Martin Clinton Tosima Manullang, Yuan-Hsiang Lin, Sheng-Jie Lai, Nai-Kuan Chou
Non-contact physiological measurements based on image sensors have developed rapidly in recent years. Among them, thermal cameras have the advantage of measuring temperature in the environment without light and have potential to develop physiological measurement applications. Various studies have used thermal camera to measure the physiological signals such as respiratory rate, heart rate, and body temperature. In this paper, we provided a general overview of the existing studies by examining the physiological signals of measurement, the used platforms, the thermal camera models and specifications, the use of camera fusion, the image and signal processing step (including the algorithms and tools used), and the performance evaluation. The advantages and challenges of thermal camera-based physiological measurement were also discussed. Several sug-gestions and prospects such as healthcare applications, machine learning, multi-parameter, and image fusion, have been proposed to improve the physiological measurement of thermal camera in the future. © 2021 by the authors. Licensee MDPI, Basel, Switzerland.
Department of Electronic and Computer Engineering, National Taiwan University of Science and Technology, Taipei, 10607, Taiwan; Department of Informatics, Institut Teknologi Sumatera, South Lampung Regency, 35365, Indonesia; Department of Cardiovascular Surgery, National Taiwan University Hospital, Taipei, 10002, Taiwan
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