Heart rate variability (HRV) analysis technology based on an autoregressive (AR) model is widely used in the assessment of autonomic nervous system function. The order of AR models has important influence on the accuracy of HRV analysis. This article presents a method to determine the optimum order of AR models. After acquiring the ECG signal of 46 healthy adults in their natural breathing state and extracting the beat-to-beat intervals (RRI) in the ECG, we used two criteria, i.e. final prediction error (FPE ) criterion to estimate the optimum model order for AR models, and prediction error whiteness test to decide the reliability of the model. We compared the frequency domain parameters including total power, power in high frequency (HF), power in low frequency (LF), LF power in normalized units and ratio of LF/HF of our HRV analysis to the results of Kubios-HRV. The results showed that the correlation coefficients of the five parameters between our methods and Kubios-HRV were greater than 0.95, and the Bland-Altman plot of the parameters was in the consistent band. The results indicate that the optimization algorithm of HRV analysis based on AR models proposed in this paper can obtain accurate results, and the results of this algorithm has good coherence with those of the Kubios-HRV software in HRV analysis.
To investigate the effect of stepwise paced breathing (PB) on pulse transit time (PTT), we collected physiological signals of electrocardiogram (ECG), respiration and arterial pulse wave during a procedure of stepwise PB, which consists of 6 different breathing rates changing in a protocol of 14.0-12.5-11.0-9.5-8.0-7.0 breath per minute (BPM), with each breathing rate lasting 3 minutes. Twenty two healthy adults involved in this experiment and the change of PTT was analyzed during the stepwise PB procedure. In our study, the PTT was measured by calculating the time interval from the R-spike of the ECG to the peaks of the second derivative of the arterial pulse wave. Ensemble empirical mode decomposition (EEMD) was applied to PTT to decompose the signal into different intrinsic mode function, and respiratory oscillation and trend component (baseline) in PTT were further extracted. It was found that the respiratory oscillations in the PTT increased with decreasing of the PB rate, and many of the subjects (14 out of 22) showed the phenomena of PTT baseline increasing during the stepwise PB procedure. The results indicated that the stepwise PB procedure induced a high level of cardiovascular oscillation and produced an accumulative effect of PTT baseline increase. As PTT is capable of predicting changes in BP over a short period of time, increase of PTT baseline indicates the decrease of blood pressure. The experiments showed that the stepwise PB procedure could reduce blood pressure for most subjects. For future work, it is necessary to develop certain indices differentiating the effectiveness of the stepwise PB procedure on the PTT baseline change, and to test the effectiveness of this stepwise PB procedure on blood pressure reduction for patients with essential hypertension.
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.