In recent years, death and economic losses caused by respiratory diseases have occurred globally, with a significant portion of respiratory disease patients facing challenges related to delayed early detection and inadequate treatment in later stages. With the advancing medical technology, numerous studies have demonstrated a close association between the volume fraction of human fractional exhaled nitric oxide (FeNO) and respiratory disease. In normal individuals, airway epithelial cells produce a small amount of nitric oxide (NO), with volume fractions generally below 2.5×10^-8. However, in patients with respiratory diseases, inflammatory cells in the airways produce a large amount of NO, with volume fractions generally 2-10 times higher than those in normal individuals. FeNO detection is a non-invasive, simple, rapid, and efficient method for exhaled breath diagnosis. It can be employed to differentiate respiratory diseases with similar clinical presentations, such as asthma, chronic obstructive pulmonary disease (COPD), and overlapping syndromes. Additionally, it can predict treatment outcomes and post-treatment management for patients with these conditions. FeNO detection provides information that cannot be obtained from medical history, physical examinations, and lung function tests alone, and it contributes to improving the diagnosis and treatment of respiratory diseases, elevating the clinical management of respiratory diseases to a new height.

For FeNO detection, we utilize tunable diode laser absorption spectroscopy (TDLAS) technology, which is known for its high sensitivity, precision, and fast response rate. The fundamental theory of TDLAS is based on Beer-Lambert's law that when light passes through a certain volume fraction of gas, gas molecules absorb light at specific wavelengths. The relationship between the emitted light intensity and incident light intensity can be directly adopted to establish the relationship between the signal magnitude and gas molecule volume fraction. Direct absorption spectroscopy (DAS) directly applies this law. Due to the susceptibility of DAS to low-frequency noise such as interference fringes, wavelength modulation spectroscopy (WMS) is a commonly adopted method to suppress low-frequency noise. The basic principle of a WMS involves the combination of a low-frequency triangular wave signal and a high-frequency sine wave signal generated by a signal generator. These signals are introduced into the laser to drive both scanning and modulation of the laser wavelength, and the laser is directed into the gas absorption cell, interacting with gas molecules. The detector receives the laser light after the interaction and converts the optical signal into an electrical signal, and the lock-in amplifier demodulates it into a harmonic signal. The relationship between the harmonic signal and gas molecule volume fraction is established by gas calibration.

We calibrate the exhaled carbon dioxide (CO₂) volume fraction within a single exhalation cycle using both DAS and WMS (Figs. 4 and 5). By simulating the second harmonic signals of mixed gases of CO₂ and NO, we determine correlation coefficients to achieve the inversion of FeNO volume fraction (Figs. 6 and 7). By a 15-minute continuous measurement of the volume fraction changes of mixed gases of CO₂ and NO, and Allan variance curve analysis, the system's CO₂ gas measurement precision and detection limit are determined to be 0.045% and 5.4×10^-3 [Figs. 8(a) and 10(a)] respectively. For NO, the measurement precision and detection limit are found to be 1.1×10^-9 and 3.4×10^-9 [Figs. 8(b) and 10(b)], respectively. By repeatedly replacing mixed gases of CO₂ and NO with nitrogen (N₂) and measuring the gas volume fraction changes over time, the system's response time is determined to be 12 s (Fig. 9). Finally, based on the gas curve during a single exhalation cycle at an exhalation flow rate of 3 L/min, the volume fractions of CO₂ and NO in the exhaled breath of 18 volunteers are determined (Figs. 11 and 12).

We establish a FeNO detection system based on TDLAS, with the selected target absorption line for NO at a wavenumber of 1900.07 cm^-1. Experimentation is conducted with NO at a volume fraction of 4.76×10^-6 under a pressure of 0.3 atm, and 46 mV is chosen as the optimal modulation amplitude. DAS and WMS are adopted to calibrate the CO₂ volume fraction. By simulating the second harmonic signals, we calculate the relationship between the signals of CO₂ and NO, completing NO volume fraction calibration. Precision, response time, and stability of both CO₂ and NO are analyzed to evaluate the system performance. Through Allan variance analysis, within an integration time of 25 s, the system's detection limits for CO₂ and NO are determined to be 5.4×10^-3 and 3.4×10^-9 respectively. Finally, an analysis of different stages of the complete exhalation cycle in adults is conducted to calculate the concentrations of CO₂ and NO, and 18 volunteer samples are processed and analyzed. Experimental results demonstrate the feasibility of using a mid-infrared quantum cascade laser (QCL) for low-concentration measurement of NO, providing references for real-time online detection of human exhaled gases.