Contactless Vital Signs Measurement System Using RGB-Thermal Image Sensors and Its Clinical Screening Test on Patients with Seasonal Influenza

Abstract

Background: In the last two decades, infrared thermography (IRT) has been applied in quarantine stations for the screening of patients with suspected infectious disease. However, the fever-based screening procedure employing IRT suffers from low sensitivity, because monitoring body temperature alone is insufficient for detecting infected patients. To overcome the drawbacks of fever-based screening, this study aims to develop and evaluate a multiple vital sign (i.e., body temperature, heart rate and respiration rate) measurement system using RGB-thermal image sensors. Methods: The RGB camera measures blood volume pulse (BVP) through variations in the light absorption from human facial areas. IRT is used to estimate the respiration rate by measuring the change in temperature near the nostrils or mouth accompanying respiration. To enable a stable and reliable system, the following image and signal processing methods were proposed and implemented: (1) an RGB-thermal image fusion approach to achieve highly reliable facial region-of-interest tracking, (2) a heart rate estimation method including a tapered window for reducing noise caused by the face tracker, reconstruction of a BVP signal with three RGB channels to optimize a linear function, thereby improving the signal-to-noise ratio and multiple signal classification (MUSIC) algorithm for estimating the pseudo-spectrum from limited time-domain BVP signals within 15 s and (3) a respiration rate estimation method implementing nasal or oral breathing signal selection based on signal quality index for stable measurement and MUSIC algorithm for rapid measurement. We tested the system on 22 healthy subjects and 28 patients with seasonal influenza, using the support vector machine (SVM) classification method. Results: The body temperature, heart rate and respiration rate measured in a non-contact manner were highly similarity to those measured via contact-type reference devices (i.e., thermometer, ECG and respiration belt), with Pearson correlation coefficients of 0.71, 0.87 and 0.87, respectively. Moreover, the optimized SVM model with three vital signs yielded sensitivity and specificity values of 85.7% and 90.1%, respectively. Conclusion: For contactless vital sign measurement, the system achieved a performance similar to that of the reference devices. The multiple vital sign-based screening achieved higher sensitivity than fever-based screening. Thus, this system represents a promising alternative for further quarantine procedures to prevent the spread of infectious diseases.

The Role of Digital Technologies that Could Be Applied for Prescreening in the Mining Industry During the COVID-19 Pandemic

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Fig. 3 Schematic representation of an artificial intelligence-based camera to sense and measure the multiple vital signs of COVID-19 along with prescreening results, source: Negishi et al ( 2020 )

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An Inclusive Survey of Contactless Wireless Sensing: A Technology Used for Remotely Monitoring Vital Signs Has the Potential to Combating COVID-19

“…In other cases, thermal camera are used, which have the ability to register the temperature of a subject. In medicine, these special cameras are deployed in quarantine facilities to continuously monitor people and help recognise people with infectious diseases by monitoring their temperature [24] [25].…”

“…only body temperature, but also heart rate and respiration rate. The RGB camera is able to measure blood volume pulse (BVP) through the variations of light absorption on the human face [24]. Fig.21 shows a thermal image of a subject being observed.…”

Sensors, Signal and Image Processing in Biomedicine and Assisted Living

“…To overcome the drawbacks of infrared thermography, which is characterized from low sensitivity for fever-based screening, a novel measurement system combining RGB with thermal image sensors is presented and evaluated in [ 3 ]. This system measures multiple vital signs, including body temperature, heart rate and respiration rate, contactlessly.…”

“…This special issue gathers a broad range of novel contributions on sensors, systems, and signal/image processing methods for biomedicine and assisted living. These include methods for heart, sleep and vital sign measurement [ 1 , 2 , 3 , 4 , 5 ]; human motion-related signal analysis in the context of rehabilitation and tremor assessment [ 6 , 7 , 8 ]; assistive systems for color deficient and visually challenged individuals, as well as for wheelchair control by people with motor disabilities [ 9 , 10 , 11 , 12 ]; and, image and video-based diagnostic systems [ 13 , 14 , 15 , 16 ].…”