不同年龄及状态下儿童脑电复杂度的特征

目的：应用非线性分析方法，研究儿童在不同年龄和不同生理状态下脑电复杂度的变化特征。方法：对45例健康状态基本正常的0～15岁儿童进行16导脑电连续24h监测，分析清醒睁眼、闭眼、NREM(非快速眼动期)睡眠Ⅰ～Ⅱ期(浅睡期)、Ⅲ～Ⅳ期(深睡期)及REM(眼速动期)睡眠共7种状态的脑电复杂度特征，并对复杂度与年龄的相关性进行分析。结果：(1)全脑复杂度在睁眼状态大于闭眼状态，清醒状态大于睡眠期。NREM睡眠期随睡眠深度增加，复杂度逐渐减低。REM期复杂度高于深睡期，但低于清醒期。(2)全脑平均脑电复杂度在睁眼、闭眼及浅睡期与年龄呈正相关，在深睡期及REM期与年龄无明显相关性。(3)在清醒闭眼状态下各脑区脑电复杂度与年龄均呈正相关，睁眼及浅睡期则以旁中线区复杂度与年龄有较好的相关性。结论：复杂度可用于研究不同生理状态下的脑动力学特征及脑电活动与脑发育的关系，可作为评价脑功能状态及脑发育水平的一个客观指标。     

Anteroposterior Difference in EEG Sleep Depth Measure is Reduced in Apnea Patients

In the present work, mean frequencies of FFT amplitude spectra from six EEG derivations were used to provide a frontopolar, a central and an occipital sleep depth measure. Parameters quantifying the anteroposterior differences in these three sleep depth measures during the night were also developed. The method was applied to analysis of 30 all-night recordings from 15 healthy control subjects and 15 apnea patients. Control subjects showed larger differences in sleep depth between frontopolar and central positions than the apnea patients. The relatively reduced frontal sleep depth in apnea patients might reflect the disruption of the dynamic sleep process caused by apneas.     

放松训练对大学生失眠患者情绪和脑功能的影响

目的 探讨放松训练对大学生失眠患者情绪及脑功能的影响.方法 采用匹兹堡睡眠质量指数量表对大学生睡眠质量进行抽样调查.选取30名有睡眠障碍的大学生进行放松训练(瑜伽功)8周,应用焦虑自评量表(self-rating anxiety scale,SAS)、觉醒及睡眠脑电比较训练前后失眠患者情绪及脑功能的改变.结果 放松训练后受试者SAS得分降低,与训练前比较差异有显著性.治疗后觉醒期患者α波增加,β波下降,α波分布正常,电压增高.睡眠期睡眠潜伏期减少,总睡眠时间延长,觉醒时间减少,觉醒次数减少,睡眠效率提高,动眼睡眠时间延长,非动眼睡眠3、4期时间延长.结论 放松训练可以改善大学生焦虑状况,改善睡眠进程及睡眠结构,恢复、提高脑功能.     

阻塞性睡眠呼吸暂停患者夜间自主神经功能与血压变化的关系

目的：明确阻塞性睡眠呼吸暂停综合征（OSAS）患者夜间自主神经功能状况及与血压变化的关系。方法：12例OSAS患者在桡动脉内留置导管监测血压并同步进行夜间多导睡眠仪连续记录，白天用心率功率谱分析法分析患者及20名健康对照者清醒及不同睡眠期自主神经功能状况。结果：病例组夜间清醒时低频／高频（LF／HF）、非快动眼睡眠（NREM）期LF、极低频（VLF）、LF／HF和液间平均LF、VLF、LF／HF较对照组明显增高；OSAS患者夜间清醒及不同睡眠期的血压变化部分指标与夜间平均LF、VLF组分呈正相关，与夜间平衡LF／HF无相关性。结论：OSAS患者夜间清醒和睡眠时均存在交感－－迷走神经不平衡，夜间自主神经功能状态以交感神经活性增高为主；OSAS患者夜间血压变化与自主神经功能状态异常有关。     

发作间期癫痫患者自然睡眠脑电图与常规清醒脑电图的对比分析

目的探讨自然睡眠脑电图（EEG）对发作间期癫痫患者的诊断价值。方法选取2011年4月～2012年2月浙江省东阳市人民医院的73例发作间期癫痫患者、25例间歇期晕厥患者、19例间歇期偏头痛患者、31例发作间期短暂性脑缺血发作患者作为研究对象,分别在自然睡眠状态下、常规清醒状态下对上述研究对象进行EEG检查,比较其灵敏度和特异度。结果自然睡眠EEG诊断发作间期癫痫患者的灵敏度、特异度分别为75.3%、100.0%。常规清醒EEG诊断发作间期癫痫患者的灵敏度、特异度分别为31.5%、100.0%。自然睡眠EEG诊断发作间期癫痫患者的灵敏度显著高于常规清醒EEG（P〈0.05）,两种EEG诊断发作间期癫痫患者的特异度相比差异无统计学意义（P〉0.05）。结论与常规清醒EEG相比,自然睡眠EEG诊断发作间期癫痫的灵敏度较高,有利于降低癫痫患者的漏诊率。     

Artificial Neural Network and Wavelet Based Automated Detection of Sleep Spindles, REM Sleep and Wake States

Backpropagation artificial neural network (ANN) has been designed to classify sleep–wake stages. Four hours continuous three channel polygraphic signals such as EEG (electroencephalogram), EOG (electrooculogram) and EMG (electromyogram) from conscious subjects were digitally recorded and stored in computer. EOG and EMG signals were used for manual identification of sleep states before training and testing of ANN. The percentages power of the 2 s epochs of the digitized EEG signals from each of three sleep–wake patterns, sleep spindles (SS), rapid eye movement (REM) sleep and awake (AWA) sates, were calculated and analyzed to select the manually confirmed sleep–wake states for each epoch. Further, second order Daubechies mother wavelet has been used to get the wavelet coefficients for the selected EEG epochs. The wavelet coefficients for the EEG epochs (64 data) were selected as inputs for the training the network and to classify SS, REM sleep and AWA stages. The ANN architecture used (64–14–3) in present study shows overall very good agreement with manual sleep stage scoring with an average of 95.35% for all the 1,140 samples tested from SS, REM and AWA stages. This architecture of ANN was also found effectively differentiating the EEG power spectra from different sleep–wake states (96.84% in SS, 93.68% in REM sleep, 95.52% in AWA state). The high performance observed with the system based on wavelet coefficients along with the ANN, highlights the need of this computational tool into the field of sleep research. Certificate of Originality  This is to certify that the article submitted for publication in Journal of Medical Systems has not been published, nor is being considered for publication, elsewhere.     

Computer Based Synchronization Analysis on Sleep EEG in Insomnia

Inter-hemispheric sleep EEG coherence is studied in 10 subjects with psycho physiological insomnia, in 10 with paradoxical insomnia, and in 10 matched controls through different states of the sleep/wakefulness cycle. Inter hemispheric EEG coherence between central electrode pairs are compared to each other within these groups. A linear measure called as Coherence Function (CF) and a nonlinear measure called as Mutual Information (MI) are performed by using the Information Theory Toolbox in the present sleep EEG synchronization study. Regarding as tests, for all-night EEG recordings of participants, both measures indicate higher degree of EEG coherence for insomnia than for controls. The results further validate inter-hemispheric CF as a sign of activity in insomnia where the EEG series from stage2, REM sleep and the eyes closed waking state. In particular, the CF is found to be more useful tool than the MI for detection of insomnia when the power spectral density estimations of sleep stages are provided by the Burg Method. In conclusion, the CF provides insights into functional connectivity of brain regions during sleep. Since the CF has a characteristic shape for sleep states, it can be proposed to identify the degree of EEG complexity depending on sleep disorders.     

基于睡眠脑电信号和深度学习的抑郁症识别研究

目的 基于睡眠脑电信号,探索深度学习Vision Transformer(ViT)结合Transformer网络对抑郁症患者识别的有效性。方法 首先对28例抑郁症患者和37例正常对照的睡眠脑电信号进行预处理,并将信号转为图像格式,保留其频域及空间域特征信息,之后将图像输送到ViT-Transformer编码网络,分别学习抑郁症患者和正常对照的快速眼动（rapid eye movement, REM）睡眠期和非快速眼动（non-rapid eye movement, NREM）睡眠期的脑电信号特征,并对抑郁症进行识别。结果 基于ViT-Transformer网络,从不同脑电频率角度,发现delta、theta和beta波的组合对抑郁症识别具有比较好的结果。其中,REM期delta-theta-beta波组合的脑电信号特征对抑郁症识别的准确率达92.8%,精准率为93.8%,抑郁症患者的召回率为84.7%,F0.5值为0.917±0.074;NREM期delta-theta-beta波组合的脑电信号特征对抑郁症的识别准确率为91.7%,精准率为90.8%,召回率为85.2%,F0.5值为0...     

Normal breathing during sleep at an altitude of 2240 meters

BACKGROUND: Mexico City is located at an altitude of 2240 meters (m) above sea level with a mean barometric pressure of 585 mmHg. Normal PaO2 and PaCO2 values in young subjects are 67 and 31 mmHg, respectively. Sleep desaturation, present in normal subjects at sea level, may be more frequent and severe at moderate altitudes. Our objective was to describe breathing during sleep in normal residents at an altitude of 2240 m above sea level. METHODS: Non-obese, long-term residents of Mexico City with normal pulmonary function and without sleep-related symptoms completed a nocturnal polysomnogram. RESULTS: A total of 23 subjects (12 males and 11 females) were studied. Mean age was 45 years (range 20-76 years). Seven subjects (four >60 years of age) presented sleep-disordered breathing (SDB) with apnea-hypopnea index >or=5 h(-1). Mean SaO2 during sleep was 93 +/- 2% and in all subjects was >or=90%. Five subjects without SDB monitored for PO2 tc maintained values of PO2 tc <60 mmHg during one half of the night. During sleep, mean PCO2et was 35 +/- 3 mmHg, breathing frequency 16 +/- 3, and heart rate 65 +/- 9. These values were maintained throughout sleep stages. CONCLUSIONS: Normal long-term residents of Mexico City had slightly lower mean oxygen saturation than that at sea level but >or=90% saturation and experienced transient desaturations. Breathing frequency and heart rate were similar to residents at sea level.     

慢性失眠患者的睡眠脑电功率特征

目的 探讨慢性失眠患者的睡眠脑电功率特征.方法 回顾性分析符合ICD-10慢性失眠诊断标准并完成整夜多导睡眠监测(PSG)患者的睡眠脑电资料.比较失眠组和对照组睡眠结构及不同睡眠分期相对脑电功率特征的差异,并进一步分析脑电功率值与不同PSG指标的相关性.结果 共计纳入45例研究对象,其中失眠患者25例(女性18例),年...     

阻塞性睡眠呼吸暂停低通气综合征患者睡眠前后鼓室压与耳声发射变化的特点

目的：观察 OSAHS 患者睡眠前后鼓室压及耳声发射各频率幅值的变化，探讨 OSAHS 患者鼓室压变化对内耳听觉的影响。方法：选择2014年10月2015年10月在我院住院的 OSAHS 患者31例（62耳）和正常对照组31例（62耳），分别在睡眠前后对两组行瞬态诱发性耳声发射（TEOAE）、畸变产物耳声发射（DPOAE）及声导抗检查。结果：OSAHS 组醒后鼓室压向负压移动，差异有统计学意义，静态声顺值、鼓室宽度变化无统计学意义，在500Hz 8000Hz 频率范围内 TEOAE 各频率段幅值下降，差异有统计学意义，DPOAE 各频率幅值下降，差异有统计学意义；而正常对照组睡眠前后鼓室压、静态声顺值、鼓室宽度变化无统计学意义，TEOAE 及 DPOAE 各频率幅值变化无统计学意义。结论：推测 OSAHS 患者中耳鼓室压向负压移动可导致内耳听觉的损害。     

Application of Classical and Model-Based Spectral Methods to Describe the State of Alertness in EEG

Electrophysiological recordings are considered a reliable method of assessing a person's alertness. Sleep medicine is asked to offer objective methods to measure daytime alertness, tiredness and sleepiness. In this study, EEG signals recorded from 30 subjects were processed by PC-computer using classical and model-based methods. The classical method (fast Fourier transform) and three model-based methods (Burg autoregresse, moving average, least-squares modified Yule–Walker autoregressive moving average methods) were selected for processing EEG signals to discriminate the alertness level of subject. Power spectra of EEG signals were obtained by using these spectrum analysis techniques. These EEG spectra were then used to compare the applied methods in terms of their frequency resolution and the effects in determination of vigilance state of subject. It is found that, FFT and MA methods have low spectral resolution, these two methods are not appropriate for the analysis of the a wake–sleep correlation. Burg AR and least-squares modified Yule–Walker ARMA methods' performance characteristics have been found extremely valuable for the determination of vigilance state of a healthy subject, because of their clear spectra.     

伴中央颞区棘波的儿童良性癫痫的临床与脑电图特征

目的 探讨伴中央颞区棘波放电的BECT的临床及脑电图特征。方法 对46例BECT患者的临床及EEG资料进行分析。结果 本组发病年龄为2.5～12.5岁,31例发作与睡眠密切相关,8例于睡眠和觉醒时均有发作,24例表现为部分性发作,13例为部分性发作继发全身性发作,发作间期脑电图均有一侧或双侧中央和（或）中颞区尖波或棘波,清醒脑电图阳性率32.60%,睡眠脑电图阳性率84.78%。结论 BECT是与年龄相关的癫痫综合征,认识其临床和EEG演变的特点及规律,可提高对BECT的诊断率。     

阻塞性睡眠呼吸暂停低通气综合症对睡眠结构及睡眠期血氧饱和度的影响

目的:探索不同程度阻塞性睡眠呼吸暂停低通气综合征(OSAHS)患者之间的呼吸障碍的差异以及连续血氧饱和度(SaO2)检测是否对阻塞性睡眠呼吸暂停低通气综合征(OSAHS)有诊断价值。方法:对259例鼾症患者进行多导睡眠图(PSG)的检测,分为单纯鼾症、轻、中、重度OSAHS共4组,收集资料并分析。结果:OSAHS组的体重、BM I均显著高于单纯鼾症组(P均<0.05)与单纯鼾症患者比较,OSAHS患者的浅睡眠%增加、深睡眠%减少,差异显著(P均<0.05)。在所有的鼾症患者中,BM I与睡眠呼吸暂停低通气指数(AH I)呈显著正相关(R=0.45;P=0.000);各OSAHS组SaO2的基础值和最低值均小于单纯鼾症组(P均<0.05);所有患者的SaO2的基础值与AH I呈显著负相关(R=-0.66,P<0.05);若以SaO2基础值<94%和SaO2<85%作为诊断OSAHS的标准,敏感性分别是67.11%和7.67%;特异性分别是100%和97.06%。结论:在单纯鼾症和OSAHS之间存在体重、BM I的显著差异,BM I与AH I显著正相关;OSAHS患者的浅睡眠比单纯鼾症患者明显增加。OSAHS患者存在睡眠时SaO2下降,并与疾病的严重程度有关;连续检测SaO2是在鼾症患者中鉴别出OSAHS的一个有效的简易方法。     

伴中央颞区棘波的儿童良性癫痫的临床与脑电图特征

目的探讨伴中央颞区棘波放电的BECT的临床及脑电图特征。方法对46例BECT患者的临床及EEG资料进行分析。结果本组发病年龄为2.5～12.5岁,31例发作与睡眠密切相关,8例于睡眠和觉醒时均有发作,24例表现为部分性发作,13例为部分性发作继发全身性发作,发作间期脑电图均有一侧或双侧中央和(或)中颞区尖波或棘波,清醒脑电图阳性率32.60%,睡眠脑电图阳性率84.78%。结论BECT是与年龄相关的癫痫综合征,认识其临床和EEG演变的特点及规律,可提高对BECT的诊断率。     

儿童额叶癫痫临床和长程视频脑电图特征

目的通过对46例儿童额叶癫痫患儿的临床表现、长程视频脑电图（VEEG）特点进行分析,提高对儿童额叶癫痫的认识。方法收集2008年12月至2014年8月儿科门诊及住院确诊的46例儿童额叶癫痫病例的资料,回顾性分析其临床表现、VEEG及神经影像学等特征。结果本组患儿发病年龄最小11个月,最大15岁。46例患儿共监测到临床发作258次,明确临床发作34例,14.7%仅于清醒期发作,61.8%仅在睡眠期发作,23.5%在清醒、睡眠中均有发作;临床发作形式包括额叶失神、局部阵挛发作、偏转性强直、姿势性强直、过度运动性自动症、口咽自动症、发声、发笑发作、临床下放电和自主神经性发作等。73.9%患儿记录到发作间期额叶为主的癫痫样放电,63.0%患儿记录到发作期额叶为主的癫痫样放电。结论儿童额叶癫痫临床发作频繁、短暂,以睡眠期发作为主,临床表现复杂多样,易漏诊;长程VEEG可监测到儿童额叶癫痫发作期临床及异常脑电图表现,可提供明确诊断率。     

伴中央颞部棘波的良性儿童癫痫脑电图分析

目的分析脑电图（EEG）在伴中央颞部棘波的良性儿童癫痫（BECCT）的诊断意义。方法对72例BECCT的EEG及临床资料进行回顾性分析。结果清醒时,EEG正常54例,异常18例（含8例不典型局灶性放电）,对清醒时EEG正常54例均进行睡眠EEG描记．则均于中央颞部出现棘、尖波。结论睡眠EEG大大提高了BECCT的诊断率,EEG为诊断BECCT的根本依据：认识BECCT的EEG及临床特点,有利于BECCT的诊断及预后评估。     

具有中央颞区棘波的良性儿童癫痫46例分析

目的总结具有中央-颞区棘波放电的儿童良性癫痫（BECCT）的临床特点及脑电图特征.方法对46例BECCT的患者进行分析,包括家族史、热性惊厥史、临床表现、脑电图变化及治疗效果预后情况.结果起病年龄3.2～12.8岁,35例患儿在5～10岁（35/46,76.09%）.有家族史8例（17.4%）,热性惊厥史6例（13.04%）,发作和睡眠密切相关者37例（37/46,80.43%）.部分性发作36例（36/46,78.26%）,强直-阵挛发作6例（6/4613.04%）.发作间期脑电图可见一侧或双侧中央和/或中颞区有尖波或棘波发放.清醒脑电图阳性率25例（54.35%）,睡眠脑电图阳性率42例（91.3%）.绝大多数患儿应用抗癫痫药物（AEDs）治疗疗效满意,占43例（93.45%）.结论 BECCT早期准确的诊断有助于治疗和判断预后,从而减轻患儿及家庭的负担.     

闸北区某社区精神病患者失眠原因分析

目的：分析导致社区精神病患者失眠的相关因素，制定相应的管理措施，为社区精神病患者失眠的防治和护理提供参考依据。方法：在本社区居家康复的精神病患者中选取200例失眠症患者，对患者进行电话随访与上门随访，通过与患者及其亲友深入交流和沟通，了解总体情况、病情状况、药剂用量。并为患者建立个人信息档案，细致登记随访结果信息表格，对随访结果资料进行全面梳理与总结，并分析影响睡眠的相关因素。结果：难以入睡70例（35％），早醒64例（32％），时睡时醒9例（4．5％），彻夜不眠15例（7．5％）；失眠症与精神状况、社会因素、环境因素、心理因素、身体情况、药物不良反应等因素相关。结论：控制精神症状，消除疼痛和药物不良反应，加强心理疏导，创造良好的睡眠环境，培养良好的睡眠习惯是控制失眠的有效措施。做好社区精神病患者的睡眠状况监测，可防止意外的发生，保证治疗的顺利进行。