Forced oscillation technique (FOT) is an active method to test pulmonary function, which can derive the mechanical characteristics of the respiratory system with liner system identification theory by pushing in an oscillation air signal and measuring the changes of output pressure and flow. A pulmonary function determination system was developed based on the FOT in this paper. Several critical technologies of this determination system were analyzed, including the selection criteria of oscillation air generator, pressure and flow sensor, the signal design of oscillation air generator, and the synchronous sampling of pressure and flow data. A software program on LabVIEW platform was set up to control the determination system and get the measuring data. The performance of sensors and oscillation air generator was verified. According to the frequency response curve of the pressure, the amplitude of driving signal to the oscillation air generator was corrected at the frequency range between 4~40 Hz. A simulation experiment was carried out to measure the respiratory impedance of the active model lung ASL5000 and the results were close to the setting values of the model lung. The experiment testified that the pulmonary function determination system based on FOT had performance good enough to provide a tool for the in-depth research of the mechanical properties of the respiratory system.
The forced oscillation technique (FOT) is an active pulmonary function measurement technique that was applied to identify the mechanical properties of the respiratory system using external excitation signals. FOT commonly includes single frequency sine, pseudorandom and periodic impulse excitation signals. Aiming at preventing the time-domain amplitude overshoot that might exist in the acquisition of combined multi sinusoidal pseudorandom signals, this paper studied the phase optimization of pseudorandom signals. We tried two methods including the random phase combination and time-frequency domain swapping algorithm to solve this problem, and used the crest factor to estimate the effect of optimization. Furthermore, in order to make the pseudorandom signals met the requirement of the respiratory system identification in 4–40 Hz, we compensated the input signals’ amplitudes at the low frequency band (4–18 Hz) according to the frequency-response curve of the oscillation unit. Resuts showed that time-frequency domain swapping algorithm could effectively optimize the phase combination of pseudorandom signals. Moreover, when the amplitudes at low frequencies were compensated, the expected stimulus signals which met the performance requirements were obtained eventually.