Increased Arousal Levels and Decreased Sleep by Brain Music in Rats

More and more studies have been reported on whether music and other types of auditory stimulation would improve the quality of sleep. Many of these studies have found significant results, but others argue that music is not significantly better than the tones or control conditions in improving sleep. For further understanding the relationship between music and sleep or music and arousal, the present study therefore examines the effects of brain music on sleep and arousal by means of biofeedback. The music is from the transformation of rapid eye movement （REM） sleep electroencephalogram （EEG） of rats using an algorithm in the Chengdu Brain Music （CBM） system. When the brain music was played back to rats, EEG data were recorded to assess the efficacy of music to induce or improve sleep, or increase arousal levels by sleep staging, etc. Our results demonstrate that exposure to the brain music increases arousal levels and decreases sleep in rats, and the underlying mechanism of decreased non-rapid eye movement （NREM） and REM sleep may be different.     

Increased Arousal Levels and Decreased Sleep by Brain Music in Rats

More and more studies have been reported on whether music and other types of auditory stimulation would improve the quality of sleep. Many of these studies have found significant results, but others argue that music is not significantly better than the tones or control conditions in improving sleep. For further understanding the relationship between music and sleep or music and arousal, the present study therefore examines the effects of brain music on sleep and arousal by means of biofeedback. The music is from the transformation of rapid eye movement (REM) sleep electroencephalogram (EEG) of rats using an algorithm in the Chengdu Brain Music (CBM) system. When the brain music was played back to rats, EEG data were recorded to assess the efficacy of music to induce or improve sleep, or increase arousal levels by sleep staging, etc. Our results demonstrate that exposure to the brain music increases arousal levels and decreases sleep in rats, and the underlying mechanism of decreased non-rapid eye movement (NREM) and REM sleep may be different.     

Support Vector Machines for Automated Recognition of Obstructive Sleep Apnea Syndrome From ECG Recordings

Obstructive sleep apnea syndrome (OSAS) is associated with cardiovascular morbidity as well as excessive daytime sleepiness and poor quality of life. In this study, we apply a machine learning technique [support vector machines (SVMs)] for automated recognition of OSAS types from their nocturnal ECG recordings. A total of 125 sets of nocturnal ECG recordings acquired from normal subjects (OSAS- ) and subjects with OSAS (OSAS+), each of approximately 8 h in duration, were analyzed. Features extracted from successive wavelet coefficient levels after wavelet decomposition of signals due to heart rate variability (HRV) from RR intervals and ECG-derived respiration (EDR) from R waves of QRS amplitudes were used as inputs to the SVMs to recognize OSAS +/- subjects. Using leave-one-out technique, the maximum accuracy of classification for 83 training sets was found to be 100% for SVMs using a subset of selected combination of HRV and EDR features. Independent test results on 42 subjects showed that it correctly recognized 24 out of 26 OSAS + subjects and 15 out of 16 OSAS - subjects (accuracy = 92.85%; Cohen's kappa value of 0.85). For estimating the relative severity of OSAS, the posterior probabilities of SVM outputs were calculated and compared with respective apnea/hypopnea index. These results suggest superior performance of SVMs in OSAS recognition supported by wavelet-based features of ECG. The results demonstrate considerable potential in applying SVMs in an ECG-based screening device that can aid a sleep specialist in the initial assessment of patients with suspected OSAS.     

Assessment of closed-loop ventilatory stability in obstructive sleep apnea

Previous studies on ventilatory control in obstructive sleep apnea (OSA) have generally indicated depressed chemosensitivity, implying greater stability of the chemical control of breathing in these subjects. However, these results were based on tests involving steady-state or quasi-steady measurements obtained in wakefulness. We have developed a method for assessing the dynamic stability characteristics of chemoreflex control in OSA patients during sleep. While continuous positive airway pressure was applied to stabilize the upper airways, acoustically stimulated arousals were used to perturb the respiratory system during sleep. The fluctuations in esophageal pressure that ensued were analyzed, using a closed-loop minimal model, to estimate the chemoreflex loop impulse response (CLIR). Tests using simulated data confirmed the validity of our estimation algorithm. Application of the method to arousal responses measured in six OSA and five normal subjects revealed no statistically significant differences in gain margins and loop gain magnitudes between the two groups. However, the CLIR in the OSA subjects exhibited faster and more oscillatory dynamics. This result implies that, in addition to unstable upper airway mechanics, an underdamped chemoreflex control system may be another important factor that promotes the occurrence of periodic obstructive apneas during sleep.     

Percutaneous biphasic electrical stimulation for treatment of obstructive sleep apnea syndrome

In this paper, we study the effect of stimulation of the genioglossus with percutaneous biphasic electrical pulses on patients with the obstructive sleep apnea syndrome (OSAS). The experiment was conducted in 22 patients clinically diagnosed with OSAS. The patients were monitored with polysomnography (PSG) in the trial. When the sleep apnea was detected, the genioglossus was stimulated with percutaneous biphasic electrical pulses that were automatically regulated by a microcontroller to achieve the optimal effect. The percutaneous biphasic electrical stimulation caused contraction of the genioglossus, forward movement of the tongue, and relieving of the glossopharyngeal airway obstruction. The SaO2, apnea time, hypoxemia time, and change of respiratory disturbance index (RDI) were compared in patients with treatment and without treatment. With percutaneous biphasic electrical stimulation of the genioglossus, the OSAS patients showed apnea time decreased (P < 0.01), RDI decreased (P < 0.01), and SaO2 increased (P < 0.01). No tissue injury or major discomfort was noticed during the trial. The stimulation of genioglossus with percutaneous biphasic electrical current pulse is an effective method for treating OSAS.     

Comparison of detrended fluctuation analysis and spectral analysis for heart rate variability in sleep and sleep apnea

Sleep has been regarded as a testing situation for the autonomic nervous system, because its activity is modulated by sleep stages. Sleep-related breathing disorders also influence the autonomic nervous system and can cause heart rate changes known as cyclical variation. We investigated the effect of sleep stages and sleep apnea on autonomic activity by analyzing heart rate variability (HRV). Since spectral analysis is suited for the identification of cyclical variations and detrended fluctuation analysis can analyze the scaling behavior and detect long-range correlations, we compared the results of both complementary techniques in 14 healthy subjects, 33 patients with moderate, and 31 patients with severe sleep apnea. The spectral parameters VLF, LF, HF, and LF/HF confirmed increasing parasympathetic activity from wakefulness and REM over light sleep to deep sleep, which is reduced in patients with sleep apnea. Discriminance analysis was used on a person and sleep stage basis to determine the best method for the separation of sleep stages and sleep apnea severity. Using spectral parameters 69.7% of the apnea severity assignments and 54.6% of the sleep stage assignments were correct, while using scaling analysis these numbers increased to 74.4% and 85.0%, respectively. We conclude that changes in HRV are better quantified by scaling analysis than by spectral analysis.     

Nonlinear analysis of the hippocampal subfields of CA1 and thedentate gyrus

The authors discuss the use of nonlinear bispectral analysis in examining the hippocampal EEG collected at subfields of CA1 and the dentate gyrus during the vigilance state of rapid-eye-movement (REM) sleep. The cross-bispectrum and its unique capabilities of detecting and quantifying quadratic nonlinear interactions occurring between these two hippocampal subfields are explained and demonstrated with simulation examples and EEG data. It was found that quadratic nonlinear interactions exist between CA1 and the dentate gyrus in the 6-8 frequency band which dominates the theta (&thetas;) rhythm observed in the hippocampal EEG during REM sleep. As a result, energy components around the frequency band of the second-order harmonics of &thetas; rhythm are not totally spontaneous, but generated largely due to quadratic nonlinear interactions     

Bispectral analysis of the rat EEG during various vigilance states

Bispectra were computed to detect phase coupling in the cortical and hippocampal EEG of the rat during various vigilance states. For EEG's recorded from the hippocampus, significant phase coupling was obtained during REM sleep between the frequency components (6-8 Hz) associated with theta rhythm.     

Analysis of heartbeat dynamics by point process adaptive filtering

Heartbeats are a point process yet, most of the current analysis methods do not model this important characteristic of these data. We describe human heartbeat time series as a history dependent inverse Gaussian model. We present a point process adaptive filter algorithm to estimate the model's time-varying parameters, and use it to compute new measures of heart rate variability. We apply our algorithm to analyze simulated heartbeat data and actual heartbeat data from a tilt table experiment and from healthy subjects and subjects with congestive heart failure during sleep. Our results suggest a new approach for characterizing heartbeat dynamics.     

A statistical model for the factory radio channel

A statistical model, based on experimental data, is presented to characterize the multipath propagation medium in typical manufacturing environments. The statistical behavior of the medium is described by a time-varying impulse response which includes the distribution of the parameters of the channel such as the gain, the interarrival time, and the number of paths. The resolvable components in a number of experimentally measured pulse responses of indoor factory radio channels were used to estimate the channel statistics. The interarrival times of the signals were modeled by the Weibull distribution. A model for the distribution of signals was presented using the modified beta distribution. The path gain coefficients were represented using the Rayleigh, Rician, or log-normal distributions. The model for the factory channel is flexible enough to fit the data for other indoor sites by changing the parameters of the factory channel appropriately relative to the size, topography, and other structural features of the site     

Sleep scoring using polysomnography data features

The paper is devoted to the analysis of multichannel biomedical signals acquired in the sleep laboratory. The data analyzed represent polysomnographic records of (i) 33 healthy individuals, (ii) 25 individuals with sleep apnea, and (iii) 18 individuals with sleep apnea and restless leg syndrome. The initial statistical analysis of the sleep segments points to an increase in the number of Wake stages and the decrease in REM stages with increase in age. The goal of the study is visualization of features associated with sleep stages as specified by an experienced neurologist and in their adaptive classification. The results of the support vector machine classifier are compared with those obtained by the k-nearest neighbors method, decision tree and neural network classification using sigmoidal and Bayesian transfer functions. The achieved accuracy for the classification into two classes (to separate the Wake stage from one of NonREM and REM stages) is between 85.6 and 97.5% for the given set of patients with sleep apnea. The proposed models allow adaptive modification of the model coefficients during the learning process to increase the diagnostic efficiency of sleep disorder analysis, in both the clinical and home environments.     

A comparison of conventional and matched filtering techniques forrapid eye movement detection of the newborn [electro-oculography]

Compares an extended conventional filter technique for automated detection and analysis of rapid eye movements (REM) in neonates, using amplitude, synchrony, velocity, and coherence threshold criteria, with a matched filtering technique using the morphology of the REM waveform. Analyses of both simulated and real data were carried out. Automated REM tabulations are compared with visual scoring by a trained observer. Both preterm and fullterm neonates were used to test these methods. Both the advantages and disadvantages of these two techniques are discussed as compared with conventional methods which use only amplitude and synchrony threshold criteria. The major advantage of the extended conventional over the conventional method, as well as the matched filtering over the extended conventional technique, is the increased REM detection rate for ten minute intervals of artifact-free sleep. More accurate methods of automated REM detection that can be applied over extended monitoring periods are still needed     

Observer of the human cardiac sympathetic nerve activity using noncausal blind source separation

We present a novel method for the blind reconstruction of the cardiac sympathetic nerve activity (CSNA) in the low-frequency (LF) band (0.04-0.15 Hz) using only heart rate and arterial blood pressure. The originality of the method consists in the application of blind source separation techniques to obtain an observer of CSNA. We show how this observer can be deduced from a linear model of the cardiovascular system by introduction of the fundamental assumptions about the independence of the cardiac sympathetic an parasympathetic outflow. In cardiovascular applications, the reliability of the observer has been assessed by verification of the fundamental assumption for the given data. A primer qualitative validation has been performed using the muscle sympathetic nerve activity as an indirect indicator of CSNA. Very satisfying and promising results have been obtained. Moreover, we have performed quantitative validations of the observer in various experimental conditions known to elicit selectively cardiac sympathetic or parasympathetic response. The experimental conditions include a supine-to-60 degrees tilt test, indirect sympathetic stimulation/inhibition by medication, and sympathetic stimulation by isometric handgrip. We show that the observer allows to highlight changing levels of the cardiac sympathetic activity in the LF band in all these experimental conditions.     

超脉冲CO2激光悬雍垂腭咽成形术治疗鼾症的近期临床研究

目的：探讨超脉冲CO2激光悬雍垂腭咽成形术治疗鼾症的可行性，技术操作及疗效。方法：采用超脉冲CO2激光悬雍垂腭咽成型术治疗鼾症64例。结果：该组病例近期均获得满意疗效，远期疗效达87.5%。术中出血极少，勿需缝合切口，切割创缘周期组织反应轻，手术时间短，无并发症发生。结论：该术式具有明显的临床应用价值，值得推广应用。     

Dispersion of Blood Pressure and Heart Rate in Essential Hypertension

The dispersion of the cardiovascular control system variables of heart period, systolic and diastolic blood pressure in a group of resting essential hypertensives has been compared with a group of normotensive subjects. Controlled variable dispersion in the absence of external perturbation was considered to be a measure of short term cardiovascular control system offset (error) from reference values (setpoint). The high blood pressure group demonstrated a greatly decreased controlled variable dispersion compared with the normal, implying the operation of a control system having a high closed loop gain, low system error and poor stability secondary to perturbation or stress. The extent of the changes in control system performance in essential hypertension was reduced by the adrenergic neuron blocking agent, guanethidine. These conclusions are consistent with and are discussed in relation to the known dynamic responses of heart rate and blood pressure to stress, together with the pathophysiology of the forward and feedback pathways of the cardiovascular control system, in essential hypertension.     

基于PVDF的可穿戴鼾声监测系统

阻塞型睡眠呼吸暂停综合征(OSAS)是常见的睡眠类疾病,为满足居家对OSAS进行初步筛查和诊断,该文设计了基于聚偏氟乙烯(PVDF)压电薄膜的鼾声监测系统。可穿戴式的鼾声监测系统包含高灵敏度鼾声传感器、低噪声信号调理电路、嵌入式系统及上位机系统。根据鼾声段和非鼾声段能量差异大的特点,基于短时能量法进行鼾声端点检测算法设计,通过采集的鼾声信号进行算法验证。经测试,系统采集的鼾声信号信噪比高,端点检测平均误差小于0.032 s,准确率达92.6%,满足潜在OSAS患者的筛查要求以及进行康复训练的自我检查,同时可减轻患者筛查和医学多导睡眠图(PSG)检测的负担。     

Mining statistically significant associations for exploratory analysis of human sleep data.

We introduce a specialized association rule mining technique that can extract patterns from complex sleep data comprising polysomnographic recordings, clinical summaries, and sleep questionnaire responses. The rules mined can describe associations among temporally annotated events and questionnaire or summary data; e.g., the likelihood that an occurrence of a rapid eye movement (REM) sleep stage during the second 100 sleep epochs of the night is associated with moderate caffeine intake. We use chi2 analysis to ensure statistical significance of the mined rules at the level P < 0.05. Our results, obtained by mining sleep-related data from 242 human subjects, reveal clinically interesting associations among the polysomnographic and summary variables. Our experience suggests that association mining may also be useful for selection of variables prior to using logistic regression.     

Local stability of REM algorithm with time-varying delays

We investigate the local stability in equilibrium for an Internet congestion control algorithm proposed by Low (see IEEE/ACM Transactions on Networking, vol.7, p.861-875,1999). The network consists of multisource and one-bottleneck link with heterogenous time-varying propagation delays. Linear matrix inequality (LMI) stability criteria is presented for discrete congestion control algorithm of TCP/REM dual model, which can be efficiently and easily solved by the LMI toolbox provided by Matlab software. An important feature is to acquire the maximum network delays to guarantee the stability of congestion control algorithm, i.e., the scale stability domain of REM algorithm.     

Cycle-Averaged Models of Cardiovascular Dynamics

Lumped-parameter time-varying electrical circuit analogs for the cardiovascular system are frequently used in medical research and teaching for simulating and analyzing hemodynamic data. Pulsatile models provide details of the intracycle dynamics of each heart beat. In some settings, however, such as when tracking a hospital patient's hemodynamic state over time, it is more useful to dynamically track the beat-to-beat or intercycle dynamics. Rather than introducing heuristic averaging during the model-building step, as is done in existing nonpulsatile models, we apply a short-term, cycle-averaging operation to the differential equations of the underlying pulsatile model to obtain cycle-averaged models. The cycle-averaging method preserves the dependence of the output variables on the model parameters. In this paper, we apply cycle averaging to a simple pulsatile cardiovascular model to derive a cycle-averaged model for cardiovascular dynamics. The resultant model captures the intercycle dynamics with relatively small approximation errors for a large range of perturbations in important system parameters