Non-contact breathing monitoring by integrating RGB and thermal imaging via RGB-thermal image registration

被引:8
作者
Maurya, Lalit [1 ,2 ]
Mahapatra, Prasant [1 ,2 ]
Chawla, Deepak [3 ]
机构
[1] Acad Sci & Innovat Res AcSIR, Ghaziabad, India
[2] CSIR Cent Sci Instruments Org CSIR CSIO, Sect 30-C, Chandigarh, India
[3] Govt Med Coll & Hosp GMCH, Dept Neonatol, Chandigarh, India
关键词
Breathing rate; Non-contact; Thermal imaging; RESPIRATORY RATE; PATTERNS; CAMERA;
D O I
10.1016/j.bbe.2021.07.002
中图分类号
R318 [生物医学工程];
学科分类号
0831 ;
摘要
Altered breathing rate is an important sign of disease status. Currently used machine-based monitoring of the breathing rate includes contact with the body, which may result in pain and discomfort. In this paper, a non-contact breathing monitoring technique is proposed by integrating RGB and thermal imaging systems with RGB-thermal image registration. This method provides a linear mapping for automated selection of the region of interest (ROI) followed by tracking to extract the breathing rate. To evaluate the efficacy of the proposed approach and its robustness against motion, talking, varying breathing rate or rhythm, and high ambient temperature, this study was conducted in three phases. Validation of the proposed approach demonstrated a strong agreement with the reference method of breathing rate monitoring using a respiration belt. During normal breathing, the mean absolute error (MAE) reached 0.11 bpm (breaths per minute). While in more challenging conditions, defined by three phases, the MAE reached 1.46, 2.08, and 1.69 bpm, respectively. In short, the proposed method performance is a promising alternative to a contact-based method due to its strong agreement and might be useful in diverse applications such as sport studies, rehabilitation centres, quarantine centres, and in hospital or airport screening during the COVID 19 pandemic. (C) 2021 Nalecz Institute of Biocybernetics and Biomedical Engineering of the Polish Academy of Sciences. Published by Elsevier B.V. All rights reserved.
引用
收藏
页码:1107 / 1122
页数:16
相关论文
共 52 条
[1]  
Abbas Abbas K., 2009, 11th International Congress of the IUPESM. World Congress on Medical Physics and Biomedical Engineering. Image Processing, Biosignal Processing, Modelling and Simulation, Biomechanics, P1306, DOI 10.1007/978-3-642-03882-2_346
[2]   Multispectral Image Feature Points [J].
Aguilera, Cristhian ;
Barrera, Fernando ;
Lumbreras, Felipe ;
Sappa, Angel D. ;
Toledo, Ricardo .
SENSORS, 2012, 12 (09) :12661-12672
[3]  
Aguilera CA, 2015, IEEE IMAGE PROC, P178, DOI 10.1109/ICIP.2015.7350783
[4]  
Al-Khalidi F., 2011, Am. J. Eng. Appl. Sci., V4, P586
[5]   Monitoring of Cardiorespiratory Signal: Principles of Remote Measurements and Review of Methods [J].
Al-Naji, Ali ;
Gibson, Kim ;
Lee, Sang-Heon ;
Chahl, Javaan .
IEEE ACCESS, 2017, 5 :15776-15790
[6]  
Baharestani MM, 2007, OSTOMY WOUND MANAG, V53, P34
[7]  
Bartula M, 2013, IEEE ENG MED BIO, P2672, DOI 10.1109/EMBC.2013.6610090
[8]   Contact-Free Respiration Rate Monitoring Using a Pan-Tilt Thermal Camera for Stationary Bike Telerehabilitation Sessions [J].
Chauvin, Ronan ;
Hamel, Mathieu ;
Briere, Simon ;
Ferland, Francois ;
Grondin, Francois ;
Letourneau, Dominic ;
Tousignant, Michel ;
Michaud, Francois .
IEEE SYSTEMS JOURNAL, 2016, 10 (03) :1046-1055
[9]   Robust tracking of respiratory rate in high-dynamic range scenes using mobile thermal imaging [J].
Cho, Youngjun ;
Julier, Simon J. ;
Marquardt, Nicola ;
Bianchi-Berthouze, Nadia .
BIOMEDICAL OPTICS EXPRESS, 2017, 8 (10) :4480-4503
[10]  
Cretikos MA, 2008, MED J AUSTRALIA, V188, P657