Examination of Potential of Thermopile-Based Contactless Respiratory Gating

Abstract

To control the spread of coronavirus disease 2019 (COVID-19), it is effective to perform a fast screening of the respiratory rate of the subject at the gate before entering a space to assess the potential risks. In this paper, we examine the potential of a novel yet cost-effective solution, called thermopile-based respiratory gating, to contactlessly screen a subject by measuring their respiratory rate in the scenario with an entrance gate. Based on a customized thermopile array system, we investigate different image and signal processing methods that measure respiratory rate from low-resolution thermal videos, where an automatic region-of-interest selection-based approach obtains a mean absolute error (MAE) of 0.8 breaths per minute. We show the feasibility of thermopile-based respiratory gating and quantify its limitations and boundary conditions in a benchmark (e.g., appearance of face mask, measurement distance and screening time). The technical validation provided by this study is helpful for designing and implementing a respiratory gating solution toward the prevention of the spread of COVID-19 during the pandemic.

Technological Evolution of Image Sensing Designed by Nanostructured Materials

“…Several image and signal processing techniques to determine the respiration rate are employed as low-resolution thermal recordings using a modified thermopile array system. A methodology based on autonomous region of interest selection yields a mean absolute error (MAE) of 0.8 breaths every 60 s for the purpose of developing and putting into practice a respiratory solution to stop the transmission of COVID-19 during the pandemic . For many computer vision applications, such as MATLAB, recognizing children in thermal images utilizing thermopile array sensors (Th-AS) is essential, particularly for recognizing children left unsupervised in a parked car in extremely high temperatures.…”

“…A methodology based on autonomous region of interest selection yields a mean absolute error (MAE) of 0.8 breaths every 60 s for the purpose of developing and putting into practice a respiratory solution to stop the transmission of COVID-19 during the pandemic. 90 For many computer vision applications, such as MATLAB, recognizing children in thermal images utilizing thermopile array sensors (Th-AS) is essential, particularly for recognizing children left unsupervised in a parked car in extremely high temperatures. Many deadly incidents have been linked to careless parenting, and most parents have expressed regret over their children's incidents.…”