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In recent years, the subject of stress has become a key research area due to the increase
in stress in people as a result of changing lifestyles, work pressure or the Covid-19 pandemic.
Therefore, the introduction of preventive strategies for health protection, based on the latest
technologies, can play a preventive and control role. The stress detection solutions used so far
were often based on expensive devices for laboratory use, such as: ECG, EMG, GSR. A less
expensive alternative is thermal imaging, which ensures non-invasive, comfortable examination,
the possibility of using it in laboratory and home conditions, and which can use low-cost cameras
while maintaining data detail. Combined with machine learning techniques, stress detection
becomes more accurate and more reliable. Thanks to its features, thermography is more often used
in interdisciplinary research. Therefore, this article focuses on stress thermal imaging, describing
and comparing the latest research approaches. The most popular methods of stress detection,
which are an alternative to thermography, are also presented. The most common ones are
indicated: the analyzed physiological signals correlating with stress, the popular research devices
used, questionnaires and classification algorithms. The limitations of thermographic stress
detection are discussed, while at the same time pointing to selected research gaps in the field of
stress recognition and detection.
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