Search

Objective: To propose a square's ring motion stimulation based on steady-state motion visual evoked potential, and compare it with the commonly used visual stimulation modes (Newton's ring motion, square flicker and circular flicker)., Methods: EEG signals were collected while 9 experimental subjects gazing at four stimulation and pattern analyzed by Canonical Correlation Analysis (CCA). Stimulation were evaluated by recognition accuracy and subjective scores., Results: The classification accuracies of SSVEP elicited by the square's ring motion(82.8%±14.1%) and Newton's ring(83.3%±11.5%) have no significant difference between them, which are lower than that of the square flicker(98.3%±4.1%) and the circular flicker(99.2%±1.8%). The shape of the figure has no significant influence on the classification accuracy either in motion mode or flicker mode. The comfort of the square's ring motion is higher than the other three stimulation according to subjective scores., Conclusions: The square's ring motion can elicit EEG and reduce the discomfort caused by flicker modes. The square's ring motion can be used as a visual stimulation in SSMVEP-based BCI system.

Rhythmic respiratory movement in a deep and slow pattern can be beneficial to cardiovascular system, this paper investigates the effect of step-wise paced breathing procedure on blood oxygen saturation (SpO2). Experiment objects were divided into two groups, the normobaric hypoxia (simulated altitude of 4 500 meters hypoxia environment, 8 persons), normoxia and normobaric group (laboratory environment, 49 persons). The respiratory movements were performed by a high-to-low progressive change in two groups respectively. During the experiment, each object's blood oxygen saturation and heart rate were recorded. Results showed that progressive guided breathing could significantly increase the subjects' blood oxygen saturation level from 90% to 95% under the hypoxic condition. Even under the normobaric and normoxic condition, progressive guided breathing with stable blood oxygen saturation level can also enhance the blood oxygen saturation level. In both groups, mean heart rate declined in the progressive guided breathing. The research showed that the step-wise paced breathing technique could regulate the blood oxygen saturation and effectively improve the level of blood oxygen saturation by adjusting the respiratory motion in the low oxygen environment.

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.

In comparison with the measurement of heart rate variability from ECG and from photoplethysmographic signal from 46 healthy adults in their spontaneous breathing state. The beat-to-beat intervals in ECG and pulse-to-pulse intervals in photoplethysmographic signal are extracted, and then the parameters of heart rate variability are calculated. Three kinds of algorithms are chosen to get the pulse-to-pulse intervals, which are the intervals of maximum of second derivative, the maximum of PPG signal and the tangent intersection. The results show that the correlation coefficients of the HRV parameters in the two calculation methods are highly correlated. The Bland-Altman scattered plots show the relative bias results from the algorithm of the maximum of PPG signal are smallest and singular points that deviate from the consistent limits are the least compared with the other two algorithms.

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.

This paper introduces a free and publicly open ICU database: multi-parameter intelligent monitoring in intensive care II: MIMIC-II, which has been built up and maintained by the laboratory of computational physiology at the Massachusetts Institute Technology, Beth Israel Deaconess Medical Center and Philips Healthcare over the past decade. This paper briefly introduces its infrastructure, implementation and applications in clinical studies. Clinical study pertaining to circadian variation in heart rate and blood pressure during sepsis is shown as a typical example of research performed with MIMIC-II. In this study, it was found there was significant difference in circadian variation in both heart rate and blood pressure between survival and non-survival groups in septic patients. This study tackled several important techniques necessary for the investigation of the circadian rhythm.