Arousal pattern following central and obstructive breathing abnormalities in infants and children

McNamara, Frances, Faiq G. Issa, and Colin E. Sullivan.Arousal pattern following central and obstructive breathing abnormalities in infants and children. J. Appl.Physiol. 81(6): 2651-2657, 1996.We analyzed thepolysomnographic records of 15 children and 20 infants with obstructivesleep apnea (OSA) to examine the interaction between central andobstructive breathing abnormalities and arousal from sleep. Eachpatient was matched for age with an infant or child who had no OSA. Wefound that the majority of respiratory events in infants and childrenwas not terminated with arousal. In children, arousals terminated 39.3 ± 7.2% of respiratory events during quiet sleep and 37.8 ± 7.2% of events during active (rapid-eye-movement) sleep. In infants,arousals terminated 7.9 ± 1.0% of events during quiet sleep and7.9 ± 1.2% of events during active sleep. In both infants andchildren, however, respiratory-related arousals occurred more frequently after obstructive apneas and hypopneas than after central events. Spontaneous arousals occurred in all patients with OSA duringquiet and active sleep. The frequency of spontaneous arousals was notdifferent between children with OSA and their matched controls. Duringactive sleep, however, infants with OSA had significantly fewerspontaneous arousals than did control infants. We conclude that arousalis not an important mechanism in the termination of respiratory eventsin infants and children and that electroencephalographic criteria arenot essential to determine the clinical severity of OSA in thepediatric population.

     

Identification of Human Vital Functions Directly Relevant to the Respiratory System Based on the Cardiac and Acoustic Parameters and Random Forest

Regarding sleep research, polysomnography (PSG) also called a sleep study, is a gold standard. It incorporates brain waves, the oxygen level in the blood, heart rate and breathing, and leg movement recordings. PSG is a complicated and expensive laboratory-based procedure, usually done in hospitals or special sleep center. In this study, an alternative technique for Sleep-Related Breathing Disorders (SRBD) based on selected cardiac and acoustic parameters and the Random Forest (RF) has been studied. A system dedicated to the detection of simultaneously acquired ECG and acoustic signals, which are collected during sleep at home environment is proposed. Results obtained indicate that classification and regression tree models such as RF are appropriate for the evaluation of sleep disorders like SRBD. The best identification of sleep irregularities at level 89.00 percent for the raw database was obtained. Thus, statistical predictive models allow identification of breathing events with high levels of sensitivity and specificity, providing an inexpensive and accurate diagnosis.     

Sleep/wake estimation using only anterior tibialis electromyography data

ABSTRACT: BACKGROUND: In sleep efficiency monitoring system, actigraphy is the simplest and most commonly used device. However, low specificity to wakefulness of actigraphy was revealed in previous studies. In this study, we assumed that sleep/wake estimation using actigraphy and electromyography (EMG) signals would show different patterns. Furthermore, each EMG pattern in two states (sleep, wake during sleep) was analysed. Finally, we proposed two types of method for the estimation of sleep/wake patterns using only EMG signals from anterior tibialis muscles and the results were compared with PSG data. METHODS: Seven healthy subjects and five patients (2 obstructive sleep apnea, 3 periodic limb movement disorder) participated in this study. Night time polysomnography (PSG) recordings were conducted, and electrooculogram, EMG, electroencephalogram, electrocardiogram, and respiration data were collected. Time domain analysis and frequency domain analysis were applied to estimate the sleep/wake patterns. Each method was based on changes in amplitude or spectrum (total power) of anterior tibialis electromyography signals during the transition from the sleep state to the wake state. To obtain the results, leave-one-out-cross-validation technique was adopted. RESULTS: Total sleep time of the each group was about 8 hours. For healthy subjects, the mean epoch-by-epoch results between time domain analysis and PSG data were 99%, 71%, 80% and 0.64 (sensitivity, specificity, accuracy and kappa value), respectively. For frequency domain analysis, the corresponding values were 99%, 73%, 81% and 0.67, respectively. Absolute and relative differences between sleep efficiency index from PSG and our methods were 0.8 and 0.8% (for frequency domain analysis). In patients with sleep-related disorder, our proposed methods revealed the substantial agreement (kappa > 0.61) for OSA patients and moderate or fair agreement for PLMD patients. CONCLUSIONS: The results of our proposed methods were comparable to those of PSG. The time and frequency domain analyses showed the similar sleep/wake estimation performance.     

Recurrence analysis of nocturnal heart rate in sleep apnea patients.

This study examines the utility of recurrence analysis in the field of sleep apnea detection from heart rate series. In 38 patients, ECGs were recorded during sleep in parallel to polysomnography (PSG). Parameters extracted from distance matrices and from recurrence plots (RPs) of the time-delay embedded RR series were tested for their suitability to detect minute-by-minute phases of sleep apnea by means of receiver operating curve (ROC) analysis against the findings of the PSG. Features derived from the continuous distance matrix yielded better results (sensitivity 77%; specificity 78%) than those quantifying the structure of the binary RP (67% and 74%, respectively), accentuating the significance of information on the magnitude of heart rate variations for sleep apnea detection. However, simpler and computationally less demanding spectral techniques yield largely comparable results (77% and 72%, respectively). This raises the question as to whether recurrence analysis of RR series yields additional insight into sleep apnea recognition from heart rate variations.     

A Novel Wearable Real-Time Sleep Apnea Detection System Based on the Acceleration Sensor

Background and objectiveThe apnea syndrome is characterized by an abnormal breath pause or reduction in the airflow during sleep. It is reported in the literature that, it affects 2% of middle-aged women and 4% of middle-aged men, approximately. This study has vital importance, especially for the elderly, the disabled, and pediatric sleep apnea patients.MethodsIn this study, a device is developed to detect apnea events to alert the patient. The device records continuously accelerations on the diaphragm by using an acceleration sensor, which is placed on the patient's diaphragm. When the apnea is detected by the accelerometer-based system, a signal is sent to the wristband, and then the vibration motor on the wristband vibrates until the patient starts breathing again. The force of the vibration motor can be adjusted according to the patients' sleep debt, especially for elderly, disabled, or pediatric patients. There is no need for a sleeping room to see the patients' breathing properties since those parameters can be stored by using the developed device on a secure digital memory card (SD) at patients' homes during sleeping.ResultsA study group were formed of 10 patients (4 males (40%) and 6 females (60%)) with different characteristics ([mean] age, 36.3; height, 169.6 cm; and body weight, 81.4 kg). The patients in the study group have sleep apnea (SA). All the apnea events were detected, and all the patients were successfully alerted. Also, the lying position, which is a significant issue, is performed in this study.ConclusionsThis work proposed using an acceleration sensor as a reliable method of sleep apnea screening, detection of an apnea event, sending alert to the patient, and detection of the patient lying position. The developed device is more economical, comfortable, and convenient than existing systems for not only the patients but also the doctors. The patients can easily use this device in their home environment.     

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

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.     

Influence of sleep state on frequency of swallowing, apnea, and arousal in human infants.

Apnea and arousal are modulated with sleep stage, and swallowing may interfere with respiratory rhythm in infants. We hypothesized that swallowing itself would display interaction with sleep state. Concurrent polysomnography and measurement of swallowing allowed time-matched analysis of 3,092 swallows, 482 apneas, and 771 arousals in 17 infants aged 1-34 wk. The mean rates of swallowing, apnea, and arousal were significantly different, being 23.3 +/- 8.5, 9.4 +/- 8.8, and 15.5 +/- 10.6 h(-1), respectively (P < 0.001 ANOVA). Swallows occurred before 25.2 +/- 7.9% and during 74.8 +/- 6.3% of apneas and before 39.8 +/- 6.0% and during 60.2 +/- 6.0% of arousals. The frequencies of apneas and arousals were both strongly influenced by sleep state (active sleep > indeterminate > quiet sleep, P < 0.001), whether or not the events coincided with swallowing, but swallowing rate showed minimal independent interaction with sleep state. Interactions between swallowing and sleep state were predominantly influenced by the coincidence of swallowing with apnea or arousal.     

自由活动大鼠睡眠状态和呼吸节律的同步监测方法

目的:设计一种睡眠呼吸暂停综合征动物模型的监测方法.方法:通过多导生理仪同步监测自由活动大鼠6 h生理睡眠时间的皮层脑电、颈部肌电,以及呼吸波形.并用人机交互的方法进行数据处理.结果:监测信号稳定、清晰易辨,根据记录到的信号可进行不同清醒-睡眠状态分期,并判断大鼠的呼吸暂停情况.结论:该法操作简便,是小动物睡眠和呼吸监测的可靠方法.     

A transition-constrained discrete hidden Markov model for automatic sleep staging

ABSTRACT: BACKGROUND: Approximately one-third of the human lifespan is spent sleeping. To diagnose sleep problems, all-night polysomnographic (PSG) recordings including electroencephalograms (EEGs), electrooculograms (EOGs) and electromyograms (EMGs), are usually acquired from the patient and scored by a well-trained expert according to Rechtschaffen & Kales (R&K) rules. Visual sleep scoring is a time-consuming and subjective process. Therefore, the development of an automatic sleep scoring method is desirable. METHOD: The EEG, EOG and EMG signals from twenty subjects were measured. In addition to selecting sleep characteristics based on the 1968 R&K rules, features utilized in other research were collected. Thirteen features were utilized including temporal and spectrum analyses of the EEG, EOG and EMG signals, and a total of 158 hours of sleep data were recorded. Ten subjects were used to train the Discrete Hidden Markov Model (DHMM), and the remaining ten were tested by the trained DHMM for recognition. Furthermore, the 2-fold cross validation was performed during this experiment. RESULTS: Overall agreement between the expert and the results presented is 85.29%. With the exception of S1, the sensitivities of each stage were more than 81%. The most accurate stage was SWS (94.9%), and the least-accurately classified stage was S1 (<34%). In the majority of cases, S1 was classified as Wake (21%), S2 (33%) or REM sleep (12%), consistent with previous studies. However, the total time of S1 in the 20 all-night sleep recordings was less than 4%. CONCLUSION: The results of the experiments demonstrate that the proposed method significantly enhances the recognition rate when compared with prior studies.     

Sleep Complaints and Polysomnographic Findings: A Study of Nuclear Power Plant Shift Workers

The literature widely recognizes that shift workers have more health complaints than the general population. The objective of this study was to describe the prevalence of sleep complaints and verify the polysomnographic (PSG) variables of shift workers in two Brazilian nuclear power plants. We carried out a subjective evaluation with a sleep questionnaire. Based on these results, the interviewees that reported sleep‐related complaints were referred for polysomnographic evaluation. Of the 327 volunteers initially evaluated by the sleep questionnaire, 113 (35%) reported sleep complaints; they were significantly older, had higher body mass index (BMI), and worked more years on shifts than those without sleep complaints. Of these 113, 90 met criteria for various sleep disorders: 30 (9%) showed obstructive sleep apnea (OSA), 18 (5.5%) showed limb movement, and 42 (13%) evidenced both sleep problems and had a significantly higher proportion of sleep stage 1 and arousals compared with the 23 shift workers that had no indices of sleep problems. The present study found that 90 (27.5%) of the evaluated participants met the PSG criteria of some type of clinical sleep disorder. This high proportion should be investigated for associations with other aspects of work, such as working hours, working schedule, years performing shift work, and access to health services. Due to the strong association between sleep disorders and the incidence of fatigue and sleepiness, the evaluation of the sleep patterns and complaints of shift workers is essential and should be considered to be one of the basic strategies of industry to prevent accidents.     

Sleep complaints and polysomnographic findings: a study of nuclear power plant shift workers

The literature widely recognizes that shift workers have more health complaints than the general population. The objective of this study was to describe the prevalence of sleep complaints and verify the polysomnographic (PSG) variables of shift workers in two Brazilian nuclear power plants. We carried out a subjective evaluation with a sleep questionnaire. Based on these results, the interviewees that reported sleep-related complaints were referred for polysomnographic evaluation. Of the 327 volunteers initially evaluated by the sleep questionnaire, 113 (35%) reported sleep complaints; they were significantly older, had higher body mass index (BMI), and worked more years on shifts than those without sleep complaints. Of these 113, 90 met criteria for various sleep disorders: 30 (9%) showed obstructive sleep apnea (OSA), 18 (5.5%) showed limb movement, and 42 (13%) evidenced both sleep problems and had a significantly higher proportion of sleep stage 1 and arousals compared with the 23 shift workers that had no indices of sleep problems. The present study found that 90 (27.5%) of the evaluated participants met the PSG criteria of some type of clinical sleep disorder. This high proportion should be investigated for associations with other aspects of work, such as working hours, working schedule, years performing shift work, and access to health services. Due to the strong association between sleep disorders and the incidence of fatigue and sleepiness, the evaluation of the sleep patterns and complaints of shift workers is essential and should be considered to be one of the basic strategies of industry to prevent accidents.     

TNF-α and Temporal Changes in Sleep Architecture in Mice Exposed to Sleep Fragmentation

TNF-α plays critical roles in host-defense, sleep-wake regulation, and the pathogenesis of various disorders. Increases in the concentration of circulating TNF-α after either sleep deprivation or sleep fragmentation (SF) appear to underlie excessive daytime sleepiness in patients with sleep apnea (OSA). Following baseline recordings, mice were subjected to 15 days of SF (daily for 12 h/day from 07.00 h to 19.00 h), and sleep parameters were recorded on days1, 7 and 15. Sleep architecture and sleep propensity were assessed in both C57BL/6J and in TNF-α double receptor KO mice (TNFR KO). To further confirm the role of TNF-α, we also assessed the effect of treatment with a TNF- α neutralizing antibody in C57BL/6J mice. SF was not associated with major changes in global sleep architecture in C57BL/6J and TNFR KO mice. TNFR KO mice showed higher baseline SWS delta power. Further, following 15 days of SF, mice injected with TNF-α neutralizing antibody and TNFR KO mice showed increased EEG SWS activity. However, SWS latency, indicative of increased propensity to sleep, was only decreased in C57BL/6J, and was unaffected in TNFR KO mice as well as in C57BL/6J mice exposed to SF but treated with TNF-α neutralizing antibody. Taken together, our findings show that the excessive sleepiness incurred by recurrent arousals during sleep may be due to activation of TNF-alpha-dependent inflammatory pathways, despite the presence of preserved sleep duration and global sleep architecture.     

Comparing in-lab full polysomnography for diagnosing sleep apnea in children to home sleep apnea tests (HSAT) with an online video attending technician

Sleep and Biological Rhythms - The main study aim was to compare the validity of children sleep apnea data obtained from standard polysomnography (PSG) to a home sleep apnea test (HSAT) accompanied...     

Detection of Abnormal Respiratory Events with Single Channel ECG and Hybrid Machine Learning Model in Patients with Obstructive Sleep Apnea

Respiratory scoring is an important step in the diagnosis of Obstructive Sleep Apnea (OSA). Airflow, abdolmel-thorax and pulse oximetry signals are obtained with the help of Polysomnography (PSG) device for the respiration scoring stage. These signals are visually scored by a specialist physician. The PSG has several disadvantages: one of them is that a technician is required to use the device. In addition, the records must be taken in the hospital environment. The aim of this study is to develop a new machine learning based hybrid sleep/awake detection method with single channel ECG alternative to respiratory scoring. For this purpose, electrocardiography (ECG) signal of 10 patients with OSA was used. The Heart Rate Variable signal was derived from the ECG signal. Then, QRS components in different frequency bands were obtained from ECG signal by digital filtering. In this way, a total of nine more signals were obtained. Each of the nine signals consists of 25 features, which amounts to a total of 225 features. Fisher feature selection algorithm and Principal Component Analysis (PCA) were used to reduce the number of features. Ultimately the features extracted from the first received signals were classified with Decision Tree, Support Vector Machines, k-Nearest Neighborhood Algorithm and Ensemble classifiers. In addition, the proposed model was checked with the Leave One Out method. At the end of the study, for the detection of apnea, 82.11% accuracy with only 3 features and 85.12% accuracy with 13 features were obtained. The sensitivity and specificity values for the 3 properties are 0.82 and 0.82, respectively. For the 13 properties, 0.85 and 0.86, respectively. These results show that the proposed model can be used for the detection of Respiratory Scoring in the OSA diagnostic process.     

自由活动大鼠睡眠呼吸监测技术改进

目的：改进大鼠睡眠呼吸监测技术,解决既往模型中咬线、脱落、信号不稳定问题。方法：改进监测电极、信号接入线路及动物手术。结果：改进后手术时间缩短,创面暴露时间减少,大鼠术后易恢复。且电极稳固性好,脑电和肌电信号更稳定清晰,信号接入线路传导性好,耐用。实现连续长时间监测,成功率高。便于根据信号进行不同清醒一睡眠状态分期,并判断大鼠睡眠呼吸暂停情况。结论：改进后的操作技术操作更简单、信号更稳定,是一项更加实用可靠的小动物睡眠呼吸监测技术。     

悬雍垂腭咽成形术治疗阻塞性睡眠呼吸 暂停综合征46 例疗效分析

目的：通过对睡眠呼吸暂停综合征病人（obstructlve sleep apnea syndrome,OSAS）睡眠呼吸参数的比较,探讨UPPP治疗OSAS的效果。方法：经多导睡眠图（Polysomnography,PSG）确诊为OSAS的病人46例,选择呼吸紊乱指数（apnea and hypopnea index,AHI）、呼吸暂停指数（apnea index,AI）及睡眠中的最低SaO2值作为评价OSAS轻重程度的指标。计算轻中度组、重度组在手术前后的AHI缓解率、最低SaO2缓解率厦显效率,并作为衡量UPPP手术治疗效果的指标。分析患者在手术前后AHI、最低SaO2的相关性;分析轻中度组和重度组的缓解率、最低SaO2缓解率及治愈率的相关性。结果：1利用UPPP手术治疗OSAS,患者手术前后AHI、最低SaO2具有相关性。2在分组资料中,轻中度组和重度组的缓解率、最低SaO2缓解率及显效率都具有显著相关性。结论：（1）UPPP是治疗OSAS的有效方法;（2）轻中度组的治疗效果要好于重度组。     

阻塞性睡眠呼吸暂停综合征临床监测分析

目的:探讨阻塞性睡眠呼吸暂停综合征患者的临床特征及评价疗效。方法:回顾分析70例阻塞性睡眠呼吸暂停综合征患者PSG监测数据。结果:随着呼吸紊乱指数的增加,年龄、体重指数、最长呼吸暂停时间、最低SaO_2%、平均SaO_2%下降等指标在轻度与中、重度SAS之间差异显著;70例患者中伴有高血压52.9%、糖尿病5.7%、冠心病21.4%。结论:OSAS是一种具有潜在危险的疾痛,对OSAS早期诊断治疗是预防发生严重并发症的关键。     

双牙列套式口腔矫正器治疗老年阻塞性呼吸暂停综合征患者的临床疗效观察

目的：探讨双牙列套式口腔矫正器治疗老年阻塞性睡眠呼吸暂停综合征(OSAS)的临床疗效。方法：选取我院诊治的60 例老 年OSAS 患者为研究对象,所有患者均自愿采用双牙列套式口腔矫正器治疗。治疗前后,应用多导睡眠监测仪(PSG)检测和比较 患者的呼吸暂停指数、低通气指数以及血氧饱和度,并评价患者的临床疗效,采用生活质量评价表(SF-6)评价患者生活质量的变 化。结果：①治疗后,患者的呼吸暂停指数、低通气指数均较治疗前明显降低,而血氧饱和度较治疗前显著增加,差异均存在统计 学意义(P<0.05),治疗总有效率为93.33%;②治疗后,患者的躯体功能、躯体健康、躯体疼痛、总体健康感、生命活力、社交功能、情 感角色以及精神健康评分均较治疗前明显提升,差异均存在统计学意义(P 均<0.05)。结论：双牙列套式口腔矫正器不仅能够有效 改善OSAS患者的症状,而且能够提高患者的生活质量,是治疗OSAS较为理想的方法之一。     

The Relationship between CPAP Usage and Corneal Thickness

The purpose of this study was to determine whether there is a correlation between CPAP usage and corneal thickness in patients with sleep disordered breathing. Full-night polysomnography (PSG) recordings were collected. Ten patients had undergone PSG recordings with continuous positive airway pressure (CPAP), and seven patients had undergone PSG recordings without CPAP. We measured corneal thickness by ultrasonic pachymeter before sleep and ten minutes after waking. We also measured visual acuity with a routine ophthalmologic eye chart before and after sleep. We asked patients to fill out a post-sleep questionnaire to get their subjective opinions. In the without-CPAP group, corneal thickness increased significantly during sleep in both eyes (left, p = 0.0025; right, p<0.0001). In the with-CPAP group, corneal thickness did not increase significantly (p>0.05 for both left and right cornea). There was no significant difference in visual acuity tests (p>0.05 for both left and right eye) between the two groups. According to our results, there is a significant increase in corneal thickness in the without-CPAP group. Our data show that a low percentage of Rapid Eye Movement (REM) sleep may cause an increase in corneal thickness, which can indicate poor corneal oxygenation. In fact, many sleep-disordered breathing (SDB) patients have low REM. Since a contact lens may cause low corneal oxygenation, SDB patients with contact lenses should be monitored carefully for their corneal thickness.     

Nonlinearity in normal human EEG: cycles,temporal asymmetry,nonstationarity and randomness,not chaos

Two-hour vigilance and sleep electroencephalogram (EEG) recordings from five healthy volunteers were analyzed using a method for identifying nonlinearity and chaos which combines the redundancy–linear redundancy approach with the surrogate data technique. A nonlinear component in the EEG was detected, however, inconsistent with the hypothesis of low-dimensional chaos. A possibility that a temporally asymmetric process may underlie or influence the EEG dynamics was indicated. A process that merges nonstationary nonlinear deterministic oscillations with randomness is proposed for an explanation of observed properties of the analyzed EEG signals. Taking these results into consideration, the use of dimensional and related chaos-based algorithms in quantitative EEG analysis is critically discussed. Received: 25 September 1994 / Accepted in revised form: 10 July 1996