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Matsumoto T, Iwata I, Sakamoto T, Hirata S. First noncontact millimeter-wave radar measurement of heart rate in great apes: Validation in chimpanzees (Pan troglodytes). Am J Primatol 2024; 86:e23633. [PMID: 38775638 DOI: 10.1002/ajp.23633] [Citation(s) in RCA: 1] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/25/2023] [Revised: 03/24/2024] [Accepted: 04/20/2024] [Indexed: 07/18/2024]
Abstract
Heart rate is a crucial vital sign and a valuable indicator for assessing the physical and psychological condition of a target animal. Heart rate contributes to (1) fundamental information for cognitive research, (2) an indicator of psychological and physical stress, and (3) improving the animal welfare of captive animals, especially in nonhuman primate studies. Heart rate has been measured using a contact-type device; however, the device burdens the target animals and that there are risks associated with anesthesia during installation. This study explores the application of heartbeat measurement techniques using millimeter-wave radar, primarily developed for humans, as a remote and noninvasive method for measuring the heart rate of nonhuman primates. Through a measurement test conducted on two chimpanzees, we observed a remarkable correspondence between the peak frequency spectrum of heart rate estimated using millimeter-wave radar and the mean value obtained from electrocardiograph data, thereby validating the accuracy of the method. To the best of our knowledge, this is the first demonstration of the precise measurement of great apes' heart rate using millimeter-wave radar technology. Compared to heart rate measurement using video analysis, the method using millimeter-wave radar has the advantage that it is less susceptible to weather and lighting conditions and that measurement techniques for multiple individuals have been developed for human subjects, while its disadvantage is that validation of measurement from long distances has not been completed. Another disadvantage common to both methods is that measurement becomes difficult when the movement of the target individual is large. The possibility of noncontact measurement of heart rate in wild and captive primates will undoubtedly open up a new research area while taking animal welfare into consideration.
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Affiliation(s)
- Takuya Matsumoto
- Department of Science, Shinshu University, Matsumoto, Nagano, Japan
| | - Itsuki Iwata
- Department of Electrical Engineering, Graduate School of Engineering, Kyoto University, Kyoto, Kyoto, Japan
| | - Takuya Sakamoto
- Department of Electrical Engineering, Graduate School of Engineering, Kyoto University, Kyoto, Kyoto, Japan
| | - Satoshi Hirata
- Kumamoto Sanctuary, Wildlife Research Center, Kyoto University, Uki, Kumamoto, Japan
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2
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Khanam FTZ, Perera AG, Al-Naji A, Mcintyre TD, Chahl J. Integrating RGB-thermal image sensors for non-contact automatic respiration rate monitoring. JOURNAL OF THE OPTICAL SOCIETY OF AMERICA. A, OPTICS, IMAGE SCIENCE, AND VISION 2024; 41:1140-1151. [PMID: 38856428 DOI: 10.1364/josaa.520757] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 02/01/2024] [Accepted: 04/23/2024] [Indexed: 06/11/2024]
Abstract
Respiration rate (RR) holds significance as a human health indicator. Presently, the conventional RR monitoring system requires direct physical contact, which may cause discomfort and pain. Therefore, this paper proposes a non-contact RR monitoring system integrating RGB and thermal imaging through RGB-thermal image alignment. The proposed method employs an advanced image processing algorithm for automatic region of interest (ROI) selection. The experimental results demonstrated a close correlation and a lower error rate between measured thermal, measured RGB, and reference data. In summary, the proposed non-contact system emerges as a promising alternative to conventional contact-based approaches without the associated discomfort and pain.
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Allado E, Poussel M, Renno J, Moussu A, Hily O, Temperelli M, Albuisson E, Chenuel B. Remote Photoplethysmography Is an Accurate Method to Remotely Measure Respiratory Rate: A Hospital-Based Trial. J Clin Med 2022; 11:3647. [PMID: 35806932 PMCID: PMC9267568 DOI: 10.3390/jcm11133647] [Citation(s) in RCA: 5] [Impact Index Per Article: 1.7] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/09/2022] [Revised: 06/14/2022] [Accepted: 06/21/2022] [Indexed: 02/04/2023] Open
Abstract
Remote photoplethysmography imaging (rPPG) is a new solution proposed to measure vital signs, such as respiratory rate (RR) in teleconsultation, by using a webcam. The results, presented here, aim at evaluating the accuracy of such remote measurement methods, compared with existing measurement methods, in a real-life clinical setting. For each patient, measurement of RR, using the standard system (control), has been carried out concomitantly with the experimental system. A 60-s time frame was used for the measurements made by our rPPG system. Age, gender, BMI, and skin phototype were collected. We performed the intraclass correlation coefficient and Bland-Altman plot to analyze the accuracy and precision of the rPPG algorithm readings. Measurements of RR, using the two methods, have been realized on 963 patients. Comparison of the two techniques showed excellent agreement (96.0%), with most of the patients (n = 924-standard patients) being in the confidence interval of 95% in Bland-Altman plotting. There were no significant differences between standard patients and outlier patients for demographic and clinical characteristics. This study indicates a good agreement between the rPPG system and the control, thus allowing clinical use of this remote assessment of the respiratory rate.
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Affiliation(s)
- Edem Allado
- CHRU-Nancy, Exploration Fonctionnelle Respiratoire—Centre Universitaire de Médecine du Sport et Activités Physiques Adaptées, F-54000 Nancy, France; (M.P.); (A.M.); (O.H.); (M.T.); (B.C.)
- DevAH, Université de Lorraine, F-54000 Nancy, France
- OMEOS, F-54000 Nancy, France;
| | - Mathias Poussel
- CHRU-Nancy, Exploration Fonctionnelle Respiratoire—Centre Universitaire de Médecine du Sport et Activités Physiques Adaptées, F-54000 Nancy, France; (M.P.); (A.M.); (O.H.); (M.T.); (B.C.)
- DevAH, Université de Lorraine, F-54000 Nancy, France
| | | | - Anthony Moussu
- CHRU-Nancy, Exploration Fonctionnelle Respiratoire—Centre Universitaire de Médecine du Sport et Activités Physiques Adaptées, F-54000 Nancy, France; (M.P.); (A.M.); (O.H.); (M.T.); (B.C.)
- OMEOS, F-54000 Nancy, France;
| | - Oriane Hily
- CHRU-Nancy, Exploration Fonctionnelle Respiratoire—Centre Universitaire de Médecine du Sport et Activités Physiques Adaptées, F-54000 Nancy, France; (M.P.); (A.M.); (O.H.); (M.T.); (B.C.)
| | - Margaux Temperelli
- CHRU-Nancy, Exploration Fonctionnelle Respiratoire—Centre Universitaire de Médecine du Sport et Activités Physiques Adaptées, F-54000 Nancy, France; (M.P.); (A.M.); (O.H.); (M.T.); (B.C.)
| | - Eliane Albuisson
- CHRU-Nancy, Direction de la Recherche Clinique et de l’Innovation, F-54000 Nancy, France;
- CNRS, IECL, Université de Lorraine, F-54000 Nancy, France
- Département du Grand Est de Recherche en Soins Primaires (DEGERESP), Université de Lorraine, F-54000 Nancy, France
| | - Bruno Chenuel
- CHRU-Nancy, Exploration Fonctionnelle Respiratoire—Centre Universitaire de Médecine du Sport et Activités Physiques Adaptées, F-54000 Nancy, France; (M.P.); (A.M.); (O.H.); (M.T.); (B.C.)
- DevAH, Université de Lorraine, F-54000 Nancy, France
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4
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Elvekjaer M, Carlsson CJ, Rasmussen SM, Porsbjerg CM, Grønbæk KK, Haahr-Raunkjær C, Sørensen HBD, Aasvang EK, Meyhoff CS. Agreement between wireless and standard measurements of vital signs in acute exacerbation of chronic obstructive pulmonary disease: a clinical validation study. Physiol Meas 2021; 42. [PMID: 33984846 DOI: 10.1088/1361-6579/ac010c] [Citation(s) in RCA: 11] [Impact Index Per Article: 2.8] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/28/2021] [Accepted: 05/13/2021] [Indexed: 11/11/2022]
Abstract
Objective.Wireless sensors for continuous monitoring of vital signs have potential to improve patient care by earlier detection of deterioration in general ward patients. We aimed to assess agreement between wireless and standard (wired) monitoring devices in patients hospitalized with acute exacerbation of chronic obstructive pulmonary disease (AECOPD).Approach.Paired measurements of vital signs were recorded with 15 min intervals for two hours. The primary outcome was agreement between wireless and standard monitor measurements using the Bland and Altman method to calculate bias with 95% limits of agreement (LoA). We considered LoA of less than ±5 beats min-1(bpm) acceptable for heart rate (HR), whereas agreement of peripheral oxygen saturation (SpO2), respiratory rate (RR), and blood pressure (BP) were acceptable if within ±3%-points, ±3 breaths min-1(brpm), and ±10 mmHg, respectively.Main results.180 sample-pairs of vital signs from 20 with AECOPD patients were recorded for comparison. The wireless versus standard monitor bias was 0.03 (LoA -3.2 to 3.3) bpm for HR measurements, 1.4% (LoA -0.7% to 3.6%) for SpO2, -7.8 (LoA -22.3 to 6.8) mmHg for systolic BP and -6.2 (LoA -16.8 to 4.5) mmHg for diastolic BP. The wireless versus standard monitor bias for RR measurements was 0.75 (LoA -6.1 to 7.6) brpm.Significance.Commercially available wireless monitors could accurately measure HR in patients admitted with AECOPD compared to standard wired monitoring. Agreement for SpO2were borderline acceptable while agreement for RR and BP should be interpreted with caution.
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Affiliation(s)
- Mikkel Elvekjaer
- Department of Anaesthesia and Intensive Care, Bispebjerg and Frederiksberg Hospital, University of Copenhagen, Copenhagen, Denmark.,Copenhagen Center for Translational Research, Copenhagen University Hospital, Bispebjerg and Frederiksberg, Denmark.,Department of Anaesthesiology, Centre for Cancer and Organ Diseases, Rigshospitalet, University of Copenhagen, Denmark
| | - Christian Jakob Carlsson
- Department of Anaesthesia and Intensive Care, Bispebjerg and Frederiksberg Hospital, University of Copenhagen, Copenhagen, Denmark.,Copenhagen Center for Translational Research, Copenhagen University Hospital, Bispebjerg and Frederiksberg, Denmark.,Department of Anaesthesiology, Centre for Cancer and Organ Diseases, Rigshospitalet, University of Copenhagen, Denmark
| | - Søren Møller Rasmussen
- Biomedical Engineering, Department of Health Technology, Technical University of Denmark, Kgs. Lyngby, Denmark
| | - Celeste M Porsbjerg
- Copenhagen Center for Translational Research, Copenhagen University Hospital, Bispebjerg and Frederiksberg, Denmark.,Respiratory Research Unit, Bispebjerg and Frederiksberg Hospital, University of Copenhagen, Denmark.,Department of Clinical Medicine, University of Copenhagen, Denmark
| | - Katja Kjær Grønbæk
- Department of Anaesthesia and Intensive Care, Bispebjerg and Frederiksberg Hospital, University of Copenhagen, Copenhagen, Denmark.,Copenhagen Center for Translational Research, Copenhagen University Hospital, Bispebjerg and Frederiksberg, Denmark.,Department of Anaesthesiology, Centre for Cancer and Organ Diseases, Rigshospitalet, University of Copenhagen, Denmark
| | - Camilla Haahr-Raunkjær
- Department of Anaesthesia and Intensive Care, Bispebjerg and Frederiksberg Hospital, University of Copenhagen, Copenhagen, Denmark.,Copenhagen Center for Translational Research, Copenhagen University Hospital, Bispebjerg and Frederiksberg, Denmark.,Department of Anaesthesiology, Centre for Cancer and Organ Diseases, Rigshospitalet, University of Copenhagen, Denmark
| | - Helge B D Sørensen
- Biomedical Engineering, Department of Health Technology, Technical University of Denmark, Kgs. Lyngby, Denmark
| | - Eske K Aasvang
- Department of Anaesthesiology, Centre for Cancer and Organ Diseases, Rigshospitalet, University of Copenhagen, Denmark.,Department of Clinical Medicine, University of Copenhagen, Denmark
| | - Christian S Meyhoff
- Department of Anaesthesia and Intensive Care, Bispebjerg and Frederiksberg Hospital, University of Copenhagen, Copenhagen, Denmark.,Copenhagen Center for Translational Research, Copenhagen University Hospital, Bispebjerg and Frederiksberg, Denmark.,Department of Clinical Medicine, University of Copenhagen, Denmark
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5
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Abstract
Patients with the COVID-19 condition require frequent and accurate blood oxygen saturation (SpO2) monitoring. The existing pulse oximeters, however, require contact-based measurement using clips or otherwise fixed sensor units or need dedicated hardware which may cause inconvenience and involve additional appointments with the patient. This study proposes a computer vision-based system using a digital camera to measure SpO2 on the basis of the imaging photoplethysmography (iPPG) signal extracted from the human’s forehead without the need for restricting the subject or physical contact. The proposed camera-based system decomposes the iPPG obtained from the red and green channels into different signals with different frequencies using a signal decomposition technique based on a complete Ensemble Empirical Mode Decomposition (EEMD) technique and Independent Component Analysis (ICA) technique to obtain the optical properties from these wavelengths and frequency channels. The proposed system is convenient, contactless, safe and cost-effective. The preliminary results for 70 videos obtained from 14 subjects of different ages and with different skin tones showed that the red and green wavelengths could be used to estimate SpO2 with good agreement and low error ratio compared to the gold standard of pulse oximetry (SA210) with a fixed measurement position.
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Khanam FTZ, Chahl LA, Chahl JS, Al-Naji A, Perera AG, Wang D, Lee Y, Ogunwa TT, Teague S, Nguyen TXB, McIntyre TD, Pegoli SP, Tao Y, McGuire JL, Huynh J, Chahl J. Noncontact Sensing of Contagion. J Imaging 2021; 7:28. [PMID: 34460627 PMCID: PMC8321279 DOI: 10.3390/jimaging7020028] [Citation(s) in RCA: 5] [Impact Index Per Article: 1.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/28/2020] [Revised: 02/02/2021] [Accepted: 02/02/2021] [Indexed: 12/28/2022] Open
Abstract
The World Health Organization (WHO) has declared COVID-19 a pandemic. We review and reduce the clinical literature on diagnosis of COVID-19 through symptoms that might be remotely detected as of early May 2020. Vital signs associated with respiratory distress and fever, coughing, and visible infections have been reported. Fever screening by temperature monitoring is currently popular. However, improved noncontact detection is sought. Vital signs including heart rate and respiratory rate are affected by the condition. Cough, fatigue, and visible infections are also reported as common symptoms. There are non-contact methods for measuring vital signs remotely that have been shown to have acceptable accuracy, reliability, and practicality in some settings. Each has its pros and cons and may perform well in some challenges but be inadequate in others. Our review shows that visible spectrum and thermal spectrum cameras offer the best options for truly noncontact sensing of those studied to date, thermal cameras due to their potential to measure all likely symptoms on a single camera, especially temperature, and video cameras due to their availability, cost, adaptability, and compatibility. Substantial supply chain disruptions during the pandemic and the widespread nature of the problem means that cost-effectiveness and availability are important considerations.
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Affiliation(s)
- Fatema-Tuz-Zohra Khanam
- School of Engineering, University of South Australia, Mawson Lakes Campus, Adelaide, SA 5095, Australia; (A.A.-N.); (A.G.P.); (D.W.); (Y.H.L.); (T.T.O.); (S.T.); (T.X.B.N.); (T.D.M.); (S.P.P.); (Y.T.); (J.L.M.); (J.H.); (J.C.)
| | - Loris A. Chahl
- School of Biomedical Sciences and Pharmacy, University of Newcastle, Newcastle, NSW 2308, Australia;
| | - Jaswant S. Chahl
- The Chahl Medical Practice, P.O. Box 2300, Dangar, NSW 2309, Australia;
| | - Ali Al-Naji
- School of Engineering, University of South Australia, Mawson Lakes Campus, Adelaide, SA 5095, Australia; (A.A.-N.); (A.G.P.); (D.W.); (Y.H.L.); (T.T.O.); (S.T.); (T.X.B.N.); (T.D.M.); (S.P.P.); (Y.T.); (J.L.M.); (J.H.); (J.C.)
- Electrical Engineering Technical College, Middle Technical University, Al Doura, Baghdad 10022, Iraq
| | - Asanka G. Perera
- School of Engineering, University of South Australia, Mawson Lakes Campus, Adelaide, SA 5095, Australia; (A.A.-N.); (A.G.P.); (D.W.); (Y.H.L.); (T.T.O.); (S.T.); (T.X.B.N.); (T.D.M.); (S.P.P.); (Y.T.); (J.L.M.); (J.H.); (J.C.)
| | - Danyi Wang
- School of Engineering, University of South Australia, Mawson Lakes Campus, Adelaide, SA 5095, Australia; (A.A.-N.); (A.G.P.); (D.W.); (Y.H.L.); (T.T.O.); (S.T.); (T.X.B.N.); (T.D.M.); (S.P.P.); (Y.T.); (J.L.M.); (J.H.); (J.C.)
| | - Y.H. Lee
- School of Engineering, University of South Australia, Mawson Lakes Campus, Adelaide, SA 5095, Australia; (A.A.-N.); (A.G.P.); (D.W.); (Y.H.L.); (T.T.O.); (S.T.); (T.X.B.N.); (T.D.M.); (S.P.P.); (Y.T.); (J.L.M.); (J.H.); (J.C.)
| | - Titilayo T. Ogunwa
- School of Engineering, University of South Australia, Mawson Lakes Campus, Adelaide, SA 5095, Australia; (A.A.-N.); (A.G.P.); (D.W.); (Y.H.L.); (T.T.O.); (S.T.); (T.X.B.N.); (T.D.M.); (S.P.P.); (Y.T.); (J.L.M.); (J.H.); (J.C.)
| | - Samuel Teague
- School of Engineering, University of South Australia, Mawson Lakes Campus, Adelaide, SA 5095, Australia; (A.A.-N.); (A.G.P.); (D.W.); (Y.H.L.); (T.T.O.); (S.T.); (T.X.B.N.); (T.D.M.); (S.P.P.); (Y.T.); (J.L.M.); (J.H.); (J.C.)
| | - Tran Xuan Bach Nguyen
- School of Engineering, University of South Australia, Mawson Lakes Campus, Adelaide, SA 5095, Australia; (A.A.-N.); (A.G.P.); (D.W.); (Y.H.L.); (T.T.O.); (S.T.); (T.X.B.N.); (T.D.M.); (S.P.P.); (Y.T.); (J.L.M.); (J.H.); (J.C.)
| | - Timothy D. McIntyre
- School of Engineering, University of South Australia, Mawson Lakes Campus, Adelaide, SA 5095, Australia; (A.A.-N.); (A.G.P.); (D.W.); (Y.H.L.); (T.T.O.); (S.T.); (T.X.B.N.); (T.D.M.); (S.P.P.); (Y.T.); (J.L.M.); (J.H.); (J.C.)
| | - Simon P. Pegoli
- School of Engineering, University of South Australia, Mawson Lakes Campus, Adelaide, SA 5095, Australia; (A.A.-N.); (A.G.P.); (D.W.); (Y.H.L.); (T.T.O.); (S.T.); (T.X.B.N.); (T.D.M.); (S.P.P.); (Y.T.); (J.L.M.); (J.H.); (J.C.)
| | - Yiting Tao
- School of Engineering, University of South Australia, Mawson Lakes Campus, Adelaide, SA 5095, Australia; (A.A.-N.); (A.G.P.); (D.W.); (Y.H.L.); (T.T.O.); (S.T.); (T.X.B.N.); (T.D.M.); (S.P.P.); (Y.T.); (J.L.M.); (J.H.); (J.C.)
| | - John L. McGuire
- School of Engineering, University of South Australia, Mawson Lakes Campus, Adelaide, SA 5095, Australia; (A.A.-N.); (A.G.P.); (D.W.); (Y.H.L.); (T.T.O.); (S.T.); (T.X.B.N.); (T.D.M.); (S.P.P.); (Y.T.); (J.L.M.); (J.H.); (J.C.)
| | - Jasmine Huynh
- School of Engineering, University of South Australia, Mawson Lakes Campus, Adelaide, SA 5095, Australia; (A.A.-N.); (A.G.P.); (D.W.); (Y.H.L.); (T.T.O.); (S.T.); (T.X.B.N.); (T.D.M.); (S.P.P.); (Y.T.); (J.L.M.); (J.H.); (J.C.)
| | - Javaan Chahl
- School of Engineering, University of South Australia, Mawson Lakes Campus, Adelaide, SA 5095, Australia; (A.A.-N.); (A.G.P.); (D.W.); (Y.H.L.); (T.T.O.); (S.T.); (T.X.B.N.); (T.D.M.); (S.P.P.); (Y.T.); (J.L.M.); (J.H.); (J.C.)
- Joint and Operations Analysis Division, Defence Science and Technology Group, Melbourne, VIC 3207, Australia
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A Pilot Study for Estimating the Cardiopulmonary Signals of Diverse Exotic Animals Using a Digital Camera. SENSORS 2019; 19:s19245445. [PMID: 31835550 PMCID: PMC6960731 DOI: 10.3390/s19245445] [Citation(s) in RCA: 8] [Impact Index Per Article: 1.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Received: 11/12/2019] [Revised: 12/01/2019] [Accepted: 12/09/2019] [Indexed: 11/17/2022]
Abstract
Monitoring the cardiopulmonary signal of animals is a challenge for veterinarians in conditions when contact with a conscious animal is inconvenient, difficult, damaging, distressing or dangerous to personnel or the animal subject. In this pilot study, we demonstrate a computer vision-based system and use examples of exotic, untamed species to demonstrate this means to extract the cardiopulmonary signal. Subject animals included the following species: Giant panda (Ailuropoda melanoleuca), African lions (Panthera leo), Sumatran tiger (Panthera tigris sumatrae), koala (Phascolarctos cinereus), red kangaroo (Macropus rufus), alpaca (Vicugna pacos), little blue penguin (Eudyptula minor), Sumatran orangutan (Pongo abelii) and Hamadryas baboon (Papio hamadryas). The study was done without need for restriction, fixation, contact or disruption of the daily routine of the subjects. The pilot system extracts the signal from the abdominal-thoracic region, where cardiopulmonary activity is most likely to be visible using image sequences captured by a digital camera. The results show motion on the body surface of the subjects that is characteristic of cardiopulmonary activity and is likely to be useful to estimate physiological parameters (pulse rate and breathing rate) of animals without any physical contact. The results of the study suggest that a fully controlled study against conventional physiological monitoring equipment is ethically warranted, which may lead to a novel approach to non-contact physiological monitoring and remotely sensed health assessment of animals. The method shows promise for applications in veterinary practice, conservation and game management, animal welfare and zoological and behavioral studies.
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Non-contact heart and respiratory rate monitoring of preterm infants based on a computer vision system: a method comparison study. Pediatr Res 2019; 86:738-741. [PMID: 31351437 DOI: 10.1038/s41390-019-0506-5] [Citation(s) in RCA: 21] [Impact Index Per Article: 3.5] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 03/13/2019] [Revised: 07/04/2019] [Accepted: 07/11/2019] [Indexed: 11/08/2022]
Abstract
BACKGROUND Non-contact heart rate (HR) and respiratory rate (RR) monitoring is necessary for preterm infants due to the potential for the adhesive electrodes of conventional electrocardiogram (ECG) to cause damage to the epidermis. This study was performed to evaluate the agreement between HR and RR measurements of preterm infants using a non-contact computer vision system with comparison to measurements obtained by the ECG. METHODS A single-centre, cross-sectional observational study was conducted in a Neonatal Unit. Ten infants and their ECG monitors were videoed using two Nikon cameras for 10 min. HR and RR measurements obtained from the non-contact system were extracted using advanced signal processing techniques and later compared to the ECG readings using Bland-Altman analysis. RESULTS The non-contact system was able to detect an apnoea when the ECG determined movement as respirations. Although the mean bias between both methods was relatively low, the limits of agreement for HR were -8.3 to 17.4 beats per minute (b.p.m.) and for RR, -22 to 23.6 respirations per minute (r.p.m.). CONCLUSIONS This study provides necessary data for improving algorithms to address confounding variables common to the neonatal population. Further studies investigating the robustness of the proposed system for premature infants are therefore required.
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Remote Monitoring of Vital Signs in Diverse Non-Clinical and Clinical Scenarios Using Computer Vision Systems: A Review. APPLIED SCIENCES-BASEL 2019. [DOI: 10.3390/app9204474] [Citation(s) in RCA: 28] [Impact Index Per Article: 4.7] [Reference Citation Analysis] [Abstract] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 11/16/2022]
Abstract
Techniques for noncontact measurement of vital signs using camera imaging technologies have been attracting increasing attention. For noncontact physiological assessments, computer vision-based methods appear to be an advantageous approach that could be robust, hygienic, reliable, safe, cost effective and suitable for long distance and long-term monitoring. In addition, video techniques allow measurements from multiple individuals opportunistically and simultaneously in groups. This paper aims to explore the progress of the technology from controlled clinical scenarios with fixed monitoring installations and controlled lighting, towards uncontrolled environments, crowds and moving sensor platforms. We focus on the diversity of applications and scenarios being studied in this topic. From this review it emerges that automatic multiple regions of interest (ROIs) selection, removal of noise artefacts caused by both illumination variations and motion artefacts, simultaneous multiple person monitoring, long distance detection, multi-camera fusion and accepted publicly available datasets are topics that still require research to enable the technology to mature into many real-world applications.
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10
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Abstract
In the aftermath of a disaster, such as earthquake, flood, or avalanche, ground search for survivors is usually hampered by unstable surfaces and difficult terrain. Drones now play an important role in these situations, allowing rescuers to locate survivors and allocate resources to saving those who can be helped. The aim of this study was to explore the utility of a drone equipped for human life detection with a novel computer vision system. The proposed system uses image sequences captured by a drone camera to remotely detect the cardiopulmonary motion caused by periodic chest movement of survivors. The results of eight human subjects and one mannequin in different poses shows that motion detection on the body surface of the survivors is likely to be useful to detect life signs without any physical contact. The results presented in this study may lead to a new approach to life detection and remote life sensing assessment of survivors.
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