Implementation of Thermal Camera for Non-Contact Physiological Measurement: A Systematic Review
| Autor: | Sheng-Jie Lai, Martin Clinton Tosima Manullang, Yuan-Hsiang Lin, Nai-Kuan Chou |
|---|---|
| Jazyk: | angličtina |
| Rok vydání: | 2021 |
| Předmět: |
Computer science
Measure (physics) ComputingMethodologies_IMAGEPROCESSINGANDCOMPUTERVISION TP1-1185 Biochemistry Temperature measurement Analytical Chemistry contactless sensors Machine Learning Respiratory Rate Heart Rate Thermal physiological measurement Computer vision Electrical and Electronic Engineering Image sensor Instrumentation Signal processing Image fusion business.industry Chemical technology Signal Processing Computer-Assisted Atomic and Molecular Physics and Optics non-contact Artificial intelligence Systematic Review thermal camera business Algorithms |
| Zdroj: | Sensors (Basel, Switzerland) Sensors, Vol 21, Iss 7777, p 7777 (2021) |
| ISSN: | 1424-8220 |
| Popis: | 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 suggestions 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. |
| Databáze: | OpenAIRE |
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