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WANG Yifan, WEN Xu. From Direct Calorimetry to Computer Vision: History and Future of Measurement of Energy Consumption in Physical Activities[J]. Journal of Shanghai University of Sport, 2023, 47(4): 92-104. DOI: 10.16099/j.sus.2022.07.13.0004
Citation: WANG Yifan, WEN Xu. From Direct Calorimetry to Computer Vision: History and Future of Measurement of Energy Consumption in Physical Activities[J]. Journal of Shanghai University of Sport, 2023, 47(4): 92-104. DOI: 10.16099/j.sus.2022.07.13.0004

From Direct Calorimetry to Computer Vision: History and Future of Measurement of Energy Consumption in Physical Activities

  • The development process of energy consumption measurement technology is systematically reviewed and clarified; various energy consumption measurement methods are analyzed; the new technology of computer vision estimation of human body energy consumption is mainly introduced; the development direction of energy consumption measurement technology in the new era of artificial intelligence is explored. Since the 17th century, the energy consumption measurement technology has gradually extended to a variety of non-calorimetric methods which started from the calorimetric method, resulting from the reason that calorimetric theories were established in 17th and 18th centuries. The 19th century witnessed the development of human body calorimetric system with the research progress on metabolism system, in the context of increasingly serious diseases. Since the 20th century, the technology innovation from the second industry revolution and further research on metabolism have helped the renewal of energy consumption measurement technology. Artificial Intelligence (AI) in the 21st century empowered the technology to develop into contactless measurement methods. With the impetus of research needs, theory and technology development, the existing measurement technologies have been renewing, but they still have limitations in terms of the measurement accuracy, operability and economy. Calorimetric method is characterized by high cost, complex operation, and poor practicability, while non-calorimetric method still needs to be improved on measurement accuracy. With the advent of the era of AI, intelligent and contactless measurement technology will be a key development direction. Microsensor is suggested to be applied regarding the calorimetric method; remote data transmission can be used to make the equipment quicker and more convenient. When regarding the non-calorimetric method, more related physical signs shall be explored to improve its measurement accuracy.
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