medical Measurements and Applications (MeMeA), Rome, Italy.","DOI":"10.1109\/MeMeA.2018.8438692"},{"key":"ref_30","doi-asserted-by":"crossref","unstructured":"Massaroni, C., Nicol\u00f2, A., Girardi, M., La Camera, A., Schena, E., Sacchetti, M., Silvestri, S., and Taffoni, F. (2019). Validation of a wearable device and an algorithm for respiratory monitoring during exercise. IEEE Sens. J.","DOI":"10.1109\/JSEN.2019.2899658"},{"key":"ref_31","doi-asserted-by":"crossref","first-page":"1878354","DOI":"10.1155\/2018\/1878354","article-title":"A Wearable System for Real-Time Continuous Monitoring of Physical Activity","volume":"2018","author":"Taffoni","year":"2018","journal-title":"J. Healthc. Eng."},{"key":"ref_32","doi-asserted-by":"crossref","first-page":"70","DOI":"10.1109\/TAU.1967.1161901","article-title":"The use of fast Fourier transform for the estimation of power spectra: A method based on time averaging over short, modified periodograms","volume":"15","author":"Welch","year":"1967","journal-title":"IEEE Trans. Audio Electroacoust."},{"key":"ref_33","doi-asserted-by":"crossref","first-page":"307","DOI":"10.2307\/2987937","article-title":"Measurement in medicine: The analysis of method comparison studies","volume":"32","author":"Altman","year":"1983","journal-title":"Statistician"},{"key":"ref_34","doi-asserted-by":"crossref","first-page":"764","DOI":"10.1109\/JBHI.2016.2532876","article-title":"Tidal Volume and Instantaneous Respiration Rate Estimation using a Volumetric Surrogate Signal Acquired via a Smartphone Camera","volume":"21","author":"Reyes","year":"2017","journal-title":"IEEE J. Biomed. Health Inform."},{"key":"ref_35","doi-asserted-by":"crossref","first-page":"1","DOI":"10.1109\/JTEHM.2017.2757485","article-title":"Simultaneous tracking of cardiorespiratory signals for multiple persons using a machine vision system with noise artifact removal","volume":"5","author":"Chahl","year":"2017","journal-title":"IEEE J. Translat. Eng. Health Med."},{"key":"ref_36","doi-asserted-by":"crossref","first-page":"e201700263","DOI":"10.1002\/jbio.201700263","article-title":"Smart textile for respiratory monitoring and thoraco-abdominal motion pattern evaluation","volume":"11","author":"Massaroni","year":"2018","journal-title":"J. Biophotonics"},{"key":"ref_37","doi-asserted-by":"crossref","first-page":"057002","DOI":"10.1117\/1.JBO.22.5.057002","article-title":"Noncontact spirometry with a webcam","volume":"22","author":"Liu","year":"2017","journal-title":"J. Biomed. 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