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Introduction: obstructive sleep apnea hypopnea syndrome (OSAHS) is a common but often under diagnosed disease among elderly persons. The aim of our study was to determine the clinical and polygraphic characteristics of OSAHS in elderly by comparing them to younger patients. Methods: a retrospective study was performed at Pavillon D pneumology at Abderrahmen Mami Hospital in Ariana including 222 patients with OSAHS, divided into two groups: group 1 including 72 patients aged 18 to 45 years and Group 2 including 150 patients aged 65 and over. Clinical and polygraphic data was collected. Results: elderly patients were more female, less exposed to tobacco but more exposed to biomass smoke. The average consultation time was significantly longer for elderly patients compared to young patients. Diurnal fatigue and memory impairment were more observed in elderly patients. Asthma, hypothyroidism, diabetes, dyslipidemia, hypertension and atrial fibrillation were most commonly observed in elderly patients. Pauses in airflow and tonsillary hypertrophy were less observed in this group. There was no significant difference in OSAHS severity between the 2 groups. Logistic regression analysis showed that elderly apneic patients were more likely to be female, to have more memory impairment and to have more comorbidities with HTA, atrial fibrillation, diabetes and hypothyroidism. Conclusion: the frequency of cardiovascular, metabolic and cognitive comorbidities requires sleep investigation in apneic elderly subject, whether the clinical presentation is typical or not. [ABSTRACT FROM AUTHOR]

Ruhan Liu,1,2,* Chenyang Li,1,* Huajun Xu,1 Kejia Wu,1 Xinyi Li,1 Yupu Liu,1 Jie Yuan,1 Lili Meng,1 Jianyin Zou,1 Weijun Huang,1 Hongliang Yi,1 Bin Sheng,2 Jian Guan,1 Shankai Yin1 1Department of Otolaryngology Head and Neck Surgery and Shanghai Key Laboratory of Sleep Disordered Breathing & Otolaryngological Institute of Shanghai Jiao Tong University, Shanghai Jiao Tong University Affiliated Sixth People’s Hospital, Shanghai, People’s Republic of China; 2Department of Computer Science and Engineering, Shanghai Jiao Tong University, Shanghai, People’s Republic of China*These authors contributed equally to this workCorrespondence: Bin Sheng; Jian Guan, Tel +86 13124853285, Email shengbin@sjtu.edu.cn; guanjian0606@sina.comPurpose: Misdiagnosis and missed diagnosis of sleep-disordered breathing (SDB) is common because polysomnography (PSG) is time-consuming, expensive, and uncomfortable. The use of recording methods based on the oxygen saturation (SpO2) signals detected by wearable devices is impractical and inaccurate for extracting signal features and detecting apnoeic events. We propose a method to automatically detect the apnoea-based SpO2 signal segments and compute the apnoea–hypopnea index (AHI) for SDB screening and grading.Patients and Methods: First, apnoea-related desaturation segments in raw SpO2 signals were detected; global features were extracted from whole night signals. Then, the SpO2 signal segments and global features were fed into a bi-directional long short-term memory convolutional neural network model to identify apnoea-related and non-apnoea-related events. The apnoea-related segments were used to assess the AHI.Results: The model was trained on 500 individuals and tested on 8131 individuals from two public hospitals and one private centre. In the testing data, the classification accuracy for apnoea-related segments was 84.3%. Individuals with SDB (AHI 15) were identified with a mean accuracy of 88.95%.Conclusion: Using automatic SDB detection based on SpO2 signals can accurately screen for SDB.Keywords: sleep apnea hypopnea syndrome, AHI, SDB severity classification, Bi-LSTM-CNN, desaturation events

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Hypopnea refers to the state in which insufficient alveolar ventilation during night sleep decreases the respiratory airflow by more than 50% of the airflow. However, sleep apnea is a more serious respiratory event, such as complete cessation of respiratory airflow for 10 seconds. The occurrence of hypopnea is a precursor to the occurrence of apnea events and the two are closely connected. In this paper, we propose a method based on the combination of discrete wavelet transform and approximate entropy of EEG signals to detect sleep apnea and hypopnea events. For this purpose, first, data preprocessing is performed on the EEG record data set obtained from Tianjin Chest Hospital, and then infinite impulse response (IIR) Butterworth bandpass filter is used to decompose the data into delta, theta, alpha, beta and gamma. Second, descriptive features are extracted based on sub-bands discrete wavelet transform such as the approximate entropy of high-frequency coefficients. Third, the features are filtered based on Support Vector Machine (SVM) recursive elimination. Finally, several machine learning algorithms including SVM, K-Nearest Neighbor (KNN) and Random forest (RF) are employed to identify the occurrence of sleep hypopnea-apnea events. The highest accuracy rate reached 94.33%, the sensitivity reached 93.10%, and the specificity reached 95.07%. The obtained results validate that the proposed method is an effective and practical diagnostic method to detect the occurrence of hypopnea-apnea events.

This paper proposes a new perspective of analyzing non-linear acoustic characteristics of the snore sounds. According to the ERB (Equivalent Rectangular Bandwidth) scale used in psychoacoustics, the ERB correlation dimension (ECD) of the snore sound was computed to feature different severity levels of sleep apnea hypopnea syndrome (SAHS). For the training group of 93 subjects, snore episodes were manually segmented and the ECD parameters of the snores were extracted, which established the gaussian mixture models (GMM). The nocturnal snore sound of the testing group of another 120 subjects was tested to detect SAHS snores, thus estimating the apnea hypopnea index (AHI), which is called AHIECD. Compared to the AHIPSG value of the gold standard polysomnography (PSG) diagnosis, the estimated AHIECD achieved an accuracy of 87.5% in diagnosis the SAHS severity levels. The results suggest that the ECD vectors can be effective parameters for screening SAHS.

Objective To explore the influence of chronic intermittent hypoxia on hearing in children with obstructive sleep apnea hypopnea syndrome. Method PTA and DPOAE were recorded in 220 ears of children suffering from OSAHS and 60 ears of healthy children. The results were analyzed. Results There was nostatistical difference between the mild OSAHS group and the control group in PTA and single frequencies（P＞0.05）. There was statistical difference between the moderate and severe OSAHS group and the control group in PTA at 4 kHz and 8 kHz（P＜0.05）. There was no statistical difference between the mild OSAHS group and the control group in the amplitudes of DPOAE（P＞0.05）. There was statistical difference between the moderate and severe OSAHS group and the control group in the amplitudes of DPOAE at 6 kHz and 8 kHz（P＜0.05）.The high-frequency hearing loss of the moderate and severe OSAHS group was positively correlated with ODI（P＜0.05）and negatively correlated with LSaO2（P＜0.05），but had no significant correlation with AHI，MSaO2 and T90（P＞0.05）. Conclusion Chronic period hypoxia may be an independent factor influencing auditory function in childhood OSAHS.The degree and frequency of blood oxygen saturation decrease are closely related to the hearing impairment of OSAHS children. [ABSTRACT FROM AUTHOR]

Introduction: Obstructive sleep apnea/hypopnea (OSAH) affects more than 15% of the general population and increases the occurrence of cardiovascular (CV) and metabolic events. Continuous positive airway pressure (CPAP) treatment is currently the gold standard treatment of OSAH and could prevent the occurrence of such events. However, long-term adherence to CPAP is a problem where a significant rate stop device treatment use. OSAH patients suffering CV disease could be less compliant due to less diurnal symptoms.Methods: We performed a prospective study of 408 non-CV or CV disease patients suffering severe OSAH syndrome and followed them during the first 5 months as well as a mean of 3 years of CPAP treatment use.Results: We demonstrated that in adult OSAH patients that two variables were associated with a low compliance (

Introduction: Obstructive sleep apnea/hypopnea (OSAH) affects more than 15% of the general population and increases the occurrence of cardiovascular (CV) and metabolic events. Continuous positive airway pressure (CPAP) treatment is currently the gold standard treatment of OSAH and could prevent the occurrence of such events. However, long-term adherence to CPAP is a problem where a significant rate stop device treatment use. OSAH patients suffering CV disease could be less compliant due to less diurnal symptoms. Methods: We performed a prospective study of 408 non-CV or CV disease patients suffering severe OSAH syndrome and followed them during the first 5 months as well as a mean of 3 years of CPAP treatment use. Results: We demonstrated that in adult OSAH patients that two variables were associated with a low compliance (<5 h/night): age <60 y and lower maximal positive airway pressure level used. There was no significant impact of the presence of CV disease on compliance of 5 months. After 3 years of CPAP, age <60 y as well as diabetes were independent factors of low compliance. There was no significant association between gender, mask types, 90th centile positive airway pressure level, apnea/hypopnea index and short- or long-term compliance in our population. Conclusions: We did not find lower compliance of CPAP in CV OSAH patients. Most of our population (68–73%) demonstrated an optimal night treatment duration at 3 years of follow-up, allowing a reduction of CV occurrence or recurrence. We hypothesize that an early and short education of OSAH as we routinely proposed could allow a significant increase in the optimal observance of CPAP in at-risk populations. [ABSTRACT FROM AUTHOR]

Objective: This paper presents a methodology to automatically screen for sleep apnea based on the detection of apnea and hypopnea events in the blood oxygen saturation (SpO2) signal. Methods: It starts by detecting all desaturations in the SpO2 signal. From these desaturations, a total of 143 time-domain features are extracted. After feature selection, the six most discriminative features are used to construct classifiers to predict if desaturations are caused by respiratory events. From these, a random forest classifier yielded the best classification performance. The number of desaturations, classified as caused by respiratory events per hour of recording, can then be used as an estimate of the apnea-hypopnea index (AHI), and to predict whether or not a patient suffers from sleep apnea-hypopnea syndrome (SAHS). All classifiers were developed based on a subset of 500 subjects of the Sleep Heart Health Study (SHHS) and tested on three different datasets, containing 8052 subjects in total. Results: An averaged desaturation classification accuracy of 82.8% was achieved over the different test sets. Subjects having SAHS with an AHI greater than 15 can be detected with an average accuracy of 87.6%. Conclusion: The achieved SAHS screening outperforms SpO2 methods from the literature on the SHHS test dataset. Moreover, the robustness of the method was shown when tested on different independent test sets. Significance: These results show that an algorithm based on simple features of SpO2 desaturations can outperform more elaborate methods in the detection of apneic events and the screening of SAHS patients. [ABSTRACT FROM AUTHOR]

Abstract Background Polysomnography (PSG) is the gold standard for diagnosing obstructive sleep apnea (OSA). However, it is time-consuming, expensive and requires technical expertise. Thus, a number of alternatives to PSG have been proposed. The present study was conducted to analyse the sensitivity, specificity and accuracy of night oximetry as a diagnostic tool in patients suspected to have sleep apnea hypopnea syndrome (SAHS), and to reduce the number of saved PSGs. Patients and methods In total, 40 middle-aged patients clinically suspected to haveObstructive Sleep Apnea Hypopnea Syndrome (OSAHS) were included in the study. They were classified into two groups: group I (the SAHS group), comprising 33patientswithapneahypopneaindex greater than or equal to5; and group II (the non-SAHS group), comprising seven patients with apnea hypopnea index l than 5. All patients were subjected to the following: (a) OSA screening questionnaire; (b) BMI in kg/m2, neck circumference in cm, and cardiac, chest and ENT examinations; (c) investigationintheform of arterialbloodgases, chest radiograph, ECG and spirometry; and (d) full PSG and overnight oximetry, which were carried out simultaneously. Results The baseline values of O2 saturation derived from PSG and oximetry were 93.33±2.32 and 91.50±2.79, respectively. The overnight oxygen desaturation index of oximetry was significantly lower in the SAHS group. Minimal SpO2 of PSG was significantly lower in the SAHS group. The best predicted cutoff value of overnight pulse oximetry using oxygen desaturation index for mild to moderate OSA patient diagnosis was 14.78, with 87.88% sensitivity and 88.71% specificity. However, the optimal cutoff value for severe OSA diagnosis was 52.55, with 86.67% sensitivity and 96% specificity. Conclusion Overnight pulse oximetry may be considered a diagnostic tool in patients suspected to have SAHS, with excellent diagnostic sensitivity, specificity and accuracy, which increased with severity.

Objective To measure the upper airway of obstructive sleep apnea hypopnea syndrome by 256 slice spiril CT, and to access the airway obstruction plane with the airway plane data in OSAHS patients. Through these measurements, we can provide assistance for clinical diagnosis and treatment. Methods This study randomly selected 178 patients diagnosed with OSAHS and 110 cases non-snoring healthy people as the control group by the Philips 256 slice CT. Under the nasopharyngeal area, velopharyngeal area, glossopharyngeal area,epiglottis area, we measured the cross-sectional area and volume of the narrowest plane in the two groups of quiet respiration and Müller status. Results The OSAHS group underwent quiet respiration and Müller status during CT scanning, and the two states about epiglottis area in cross-sectional area and volume had no significant difference, Other groups had differences between the parameters. There was a significant difference in the volume about velopharyngeal area and glossopharyngeal area. In the control group undergoing quiet respiration and Müller status during CT scanning, there was difference in velopharyngeal cross-sectional area. Other parameters had no significant difference. Conclusions The obstruction plate of OSAHS patients with 256-slice spiril CT measurement is mostly in the velopharyngeal area and glossopharyngeal area. The volume measurement of upper airway by CT can predict airway obstruction plate in patients with OSAHS. [ABSTRACT FROM AUTHOR]

Introduction: obstructive sleep apnea hypopnea syndrome (OSAHS) is a common but often under diagnosed disease among elderly persons. The aim of our study was to determine the clinical and polygraphic characteristics of OSAHS in elderly by comparing them to younger patients., Methods: a retrospective study was performed at Pavillon D pneumology at Abderrahmen Mami Hospital in Ariana including 222 patients with OSAHS, divided into two groups: group 1 including 72 patients aged 18 to 45 years and Group 2 including 150 patients aged 65 and over. Clinical and polygraphic data was collected., Results: elderly patients were more female, less exposed to tobacco but more exposed to biomass smoke. The average consultation time was significantly longer for elderly patients compared to young patients. Diurnal fatigue and memory impairment were more observed in elderly patients. Asthma, hypothyroidism, diabetes, dyslipidemia, hypertension and atrial fibrillation were most commonly observed in elderly patients. Pauses in airflow and tonsillary hypertrophy were less observed in this group. There was no significant difference in OSAHS severity between the 2 groups. Logistic regression analysis showed that elderly apneic patients were more likely to be female, to have more memory impairment and to have more comorbidities with HTA, atrial fibrillation, diabetes and hypothyroidism., Conclusion: the frequency of cardiovascular, metabolic and cognitive comorbidities requires sleep investigation in apneic elderly subject, whether the clinical presentation is typical or not., Competing Interests: Les auteurs ne déclarent aucun conflit d´intérêts., (Copyright: Imen Sahnoun et al.)

Objective To provide an comprehensive evaluation of the correlation between sleep apnea hypopnea syndrome (SAHS) and nonalcoholic fatty liver disease (NAFLD). Methods The various case-control studies on the relationship between SAHS and NAFLD were retrieved from all kinds of large-scale databases at home and abroad (including Web of science, EMbase, Pubmed, Springer Link, EBSCO Databases, CNKI, CQVIP, Wanfang Data). The quality evaluation of included studies was made by two independent researchers. RevMan 5.1 and stata 12.0 software were used for meta-analysis. Results A total of 11 qualified documents were included in this study. Meta analysis showed that the relative risk of NAFLD was increased in SAHS patients than non-SAHS patients (RR=2.82, 95%CI:2.03-3.92, P<0.01). The serum alanine aminotransferase (ALT) increased in SAHS patients (SMD=0.53, 95% CI:0.02-1.05, P < 0.05). Compared with non-SAHS patients, the apnea-hypopnea index (AHI) was significantly higher in SAHS patients combined with severe NAFLD than those combined with mild NAFLD (SMD=1.42, 95%CI:0.12-2.72, P < 0.05). Conclusion The risk of NAFLD in?creases in SAHS patients. The severity of NAFLD is relatively higher with the severity of intermittent hypoxia. [ABSTRACT FROM AUTHOR]

This study is aimed at assessing the usefulness of different feature selection and classification methodologies in the context of sleep apnea hypopnea syndrome (SAHS) detection. Feature extraction, selection and classification stages were applied to analyze blood oxygen saturation (Sa02) recordings in order to simplify polysomnography (PSG), the gold standard diagnostic methodology for SAHS. Statistical, spectral and nonlinear measures were computed to compose the initial feature set. Principal component analysis (PCA), forward stepwise feature selection (FSFS) and genetic algorithms (GAs) were applied to select feature subsets. Fisher's linear discriminant (FLD), logistic regression (LR) and support vector machines (SVMs) were applied in the classification stage. Optimum classification algorithms from each combination of these feature selection and classification approaches were prospectively validated on datasets from two independent sleep units. FSFS + LR achieved the highest diagnosticperformance using a small feature subset (4 features), reaching 83.2% accuracy in the validation set and 88.7% accuracy in the test set. Similarly, GAs + SVM also achieved high generalization capability using a small number of input features (7 features), with 84.2% accuracy on the validation set and 84.5% accuracy in the test set. Our results suggest that reduced subsets of complementary features (25% to 50% of total features) and classifiers with high generalization ability could provide high-performance screening tools in the context of SAHS. [ABSTRACT FROM AUTHOR]

• Designing LSTM network structure to process time series information. • Using a variety of audio features to synthesize information to identify snoring. • Multi contrast experiments under a large amount of data, the network has high performance. Obstructive sleep apnea hypopnea syndrome (OSAHS) is a high incidence disease with serious hazard and potential danger. The polysomnography(PSG) has become the gold standard to diagnose OSAHS. However, the PSG is limited for household use because of its operational complexity, technical nature and high consumption.Currently, Microphone, as a non-contacting tensor, is an alternative method. And researchers devoted to analyze respiratory sound for detecting and evaluating OSAHS patients. In this paper, a classifier based on Long Short-Term Memory (LSTM) is proposed to identify the respiratory event-related snoring from simple snoring. Firstly, we collected the sleep sound of 33 patients and 10 normal people from the hospital. And 4780 abnormal snoring segments and 10,740 normal snoring segments were recorded by Mics. Then Mel-frequency cepstrum coefficients(MFCC), Mel Filter Banks (Fbanks), Short-time Energy and Linear Prediction Coefficient(LPC), representing the different characteristics of snoring, are extracted as characteristic features of snoring.At last, a multi-input model based on LSTM is designed, which can receive various audio features to synthesize information to identify snoring. Compared with single feature network processing, the use of multiple feature coefficients can identify the features of snoring at a fine-grained level. In the experiment, our method could classify respiratory event related snoring and normal snoring at accuracy 95.3%, and the accuracy of the three-category snore related to the severity of OSAHS can reach 81.6%. The recognition results can be used for the auxiliary diagnosis of OSAHS. [ABSTRACT FROM AUTHOR]

Introduction: We have previously shown that plasma levels of orexin-A, a neuropeptide with an arousal-stimulating action, were decreased in parallel with the severity of the disease in patients with obstructive sleep apnea-hypopnea syndrome (OSAHS). Objective: To clarify the effects of nasal continuous positive airway pressure (nCPAP) treatment on plasma orexin-A levels in patients with this syndrome. Method: Sleep tests and blood sample collections were conducted at the sleep-related respiratory disorders clinic and the sleep laboratory of the Iwate Medical University Hospital. We studied 27 patients with OSAHS (apnea-hypopnea index [AHI], ≥ 20 by polysomnography) who were treated with nCPAP for 3 to 6 months. These patients were divided into the following two groups according to the arousal index (AI): group A (n = 11), ≥ 60; group B (n = 16), < 60. Plasma samples were obtained before and after the nCPAP treatment for 3 to 6 months. Plasma immunoreactive (IR)-orexin-A concentrations were measured by radioimmunoassay after the extraction using cartridges. Results: Plasma IR-orexin-A concentrations were inversely correlated with the AI (r = -0.807; p 7lt; 0.0001) and AHI (r = -0.661; p < 0.0001) in 27 patients before the nCPAP treatment. Mean (± SEM) plasma IR-orexin-A concentrations were significantly lower in group A (1.0 ± 0.3 pmol/L) than in group B (4.6 ± 0.4 pmol/L). Mean plasma IR-orexin-A concentrations were significantly increased after the nCPAP treatment in group A (to 3.4 ± 1.2 pmol/L; p = 0.0069), whereas they were not significantly changed in group B. The increases in plasma IR-orexin-A concentrations after the nCPAP treatment were in parallel with the improvements in AI and Epworth sleepiness scale (a marker of severity of daytime excessive sleepiness) score in group A. Conclusions: The low plasma orexin-A levels were increased by the nCPAP treatment in patients with severe OSAHS, suggesting that orexin-A is a plasma marker that reflects the severity of OSAHS and the response to treatment. [ABSTRACT FROM AUTHOR]

Study objectives: Auto-continuous positive airway pressure (CPA]?) has been reported to have no more efficacy than constant CPAP in unselected patients with sleep apnea hypopnea syndrome (SAHS). The aim of this study was to evaluate patients judged to be good candidates for auto-CPAP because of a high within-night variability in pressure requirement. Design: Single-blind, randomized, cross-over study (2 x 8 weeks) to compare auto-CPA]? with constant C PAP. Patients: Outpatients with moderate-to-severe SAHS attending the chest clinic. Interventions: Patients were equipped at home in the auto-CPAP mode (model GK418A; Malinckrodt; Nancy, France), using a 4- to 14-cm H20 pressure range. Those individuals having a high within-night variability in pressure requirement, assessed at the end of a 14-day run-in period, were included in the cross-over study. Auto-CPAP was compared with constant CPA]? (according to a titration night in the sleep laboratory) in terms of compliance, efficacy on apneas (assessed from the pressure monitor), and sleepiness (assessed on the Epworth sleepiness scale). Measurements and results: Of 90 consecutive patients with SAHS, 27 patients were selected for a within-night variability in pressure requirement exceeding a given threshold. After completion of the cross-over, 24 patients were evaluable. The median percentage of nights the machine was used was 95.5% (range, 45 to 100%) on constant CPAP, and 96.5% (range, 40 to 100%) on auto-CPAP; the median apnea index recorded by the device was 0.40/h (range, 0 to 2.40/h) on constant CPA]?, and 0.45/h (range, 0 to 5.80/h) on auto-CPAP (differences not significant). The mean Epworth sleepiness score was significantly (p < 0.01) lower on auto-CPA]? (5.1; SD, 2.8) than on constant CPA]? (6.1; SD, 2.8). Conclusions: In patients selected for a high within-night variability in pressure requirement, auto-CPAP administered via a GK418A device was equivalent to constant CPAP based on a titration night in the sleep laboratory. Subjective ratings for sleepiness were slightly lower on auto-CPAP. (CHEST 2004; 126:31-37,) [ABSTRACT FROM AUTHOR]

• Symbolic transfer entropy quantified cortical effective connectivity during sleep. • Posterior-to-anterior pattern of information flow was compared between groups. • Abnormal cortical effective connectivity in SAHS patients was characterized. • Posterior-to-anterior features got a good result in SAHS severities classification. • Cortical effective connectivity may perform as EEG biomarkers in SAHS diagnosis. Sleep apnea hypopnea syndrome (SAHS) is a prevalent sleep breathing disorder that can lead to brain damage and is also a risk factor for cognitive impairment and some common diseases. Studies on cortical effective connectivity (EC) during sleep may provide more direct and pathological information and shed new light on brain dysfunction due to SAHS. However, the EC is rarely explored in SAHS patients, especially during different sleep stages. To this end, six-channel EEG signals of 43 SAHS patients and 41 healthy participants were recorded by whole-night polysomnography (PSG). The symbolic transfer entropy (STE) was applied to measure the EC between cortical regions in different frequency bands. Posterior-anterior ratio (PA) was employed to evaluate the posterior-to-anterior pattern of information flow based on overall cortical EC. The statistical characteristics of the STE and PA and of the intra-individual normalized parameters (STE* and PA*) were served as different feature sets for classifying the severity of SAHS. Although the patterns of STE across electrodes were similar, significant differences were found between the patient and the control groups. The variation trends across stages in the PA were also different in multiple frequency bands between groups. Important features extracted from the STE* and PA* were distributed in multiple rhythms, mainly in δ, α, and γ. The PA* feature set gave the best results, with accuracies of 98.8% and 83.3% for SAHS diagnosis (binary) and severity classification (four-way). These results suggest that modifications in cortical EC were existed in SAHS patients during sleep, which may help characterize cortical abnormality in patients. [ABSTRACT FROM AUTHOR]

Objective . Sleep apnea hypopnea syndrome (SAHS) induces abnormalities in brain function. This study aims to find features that can characterize the impact of SAHS on the brain functional connectivity (FC) during sleep. Approach . Seventy-eight participants (39 SAHS patients and 39 age-matched healthy controls) were recruited and underwent a whole night of polysomnography. The improved weighted phase lag index algorithm was utilized to evaluate FC in δ , θ , α , β , and γ bands of six EEG channels. The regional FC features were further constructed to characterize the asymmetries of FC between the left and right hemispheres, the imbalances of FC between the inter- and intra-hemispheres, and those between the anterior and posterior cortex, respectively. Then, support vector machines and feature evaluation were used to verify the discriminative ability for the abnormal FC in SAHS patients of the above-mentioned features. Main results. The study observed abnormal FC changes in SAHS patients during sleep in multiple frequency bands. Moreover, regional FC features performed better in SAHS screening, and important features were mainly distributed in β and γ bands. Significance . Our research exhibited the abnormal regional FC in SAHS patients during sleep, which provided new insights and established indicators to investigate the changes of brain function in patients., (© 2021 Institute of Physics and Engineering in Medicine.)

Introduction: Sleep apnea/hypopnea syndrome (SAHS) can change brain structure and function. These alterations are related to respiratory event-induced abnormal sleep, however, how brain activity changes during these events is less well understood., Methods: To study information content and interaction among various cortical regions, we analyzed the variations of permutation entropy (PeEn) and symbolic transfer entropy (STE) of electroencephalography (EEG) activity during respiratory events. In this study, 57 patients with moderate SAHS were enrolled, including 2804 respiratory events. The events terminated with cortical arousal were independently researched., Results: PeEn and STE were lower during apnea/hypopnea, and most of the brain interaction was higher after apnea/hypopnea termination than that before apnea in N2 stage. As indicated by STE, the respiratory events also affected the stability of information transmission mode. In N1, N2, and rapid eye movement (REM) stages, the information flow direction was posterior-to-anterior, but the anterior-to-posterior increased relatively during apnea/hypopnea. The above EEG activity trends maintained in events with cortical arousal., Conclusions: These results may be related to the intermittent hypoxia during apnea and the cortical response. Furthermore, increased frontal information outflow, which was related to the compensatory activation of frontal neurons, may associate with cognitive function.