摘要
人体呼气中一氧化氮浓度(FeNO)与肺部呼吸道疾病有着紧密的联系,美国食品和药品管理局(FDA)、欧洲呼吸学会(ERS)和美国胸科学会(ATS)等权威机构相继将FeNO作为哮喘生物标志物,并将FeNO列为呼吸系统疾病的常规检查项目。针对FeNO高灵敏监测需求,发展了一套中红外波长调制激光吸收光谱检测仪,利用多元线性回归的方法解决了CO_(2)谱线交叉干扰问题,NO的检测限达到0.12×10^(-9)。利用多浓度标准气体对样机性能进行了定标,在0~215×10^(-9)体积分数范围内,仪器结果的线性相关性为0.994。最后,对中国中医科学院西苑医院的志愿者呼气样本进行了测量。
The fractional exhaled nitric oxide(FeNO)is closely related to lung and respiratory diseases.Authorities such as the US Food and Drug Administration(FDA),European Respiratory Society(ERS),and American Thoracic Society(ATS)have successively identified FeNO as an asthma biomarker and listed FeNO as a routine inspection item for respiratory diseases.In order to meet the needs of highsensitivity monitoring of FeNO,a midinfrared wavelength modulation laser absorption spectrometer is developed in this paper.The problem of cross interference of CO_(2) spectral lines is solved by the method of multiple linear regression,and the detection limit of NO reaches 0.12×10^(-9).The performance of the prototype is calibrated by standard gases with different concentrations,and the linear correlation of the instrument results is 0.994 in the volume fraction range of 0-215×10^(-9).Finally,the breath samples of volunteers from Xiyuan Hospital of Chinese Academy of Chinese Medical Sciences are measured.
作者
赵之豪
陈兵
邓昊
马国盛
黄安
刘英
阚瑞峰
苑振宇
Zhao Zhihao;Chen Bing;Deng Hao;Ma Guosheng;Huang An;Liu Ying;Kan Ruifeng;Yuan Zhenyu(College of Information Science and Engineering,Northeastern University,Shenyang 110000,Liaoning,China;Key Laboratory of Environmental Optics and Technology,Anhui Institute of Optics and Fine Mechanics,Hefei Institutes of Physical Science,Chinese Academy of Sciences,Hefei 230000,Anhui,China;University of Science and Technology of China,Hefei 230000,Anhui,China)
出处
《光学学报》
EI
CAS
CSCD
北大核心
2022年第21期220-226,共7页
Acta Optica Sinica
基金
国家自然科学基金青年项目(41901081,61805286)
中国科学院院级重大研制项目(ZDKYYQ20200006)
中国科学院环境光学与技术重点实验室开放基金(2005DP173065-2021-03)。
关键词
光谱学
一氧化氮
激光光谱
中红外波长调制
多元线性回归
spectroscopy
nitric oxide
laser spectrum
midinfrared wavelength modulation
multiple linear regression
作者简介
通信作者:苑振宇,yuanzhenyu@ise.neu.edu.cn;通信作者:阚瑞峰,kanruifeng@aiofm.ac.cn。
