Clinical accuracy of infrared temperature measurement devices: a comparison against non-invasive core-body temperature.

During the coronavirus 2019 (COVID-19) pandemic, the implementation of non-contact infrared thermometry (NCIT) became an increasingly popular method of screening body temperature. However, data on the accuracy of these devices and the standardisation of their use are limited. In the current study, the body temperature of non-febrile volunteers was measured using infrared (IR) thermography, IR tympanic thermometry and IR gun thermometry at different facial feature locations and distances and compared with SpotOn core-body temperature. Poor agreement was found between all IR devices and SpotOn measurements (intra-class correlation coefficient <0.8). Bland-Alman analysis showed the narrowest limits of agreement with the IR gun at 3 cm from the forehead (bias = 0.19°C, limits of agreement (LOA): -0.58°C to 0.97°C) and widest with the IR gun at the nose (bias = 1.40°C, LOA: -1.15°C to 3.94°C). Thus, our findings challenge the established use of IR thermometry devices within hospital settings without adequate standard operating procedures to reduce operator error.

Free-living core body temperature monitoring using a wrist-worn sensor after COVID-19 booster vaccination: a pilot study.

Core body temperature (CBT) is a key vital sign and fever is an important indicator of disease. In the past decade, there has been growing interest for vital sign monitoring technology that may be embedded in wearable devices, and the COVID-19 pandemic has highlighted the need for remote patient monitoring systems. While wrist-worn sensors allow continuous assessment of heart rate and oxygen saturation, reliable measurement of CBT at the wrist remains challenging. In this study, CBT was measured continuously in a free-living setting using a novel technology worn at the wrist and compared to reference core body temperature measurements, i.e., CBT values acquired with an ingestible temperature-sensing pill. Fifty individuals who received the COVID-19 booster vaccination were included. The datasets of 33 individuals were used to develop the CBT prediction algorithm, and the algorithm was then validated on the datasets of 17 participants. Mean observation time was 26.4 h and CBT > 38.0 °C occurred in 66% of the participants. CBT predicted by the wrist-worn sensor showed good correlation to the reference CBT (r = 0.72). Bland-Altman statistics showed an average bias of 0.11 °C of CBT predicted by the wrist-worn device compared to reference CBT, and limits of agreement were - 0.67 to + 0.93 °C, which is comparable to the bias and limits of agreement of commonly used tympanic membrane thermometers. The small size of the components needed for this technology would allow its integration into a variety of wearable monitoring systems assessing other vital signs and at the same time allowing maximal freedom of movement to the user.

Joint Masked Face Recognition and Temperature Measurement System Using Convolutional Neural Networks.

With the outbreak of COVID-19, epidemic prevention has become a way to prevent the spread of epidemics. Many public places, such as hospitals, schools, and office places, require disinfection and temperature measurement. To implement epidemic prevention systems and reduce the risk of infection, it is a recent trend to measure body temperature through non-contact sensing systems with thermal imaging cameras. Compared to fingerprints and irises, face recognition is accurate and does not require close contact, which significantly reduces the risk of infection. However, masks block most facial features, resulting in the low accuracy of face recognition systems. This work combines masked face recognition with a thermal imaging camera for use as an automated attendance system. It can record body temperature and recognize the person at the same time. Through the designed UI system, we can search the attendance information of each person. We not only provide the design method based on convolutional neural networks (CNNs), but also provide the complete embedded system as a real demonstration and achieve a 94.1% accuracy rate of masked face recognition in the real world. With the face recognition system combined with a thermal imaging camera, the purpose of screening body temperature when checking in at work can be achieved.

Measurement and Processing of Thermographic Data of Passing Persons for Epidemiological Purposes.

Non-contact temperature measurement of persons during an epidemic is the most preferred measurement option because of the safety of personnel and minimal possibility of spreading infection. The use of infrared (IR) sensors to monitor building entrances for infected persons has seen a major boom between 2020 and 2022 due to the COVID-19 epidemic, but with questionable results. This article does not deal with the precise determination of the temperature of an individual person but focuses on the possibility of using infrared cameras for monitoring the health of the population. The aim is to use large amounts of infrared data from many locations to provide information to epidemiologists so they can have better information about potential outbreaks. This paper focuses on the long-term monitoring of the temperature of passing persons inside public buildings and the search for the most appropriate tools for this purpose and is intended as the first step towards creating a useful tool for epidemiologists. As a classical approach, the identification of persons based on their characteristic temperature values over time throughout the day is used. These results are compared with the results of a method using artificial intelligence (AI) to evaluate temperature from simultaneously acquired infrared images. The advantages and disadvantages of both methods are discussed.

Influence of Hospital Environmental Variables on Thermometric Measurements and Level of Concordance: A Cross-Sectional Descriptive Study.

During a pandemic, and given the need to quickly screen febrile and non-febrile humans, it is necessary to know the concordance between different thermometers (TMs) and understand how environmental factors influence the measurements made by these instruments. OBJECTIVE: The objective of this study is to identify the potential influence of environmental factors on the measurements made by four different TMs and the concordance between these instruments in a hospital setting. METHOD: The study employed a cross-sectional observational methodology. The participants were patients who had been hospitalised in the traumatology unit. The variables were body temperature, room temperature, room relative humidity, light, and noise. The instruments used were a Non Contract Infrared TM, Axillary Electronic TM, Gallium TM, and Tympanic TM. A lux meter, a sound level meter, and a thermohygrometer measured the ambient variables. RESULTS: The study sample included 288 participants. Weak significant relationships were found between noise and body temperature measured with Tympanic Infrared TM, r = -0.146 (p < 0.01) and likewise between environmental temperature and this same TM, r = 0.133 (p < 0.05). The concordance between the measurements made by the four different TMs showed an Intraclass Correlation Coefficient (ICC) of 0.479. CONCLUSIONS: The concordance between the four TMs was considered "fair".

Possible spread of SARS-CoV-2 in domestic and wild animals and body temperature role.

The COVID-19 pandemic was officially announced in March 2020 and is still moving around the world. Virus strains, their pathogenicity and infectivity are changing, but the ability is fast to spread and harm people's health remained, despite the seasonality seasons and other circumstances. Most likely, humanity is doomed for a long time to coexistence with this emergent pathogen, since it is already circulating not only among the human population, but and among fauna, especially among wild animals in different regions of the planet. Thus, the range the virus has expanded, the material and conditions for its evolution are more than enough. The detection of SARS-CoV-2 in known infected fauna species is analyzed and possible spread and ongoing circulation of the virus in domestic and wild animals are discussed. One of the main focus of the article is the role of animal body temperature, its fluctuations and the presence of entry receptors in the susceptibility of different animal species to SARS-CoV-2 infection and virus spreading in possible new ecological niches. The possibility of long-term circulation of the pathogen among susceptible organisms is discussed.

Role of Wearable Sensing Technology to Manage Long COVID.

Long COVID consequences have changed the perception towards disease management, and it is moving towards personal healthcare monitoring. In this regard, wearable devices have revolutionized the personal healthcare sector to track and monitor physiological parameters of the human body continuously. This would be largely beneficial for early detection (asymptomatic and pre-symptomatic cases of COVID-19), live patient conditions, and long COVID monitoring (COVID recovered patients and healthy individuals) for better COVID-19 management. There are multitude of wearable devices that can observe various human body parameters for remotely monitoring patients and self-monitoring mode for individuals. Smart watches, smart tattoos, rings, smart facemasks, nano-patches, etc., have emerged as the monitoring devices for key physiological parameters, such as body temperature, respiration rate, heart rate, oxygen level, etc. This review includes long COVID challenges for frequent monitoring of biometrics and its possible solution with wearable device technologies for diagnosis and post-therapy of diseases.

Potential of using facial thermal imaging in patient triage of flu-like syndrome during the COVID-19 pandemic crisis.

The screening of flu-like syndrome is difficult due to nonspecific symptoms or even oligosymptomatic presentation and became even more complex during the Covid-19 pandemic. However, an efficient screening tool plays an important role in the control of highly contagious diseases, allowing more efficient medical-epidemiological approaches and rational management of global health resources. Infrared thermography is a technique sensitive to small alterations in the skin temperature which may be related to early signs of inflammation and thus being relevant in the detection of infectious diseases. Thus, the objective of this study was to evaluate the potential of facial thermal profiles as a risk evaluator of symptoms and signs of SARs diseases, using COVID-19 as background disease. A total of 136 patients were inquired about the most common symptoms of COVID-19 infection and were submitted to an infrared image scanning, where the temperatures of 10 parameters from different regions of the face were captured. We used RT-qPCR as the ground truth to compare with the thermal parameters, in order to evaluate the performance of infrared imaging in COVID-19 screening. Only 16% of infected patients had fever at the hospital admission, and most infrared thermal variables presented values of temperature significantly higher in infected patients. The maximum eye temperature (MaxE) showed the highest predictive value at a cut-off of >35.9°C (sn = 71.87%, sp = 86.11%, LR+ = 5.18, LR- = 0.33, AUC = 0.850, p < 0.001). Our predictive model reached an accuracy of 86% for disease detection, indicating that facial infrared thermal scanning, based on the combination of different facial regions and the thermal profile of the face, has potential to act as a more accurate diagnostic support method for early COVID-19 screening, when compared to classical infrared methods, based on a single spot with the maximum skin temperature of the face.

Determination of Internal Temperature by Measuring the Temperature of the Body Surface Due to Environmental Physical Factors-First Study of Fever Screening in the COVID Pandemic.

The SARS-CoV-2 virus pandemic has shown that the use of a contact thermometer to verify the elevated body temperature of a suspected person carries a risk of spreading disease. The perfect solution seems to be the use of thermal imaging as a diagnostic method in fever evaluation. The aim of the research is to develop an algorithm for thermovision measurements in fever screening standards in the context of the impact of various weather conditions on the temperature of people entering the public institution. Each examined person had two thermal images of the face-AP and lateral projection. Using a T1020 FLIR thermal camera with a resolution of 1024 × 768 pixels; the mean temperature was measured from the area of the forehead, the maximum forehead, the corners of the eyes, the inside of the mouth and the external auditory canal temperature. On the other hand, using classic contact thermometers, the temperature in the armpit and ear was measured. The obtained preliminary results showed very strong and positive correlations between the temperature in the ear measured with an ear thermometer and the maximum, minimum and average forehead temperature. These correlations oscillate at approximately r = 0.6, but the highest value of Spearman coefficient was obtained for the mean temperature of the forehead. Moreover, high correlations were also obtained between the temperature in the ear, measured with an ear thermometer, and the maximum temperature in the corners of the eyes and in the ear, measured with a thermal imaging camera. These values were, respectively, r = 0.54, r = 0.65. In summarizing, remote body temperature measurement taken with a thermal camera can be useful in the assessment of the body's core temperature.

Evaluation of a Wearable in-Ear Sensor for Temperature and Heart Rate Monitoring: A Pilot Study.

In the context of the COVID-19 pandemic, wearable sensors are important for early detection of critical illness especially in COVID-19 outpatients. We sought to determine in this pilot study whether a wearable in-ear sensor for continuous body temperature and heart rate monitoring (Cosinuss company, Munich) is sufficiently accurate for body temperature and heart rate monitoring. Comparing with several anesthesiologic standard of care monitoring devices (urinary bladder and zero-heat flux thermometer and ECG), we evaluated the in-ear sensor during non-cardiac surgery (German Clinical Trials Register Reg.-No: DRKS00012848). Limits of Agreement (LoA) based on Bland-Altman analysis were used to study the agreement between the in-ear sensor and the reference methods. The estimated LoA of the Cosinuss One and bladder temperature monitoring were [-0.79, 0.49] °C (95% confidence intervals [-1.03, -0.65] (lower LoA) and [0.35, 0.73] (upper LoA)), and [-0.78, 0.34] °C (95% confidence intervals [-1.18, -0.59] (lower LoA) and [0.16, 0.74] (upper LoA)) of the Cosinuss One and zero-heat flux temperature monitoring. 89% and 79% of Cosinuss One temperature monitoring were within ± 0.5 °C limit of bladder and zero-heat flux monitoring, respectively. The estimated LoA of Cosinuss One and ECG heart rate monitoring were [-4.81, 4.27] BPM (95% confidence intervals [-5.09, -4.56] (lower LoA) and [4.01, 4.54] (upper LoA)). The proportion of detection differences within ± 2BPM was 84%. Body temperature and heart rate were reliably measured by the wearable in-ear sensor.

A Novel Non-Invasive Thermometer for Continuous Core Body Temperature: Comparison with Tympanic Temperature in an Acute Stroke Clinical Setting.

There is a growing research interest in wireless non-invasive solutions for core temperature estimation and their application in clinical settings. This study aimed to investigate the use of a novel wireless non-invasive heat flux-based thermometer in acute stroke patients admitted to a stroke unit and compare the measurements with the currently used infrared (IR) tympanic temperature readings. The study encompassed 30 acute ischemic stroke patients who underwent continuous measurement (Tcore) with the novel wearable non-invasive CORE device. Paired measurements of Tcore and tympanic temperature (Ttym) by using a standard IR-device were performed 3-5 times/day, yielding a total of 305 measurements. The predicted core temperatures (Tcore) were significantly correlated with Ttym (r = 0.89, p < 0.001). The comparison of the Tcore and Ttym measurements by Bland-Altman analysis showed a good agreement between them, with a low mean difference of 0.11 ± 0.34 °C, and no proportional bias was observed (B = -0.003, p = 0.923). The Tcore measurements correctly predicted the presence or absence of Ttym hyperthermia or fever in 94.1% and 97.4% of cases, respectively. Temperature monitoring with a novel wireless non-invasive heat flux-based thermometer could be a reliable alternative to the Ttym method for assessing core temperature in acute ischemic stroke patients.

Safety and tolerability of a multilineage-differentiating stress-enduring cell-based product in neonatal hypoxic-ischaemic encephalopathy with therapeutic hypothermia (SHIELD trial): a clinical trial protocol open-label, non-randomised, dose-escalation trial.

INTRODUCTION: Neonatal hypoxic-ischaemic encephalopathy (HIE) is an important illness associated with death or cerebral palsy. This study aims to assess the safety and tolerability of the allogenic human multilineage-differentiating stress-enduring cell (Muse cell)-based product (CL2020) cells in newborns with HIE. This is the first clinical trial of CL2020 cells in neonates. METHODS AND ANALYSIS: This is a single-centre, open-label, dose-escalation study enrolling up to 12 patients. Neonates with HIE who receive a course of therapeutic hypothermia therapy, which cools to a body temperature of 33°C-34°C for 72 hours, will be included in this study. A single intravenous injection of CL2020 cells will be administered between 5 and 14 days of age. Subjects in the low-dose and high-dose cohorts will receive 1.5 and 15 million cells per dose, respectively. The primary outcome is the occurrence of any adverse events within 12 weeks after administration. The main secondary outcome is the Bayley Scales of Infant and Toddler Development Third Edition score and the developmental quotient per the Kyoto Scale of Psychological Development 2001 at 78 weeks. ETHICS AND DISSEMINATION: This study will be conducted in accordance with the Declaration of Helsinki and Good Clinical Practice. The Nagoya University Hospital Institutional Review Board (No. 312005) approved this study on 13 November 2019. The results of this study will be published in peer-reviewed journal and reported in international conferences. TRIAL REGISTRATION NUMBERS: NCT04261335, jRCT2043190112.

[Infrared Sensor ZTP-135SR and Its Application in Infrared Body Temperature Measurement].

Body temperature is an essential physiological parameter. Conducting non-contact, fast and accurate measurement of temperature is increasing important under the background of COVID-19. The study introduces an infrared temperature measurement system based on the thermopile infrared temperature sensor ZTP-135SR. Extracting original temperature date of sensor, post-amplification and filter processing have been performed to ensure accuracy of the system. In addition, the temperature data of environmental compensation which obtained by polynomial fitting is added to the system to further improve measurement accuracy.

Coronavirus Disease 2019 Temperature Trajectories Correlate With Hyperinflammatory and Hypercoagulable Subphenotypes.

OBJECTIVES: Body temperature trajectories of infected patients are associated with specific immune profiles and survival. We determined the association between temperature trajectories and distinct manifestations of coronavirus disease 2019. DESIGN: Retrospective observational study. SETTING: Four hospitals within an academic healthcare system from March 2020 to February 2021. PATIENTS: All adult patients hospitalized with coronavirus disease 2019. INTERVENTIONS: Using a validated group-based trajectory model, we classified patients into four previously defined temperature trajectory subphenotypes using oral temperature measurements from the first 72 hours of hospitalization. Clinical characteristics, biomarkers, and outcomes were compared between subphenotypes. MEASUREMENTS AND MAIN RESULTS: The 5,903 hospitalized coronavirus disease 2019 patients were classified into four subphenotypes: hyperthermic slow resolvers (n = 1,452, 25%), hyperthermic fast resolvers (1,469, 25%), normothermics (2,126, 36%), and hypothermics (856, 15%). Hypothermics had abnormal coagulation markers, with the highest d-dimer and fibrin monomers (p < 0.001) and the highest prevalence of cerebrovascular accidents (10%, p = 0.001). The prevalence of venous thromboembolism was significantly different between subphenotypes (p = 0.005), with the highest rate in hypothermics (8.5%) and lowest in hyperthermic slow resolvers (5.1%). Hyperthermic slow resolvers had abnormal inflammatory markers, with the highest C-reactive protein, ferritin, and interleukin-6 (p < 0.001). Hyperthermic slow resolvers had increased odds of mechanical ventilation, vasopressors, and 30-day inpatient mortality (odds ratio, 1.58; 95% CI, 1.13-2.19) compared with hyperthermic fast resolvers. Over the course of the pandemic, we observed a drastic decrease in the prevalence of hyperthermic slow resolvers, from representing 53% of admissions in March 2020 to less than 15% by 2021. We found that dexamethasone use was associated with significant reduction in probability of hyperthermic slow resolvers membership (27% reduction; 95% CI, 23-31%; p < 0.001). CONCLUSIONS: Hypothermics had abnormal coagulation markers, suggesting a hypercoagulable subphenotype. Hyperthermic slow resolvers had elevated inflammatory markers and the highest odds of mortality, suggesting a hyperinflammatory subphenotype. Future work should investigate whether temperature subphenotypes benefit from targeted antithrombotic and anti-inflammatory strategies.

Current infection prevention and control strategies of COVID-19 in hospitals

Background/aim: Coronavirus disease 2019 (COVID-19), caused by the severe acute respiratory syndrome coronavirus-2 (SARS-CoV-2), has been appeared first in China since December 2019. Transmission of SARS-CoV-2 occurs primarily with droplets through coughing and sneezing and also occurs through inhalation of aerosolized secretions, which travel, remain suspended in the air longer. Materials and methods: Since early stages of the outbreak, COVID-19 cases have been described in healthcare workers (HCWs). However, in the early stages, the disease may be asymptomatic. This may lead to incorrect diagnosis or delayed diagnosis and may lead to the nosocomial spread of the virus. One of the most important causes of transmission among HCWs is being exposed to an aerosolized virus in a closed environment for a long time. It is possible to prevent and control the spread of COVID-19 in hospitals with outpatient treatment and triage. Results: Infection control measures, including wearing surgical masks, hand hygiene, and social distance are considered essential in preventing human-to-human transmissions of SARS-CoV-2. Immediate response and practices of infection control measures are critical for saving lives during an epidemic inside and outside the hospital. Conclusion: Analyzing current knowledge about the features of SARS-CoV-2 infection, screening, personal protection protocols, triage and psychological support practices for healthcare professionals can be promising in terms of controlling the infection.

Detection of COVID-19 using multimodal data from a wearable device: results from the first TemPredict Study.

Early detection of diseases such as COVID-19 could be a critical tool in reducing disease transmission by helping individuals recognize when they should self-isolate, seek testing, and obtain early medical intervention. Consumer wearable devices that continuously measure physiological metrics hold promise as tools for early illness detection. We gathered daily questionnaire data and physiological data using a consumer wearable (Oura Ring) from 63,153 participants, of whom 704 self-reported possible COVID-19 disease. We selected 73 of these 704 participants with reliable confirmation of COVID-19 by PCR testing and high-quality physiological data for algorithm training to identify onset of COVID-19 using machine learning classification. The algorithm identified COVID-19 an average of 2.75 days before participants sought diagnostic testing with a sensitivity of 82% and specificity of 63%. The receiving operating characteristic (ROC) area under the curve (AUC) was 0.819 (95% CI [0.809, 0.830]). Including continuous temperature yielded an AUC 4.9% higher than without this feature. For further validation, we obtained SARS CoV-2 antibody in a subset of participants and identified 10 additional participants who self-reported COVID-19 disease with antibody confirmation. The algorithm had an overall ROC AUC of 0.819 (95% CI [0.809, 0.830]), with a sensitivity of 90% and specificity of 80% in these additional participants. Finally, we observed substantial variation in accuracy based on age and biological sex. Findings highlight the importance of including temperature assessment, using continuous physiological features for alignment, and including diverse populations in algorithm development to optimize accuracy in COVID-19 detection from wearables.

Fabrication of Wearable PDMS Device for Rapid Detection of Nucleic Acids via Recombinase Polymerase Amplification Operated by Human Body Heat.

Pathogen detection by nucleic acid amplification proved its significance during the current coronavirus disease 2019 (COVID-19) pandemic. The emergence of recombinase polymerase amplification (RPA) has enabled nucleic acid amplification in limited-resource conditions owing to the low operating temperatures around the human body. In this study, we fabricated a wearable RPA microdevice using poly(dimethylsiloxane) (PDMS), which can form soft-but tight-contact with human skin without external support during the body-heat-based reaction process. In particular, the curing agent ratio of PDMS was tuned to improve the flexibility and adhesion of the device for better contact with human skin, as well as to temporally bond the microdevice without requiring further surface modification steps. For PDMS characterization, water contact angle measurements and tests for flexibility, stretchability, bond strength, comfortability, and bendability were conducted to confirm the surface properties of the different mixing ratios of PDMS. By using human body heat, the wearable RPA microdevices were successfully applied to amplify 210 bp from Escherichia coli O157:H7 (E. coli O157:H7) and 203 bp from the DNA plasmid SARS-CoV-2 within 23 min. The limit of detection (LOD) was approximately 500 pg/reaction for genomic DNA template (E. coli O157:H7), and 600 fg/reaction for plasmid DNA template (SARS-CoV-2), based on gel electrophoresis. The wearable RPA microdevice could have a high impact on DNA amplification in instrument-free and resource-limited settings.

Forehead, Temple and Wrist Temperature Assessment of Ethnic Groups using Infrared Technology.

Non-contact infrared sensors are widely used as a diagnostic tool for elevated body temperature during initial screening for coronaviruses. The aim of this study was to investigate the thermal differences at three anatomical points: temple, forehead, and wrist, in the initial screening for temperature indicative of febrile and non-febrile states in skin pigmentation variations in Black, Half-Black and Caucasian skins, correlated with height and weight variables. Temperatures were obtained by means of an infrared thermometer in 289 volunteers with mean age of 18.30 ± 0.76, in a controlled environment according to Singapore Standard, SS582 part 1 and 2, normative standard IEC 80601-2-59, with standard technical protocols established by the International Organization for Standardization, ISO / TR 13154. The data were processed in MATLAB® R2021a, and data normality verified by Kolmogorov-Smirnov test, non-parametric data paired between temple / forehead / wrist were compared using the Wilcoxon signed-rank test. The results show different median temperatures in these anatomical regions, 37.2°C at the temple, 36.8°C at the forehead and 36.4°C at the wrist. As the temple region presents a temperature higher than the other investigated regions and, therefore, close to the core temperature, it should be considered for the initial screening of SARS-CoV-2 when using non-contact infrared thermometers. Furthermore, no significant changes were found due to variation in skin tone, height, or weight.

Predicting Deep Body Temperature (Tb) from Forehead Skin Temperature: Tb or Not Tb?

There is a need to rapidly screen individuals for heat strain and fever using skin temperature (Tsk) as an index of deep body temperature (Tb). This study's aim was to assess whether Tsk could serve as an accurate and valid index of Tb during a simulated heatwave. Seven participants maintained a continuous schedule over 9-days, in 3-day parts; pre-/post-HW (25.4 °C), simulated-HW (35.4 °C). Contact thermistors measured Tsk (Tforehead, Tfinger); radio pills measured gastrointestinal temperature (Tgi). Proximal-distal temperature gradients (ΔTforehead-finger) were also measured. Measurements were grouped into ambient conditions: 22, 25, and 35 °C. Tgi and Tforehead only displayed a significant relationship in 22 °C (r: 0.591; p < 0.001) and 25 °C (r: 0.408; p < 0.001) conditions. A linear regression of all conditions identified Tforehead and ΔTforehead-finger as significant predictors of Tgi (r2: 0.588; F: 125.771; p < 0.001), producing a root mean square error of 0.26 °C. Additional residual analysis identified Tforehead to be responsible for a plateau in Tgi prediction above 37 °C. Contact Tforehead was shown to be a statistically suitable indicator of Tgi in non-HW conditions; however, an error of ~1 °C makes this physiologically redundant. The measurement of multiple sites may improve Tb prediction, though it is still physiologically unsuitable, especially at higher ambient temperatures.

Contactless Measurement of Vital Signs Using Thermal and RGB Cameras: A Study of COVID 19-Related Health Monitoring.

In this study, a contactless vital signs monitoring system was proposed, which can measure body temperature (BT), heart rate (HR) and respiration rate (RR) for people with and without face masks using a thermal and an RGB camera. The convolution neural network (CNN) based face detector was applied and three regions of interest (ROIs) were located based on facial landmarks for vital sign estimation. Ten healthy subjects from a variety of ethnic backgrounds with skin colors from pale white to darker brown participated in several different experiments. The absolute error (AE) between the estimated HR using the proposed method and the reference HR from all experiments is 2.70±2.28 beats/min (mean ± std), and the AE between the estimated RR and the reference RR from all experiments is 1.47±1.33 breaths/min (mean ± std) at a distance of 0.6-1.2 m.