WANG Wei, WANG Yi, LIU Yanxiang, YANG Zhuoqing, LI Tie. Research progress on end-tidal carbon dioxide detection technologyJ. Journal of Functional Materials and Devices. DOI: 10.3724/jfmd.2603043
Citation: WANG Wei, WANG Yi, LIU Yanxiang, YANG Zhuoqing, LI Tie. Research progress on end-tidal carbon dioxide detection technologyJ. Journal of Functional Materials and Devices. DOI: 10.3724/jfmd.2603043

Research progress on end-tidal carbon dioxide detection technology

  • End-tidal carbon dioxide (ETCO2), as an important physiological parameter reflecting the state of gas exchange in the lungs, has significant application value in medical scenarios such as respiratory disease management. With the increasing demand for respiratory health monitoring and portable medical devices, respiratory monitoring is advancing toward continuous, non-invasive, and portable approaches. ETCO2 detection technology faces multiple engineering constraints, including dynamic response, high humidity interference, and system miniaturization, which impose stringent requirements on the overall performance of sensing technologies. This paper, starting from the application scenarios of ETCO2 detection, systematically analyzes its key technical constraints in terms of concentration range, dynamic characteristics, environmental interference, and engineering implementation. Based on this analysis, a comparative evaluation is conducted of CO2 gas sensing technologies, including non-dispersive infrared (NDIR), photoacoustic spectroscopy (PAS), tunable diode laser absorption spectroscopy (TDLAS), solid-state gas sensing, and semiconductor sensing2. Through comprehensive multi-parameter analysis, NDIR technology demonstrates optimal overall suitability for ETCO2 detection requirements in terms of selectivity, measurement range, system complexity, and engineering feasibility. Furthermore, this paper reviews the research progress of NDIR technology in ETCO2 detection and concludes that future advancements in ETCO2 detection can achieve continuous improvements in high precision, low power consumption, and multi-parameter fusion within NDIR-based systems through device optimization, system integration, and data-driven approaches, thereby providing critical technical support for continuous monitoring and accurate assessment of respiratory health.
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