Yuxi Luo

Role of electroencephalogram and oxygen saturation in the induction mechanism of arousal for obstructive sleep apnea-hypopnea syndrome patients

Abstract Arousal concomitant with obstructive sleep apnea-hypopnea syndrome (OSAHS) is known to result in sleep fragmentation and excessive daytime sleepiness. The cause of arousal is multifarious, and the mechanism is not yet clear. The aim of this study was to further research the induction mechanism of arousal by investigating the variation of electroencephalogram (EEG) and oxygen saturation (SaO2). This study enrolled 20 subjects with a clinical diagnosis of OSAHS who underwent overnight polysomnography. Respiratory events and arousals were scored, and individuals with insufficient samples (<30) were excluded. Thus, 13 subjects mostly with severe OSAHS were analyzed in this study. The wavelet coefficients, spectral power of EEG (C4-M1 and C3-M2) before arousal or airway reopening, and the maximum desaturations of SaO2 during respiratory events were analyzed. For most subjects, EEG (in stages N1 and N2) during respiratory events with arousals exhibited significantly lower values of wavelet coefficients and spectral power (p < 0.05). The maximum desaturations of SaO2 during respiratory events with arousals are larger than those without among individual. In binary logistic regression analysis, the P values of EEG features and SaO2 desaturation were both less than 0.001. Our results demonstrate that in light NREM stage, less activity in EEG during respiratory events and larger SaO2 drop both independently were related to the occurrence of arousal. These significant differences come from major subjects based on the statistical analysis, and help supplement the induction mechanism of arousal.

The Impact of Respiratory Events on the Autonomic Nervous System during Sleep

Sleep apnea hypopnea syndrome (SAHS) is an independent risk factor for cardiovascular diseases. However, the pathophysiology between them is not yet clear. This paper seeks to understand how respiratory events impact the cardiovascular system by heart rate variability. We compared the differences between successional pathological respiratory events (PR) and pure normal respiration (NR) during sleep. The transitions between normal and pathological respiration (TR) were also analyzed. Thirteen patients who suffered moderate or severe SAHS were enrolled in this study. The results demonstrate that the beat-to-beat interval (RR interval) mean value and sample entropy are significantly lower during PR than during NR. RR interval standard deviation, the power of very low frequency (VLF) and low frequency (LF), total power, and the low frequency/high frequency (LF/HF) ratio were significantly larger during PR than during NR. However, the high frequency (HF) power was not significantly different between normal and pathological respiration. Additionally, the trends during TR also supported these significant differences. The results indicate that during pathological respiration, as the heart rate and its volatility increase, the complexity of its rhythm decreases. We conclude that the energy of the autonomic nervous system rapidly increases during pathological respiration, especially at the beginning. The HF power does not significantly change to modulate the heart rhythm, but the activity of the sympathetic nervous system will significantly increase, resulting in the imbalance of the LF/HF ratio. In addition to these findings, this paper discusses the influence of arousal on these indices during TR.

A BREATHING SYNCHRONIZATION STRATEGY FOR THE NON-INVASIVE VENTILATOR SYSTEM

The study presents a method to achieve a subject-ventilator synchronic pressure supply for a non-invasive ventilator (NIV) used for obstructive sleep apnea syndrome (OSAS), solely through controlling the blower instead of using expiratory relief valves. The controller used air flow signal to distinguish inspiratory and expiratory phases, and used a fast auto-forecast (AF) algorithm to predict the current inspiratory duration based on respiration periods distinguished previously. Then in a patients late inspiration the mechanical expiratory state was triggered to release pressure in advance. Afterward, when the beginning of a patients actual expiration was detected, a timer was used to trigger the end-expiratory state. As the index of patient-ventilator synchrony, subjects chest movement was detected by electrical impedance signal in experiments. The experimental results indicated that the previous state transition based on the prediction of inspiratory duration can eliminate the pressure overshoot spike, and then avoid excessive expiratory pressure to subjects. The fast auto-forecast with end expiratory positive airway pressure (AF-EEPAP) controlling strategy presented in this paper provided a mild pressure curve, which is consistent with the subjects respiratory physiology, and thus improved respiratory synchrony between subject and ventilator.

Correlation study in respiration fluctuations during sleep stages

BACKGROUND Healthy sleep can be characterized by several stages: wake, light, SWS, and REM sleep. The clinical experts find that the breath of subjects is different in these sleep stages, but such observation is lacking data supporting, The statistical research about investigating breathing patterns during sleep process will be helpful for the sleep and breathing domain. OBJECTIVE The objective of the paper is to statistically analyze the respiratory characteristics during different sleep stages. METHODS Firstly, we calculated the mean value and standard deviation of respiratory rates of these stages, in which the respiratory rates were obtained by the autocorrelation method. Then the detrended fluctuation analysis (DFA) algorithm was applied to analyze long-range correlation of respiratory rates of sleep stages. RESULTS The mean and standard deviation of respiratory rates are wake: 16.62 ± 2.43 cycles per minute (CPM), light: 15.15 ± 1.53 CPM, SWS: 15.06 ± 0.96 CPM and REM: 16.37 ± 2.03 CPM, respectively. The scaling exponent applied by detrended fluctuation analysis (DFA) algorithm reached about 0.7 for each stage. CONCLUSION Results of the mean and standard deviation of respiratory rates show that different sleep stages lead to different autonomic regulations of breathing and exhibit different respiratory rates and fluctuations. And the DFA results demonstrate that respiratory rates are all long-range correlated in these stages although they lead to different fluctuation.

The independent and combined effects of respiratory events and cortical arousals on the autonomic nervous system across sleep stages

PurposeDuring sleep, respiratory events readily modulate the autonomic nervous system (ANS). Whether such modulation is caused by the respiratory event itself or the cortical arousal that follows and whether these influences differ across sleep stages are not clear. Thus, we aimed to study the independent and combined effects of respiratory events and cortical arousals on the ANS across sleep stages.MethodsWe recruited 22 male patients with sleep apnea-hypopnea syndrome (SAHS) and analyzed the differences in the indices of heart rate variability among normal respiration (NR), pathological respiratory events without cortical arousals (PR), cortical arousals without respiratory events (CA), and the coexistence of PR and CA (PR&CA), by sleep stage.ResultsCompared with NR, four indices of variation of the beat-to-beat interval demonstrated consistent results in all sleep stages generally: PR&CA showed the biggest difference, followed by PR and followed by CA, which exhibited the least difference. Thus, the respiratory event itself affects ANS modulation, but the cortical arousal that follows generally enhances this effect. For low-frequency power and low-frequency/high-frequency power ratio (LF/HF), PR&CA had the greatest impact. For mean beat-to-beat interval and high-frequency power (HFP), the influence of PR, CA, and PR&CA depended on sleep depth. However, PR&CA had a different influence on HFP in N2 stage vs. REM stage.ConclusionsSleep stage also has an effect on this neuromodulatory mechanism. These findings may help clarify the relationship between SAHS and cardiovascular disease.

K-complex morphological features in male obstructive sleep apnea-hypopnea syndrome patients

This study characterized the differences in K-complex (KC) morphology features between obstructive sleep apnea-hypopnea syndrome (OSAHS) patients and healthy controls and analyzed the effect of respiratory events on KC morphology. We enrolled 42 male subjects (21 OSAHS patients and 21 age-matched healthy controls) who underwent overnight polysomnography. KCs in stage N2 were manually identified. We found that KCs in healthy controls had larger negative and whole amplitudes, longer durations, and smoother positive waves than OSAHS patients but smaller positive amplitudes. Most features showed highly significant differences after Bonferroni correction (p<0.001/3). After separating out the KCs associated with respiratory events in OSAHS patients, the differences between the groups remained but were relatively smaller. In OSAHS patients, compared with the spontaneous KCs not evoked by obvious factors, the KCs occurring after respiratory events had larger amplitudes, steeper slopes, larger negative wave amplitude and duration ratios. KCs occurring during respiratory events showed lower amplitudes and shorter durations. These results may reveal the impact of respiratory events on sleep and brain function.

The correlations between electroencephalogram frequency components and restoration of stable breathing from respiratory events in sleep apnea hypopnea syndrome

The purpose of this study was to explore the ways in which the Electroencephalogram (EEG) and oxygen saturation (SpO2) are involved in the progressive respiratory restoration process in patients with sleep apnea hypopnea syndrome (SAHS). Twenty-five SAHS patients were enrolled in the analysis. The respiratory events scored from polysomnography (PSG) recordings were divided into two groups as follows: the events followed by secondary events (SREs), which failed to recover stable breathing and those that spontaneously restored stable ventilation (N-SREs). The trends over the course from consecutive respiratory events (CRE) to stable breathing were also analyzed. Higher spectral powers of the δ, θ, and α bands and smaller sample entropy (SampEn) values in the EEG, along with a smaller SpO2 drop were observed in N-SREs, compared to those in SREs. It indicated there are correlations between these conditions and the restoration from respiratory events. The δ band power was the most relevant feature. In the CRE restoring process, the δ, θ, and α powers were significantly increased, while SampEn values exhibited the opposite tendency. Our results may reveal the relationship between EEG activity and respiratory rhythm control.

A NONINVASIVE METHOD TO EVALUATE THE DEGREE OF UPPER AIRWAY STENOSIS

Purpose: This paper presented a new approach to noninvasively evaluate the upper airway stenosis for obstructive sleep apnea syndrome (OSAS) patients. Methods: In the proposed method, thoracic and abdominal movements were selected to calculate the respiratory movement (RM) and to indicate the change of lung volume. Due to the cumulative effect of thermal sensor, the oronasal-thermistor signal (T_flow) is applied to estimate the air mass change in lung. Based on the mathematical relationship, the “RM–T_flow curves”, drawn by RM and T_flow, together with the correlation coefficients (rRM-TF) were used to analyze the upper airway stenosis. Results: This method was verified through portable monitoring (PM) based experiments, and numerical analysis of the polysomnography (PSG) data from 20 OSAS patients and 15 non-OSAS controls. Our results indicate the rRM-TF values decrease with the narrowing of the upper airway. At each sleep stage, the rRM-TF mean values of OSAS subjects are significantly (p<0.01) smaller ...

Relevance between the oro-nasal thermistor signal's derivative and the nasal pressure transducer signal in airflow monitoring

Signals of an oro-nasal thermistor (Th) and a nasal air pressure transducer (NP) are widely used as surrogates of airflow for diagnosing sleep-disordered breathing, while the relationships between Th and NP were less discussed. To demonstrate the time derivative of Th is linear correlated with NP, a total of 15,053 epochs (defined 30-s as 1 epoch) clinical data were studied. The correlation coefficients between the time derivative of Th and NP in each epoch were calculated and its mean value is 0.87. It indicated that the time derivative of Th has a linear positive correlation with NP.