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

Tesař, Jiří; Muzika, Lukáš; Skála, Jiří; Kohlschütter, Tomáš; Honner, Milan

doi:10.3390/s23062945

Cited by 3 publications

(2 citation statements)

References 14 publications

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“…WD comes with sensors that can interpret physiological signals via electrical impulses. These devices find widespread usage in the healthcare sector, as well as in certain industries and sports fields [ 15 ]. In recent years, there has been a significant increase in the use of wearable biomedical sensors in healthcare, with a focus on monitoring vital signs in real time to manage chronic diseases [ 16 , 17 ].…”

Section: Introductionmentioning

confidence: 99%

A Low-Cost Wearable Device to Estimate Body Temperature Based on Wrist Temperature

Mata-Romero,

Simental-Martínez,

Guerrero-Osuna

et al. 2024

Sensors

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The remote monitoring of vital signs and healthcare provision has become an urgent necessity due to the impact of the COVID-19 pandemic on the world. Blood oxygen level, heart rate, and body temperature data are crucial for managing the disease and ensuring timely medical care. This study proposes a low-cost wearable device employing non-contact sensors to monitor, process, and visualize critical variables, focusing on body temperature measurement as a key health indicator. The wearable device developed offers a non-invasive and continuous method to gather wrist and forehead temperature data. However, since there is a discrepancy between wrist and actual forehead temperature, this study incorporates statistical methods and machine learning to estimate the core forehead temperature from the wrist. This research collects 2130 samples from 30 volunteers, and both the statistical least squares method and machine learning via linear regression are applied to analyze these data. It is observed that all models achieve a significant fit, but the third-degree polynomial model stands out in both approaches. It achieves an R2 value of 0.9769 in the statistical analysis and 0.9791 in machine learning.

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Section: Introductionmentioning

confidence: 99%

A Low-Cost Wearable Device to Estimate Body Temperature Based on Wrist Temperature

Mata-Romero,

Simental-Martínez,

Guerrero-Osuna

et al. 2024

Sensors

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show abstract

“…To combat various infectious viruses, governments need to direct prevention and control in public places and assign monitors, for example, non-contact temperature measurements through monitoring instruments [ 3 , 4 , 5 ]. However, monitoring large numbers of people in most places is a challenging task that involves detecting the wearing of masks, which most monitoring instruments lack.…”

Section: Introductionmentioning

confidence: 99%

A Face Detection and Standardized Mask-Wearing Recognition Algorithm

Zhang

et al. 2023

Sensors

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In the era of coronavirus disease (COVID-19), wearing a mask could effectively protect people from the risk of infection and largely reduce transmission in public places. To prevent the spread of the virus, instruments are needed in public places to monitor whether people are wearing masks, which has higher requirements for the accuracy and speed of detection algorithms. To meet the demand for high accuracy and real-time monitoring, we propose a single-stage approach based on YOLOv4 to identify the face and whether to regulate the wearing of masks. In this approach, we propose a new feature pyramidal network based on the attention mechanism to reduce the loss of object information that can be caused by sampling and pooling in convolutional neural networks. The network is able to deeply mine the feature map for spatial and communication factors, and the multi-scale feature fusion makes the feature map equipped with location and semantic information. Based on the complete intersection over union (CIoU), a penalty function based on the norm is proposed to improve positioning accuracy, which is more accurate at the detection of small objects; the new bounding box regression function is called Norm CIoU (NCIoU). This function is applicable to various object-detection bounding box regression tasks. A combination of the two functions to calculate the confidence loss is used to mitigate the problem of the algorithm bias towards determinating no objects in the image. Moreover, we provide a dataset for recognizing faces and masks (RFM) that includes 12,133 realistic images. The dataset contains three categories: face, standardized mask and non-standardized mask. Experiments conducted on the dataset demonstrate that the proposed approach achieves mAP@.5:.95 69.70% and AP75 73.80%, outperforming the compared methods.

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Role of Artificial Intelligence in Medical Image Analysis: A Review of Current Trends and Future Directions

Li,

Zhang,

Yang

et al. 2024

J. Med. Biol. Eng.

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

Cited by 3 publications

References 14 publications

A Low-Cost Wearable Device to Estimate Body Temperature Based on Wrist Temperature

A Low-Cost Wearable Device to Estimate Body Temperature Based on Wrist Temperature

A Face Detection and Standardized Mask-Wearing Recognition Algorithm

Role of Artificial Intelligence in Medical Image Analysis: A Review of Current Trends and Future Directions

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