Swarnkar V, Abeyratne Udantha R, Hukins C
School of Information Technology and Electrical Engineering, The University of Queensland, Brisbane, Qld 4072, Australia.
Physiol Meas. 2007 Aug;28(8):869-80. doi: 10.1088/0967-3334/28/8/010. Epub 2007 Jul 19.
Sleep apnoea hypopnea syndrome (SAHS) is a serious sleep disorder affecting a large percentage of the population. Apnoea/hypopnea and electroencephalographic-arousal (EEGA) events occur frequently in SAHS patients. These events significantly disturb the sleep architecture, as revealed through nocturnal EEG signals. Even though EEG carries vital information on the state of the brain, its use in clinical SAHS diagnosis is limited mainly to routine sleep staging. In this paper, we address this issue. We propose a novel measure, called the inter-hemispheric asynchrony (Psi(a-->b)), to capture EEG-symmetry changes associated with a transition a --> b between the brain states 'a' and 'b'. Our work takes into account macro-states such as the traditional sleep stages, and micro-states such as EEGA and apnoea/hypopnea events. We measured EEG data using electrodes C4-A2 and C3-A1 of the International 10/20 System from 18 subjects undergoing polysomnography (PSG) testing. These electrode pairs are symmetrical about the brain mid-line and allow us to discern any hemispheric EEG asymmetry. EEG data were segmented and filtered into classical bands delta(0.5-4 Hz), theta(4.1-8 Hz), alpha(8.1-12 Hz) and beta(12.1-16 Hz). Then they were further categorized according to the particular sleep state of their origin. Spectral correlation coefficients were computed between the EEG data from the two hemispheres and averaged over the overnight EEG recording. This was done for each frequency band and state of interest, and then the measure Psi(a-->b) was computed. Results from the 18 subjects showed that Psi(a-->b) increased significantly (p < 0.05) when the sleep state changed from NREM to REM, in all the frequency bands considered. Similarly, within both NREM and REM macro-states, Psi(a-->b) changes significantly (p < 0.1) with micro-state changes from the background state towards apnoea/hypopnea and EEGA states. Extensive statistical analysis we conducted with the 18 subjects indicated that the measure Psi(a-->b) provides a novel insight into the functional asymmetry of the brain during SAHS events.
睡眠呼吸暂停低通气综合征（SAHS）是一种严重的睡眠障碍，影响着很大比例的人口。呼吸暂停/低通气和脑电图觉醒（EEGA）事件在SAHS患者中频繁发生。这些事件显著扰乱睡眠结构，夜间脑电图信号揭示了这一点。尽管脑电图携带有关大脑状态的重要信息，但其在临床SAHS诊断中的应用主要限于常规睡眠分期。在本文中，我们解决了这个问题。我们提出了一种名为半球间异步性（Psi(a-->b)）的新测量方法，以捕捉与大脑状态“a”和“b”之间的转变a --> b相关的脑电图对称性变化。我们的工作考虑了传统睡眠阶段等宏观状态，以及EEGA和呼吸暂停/低通气事件等微观状态。我们使用国际10/20系统的电极C4 - A2和C3 - A1，对18名接受多导睡眠图（PSG）测试的受试者的脑电图数据进行了测量。这些电极对关于大脑中线对称，使我们能够辨别任何半球脑电图不对称性。脑电图数据被分割并过滤到经典频段：δ（0.5 - 4Hz）、θ（4.1 - 8Hz）、α（8.1 - 12Hz）和β（12.1 - 16Hz）。然后根据其起源的特定睡眠状态对它们进行进一步分类。计算两个半球脑电图数据之间的频谱相关系数，并在整夜脑电图记录上进行平均。对每个感兴趣的频段和状态都进行了这样的操作，然后计算测量值Psi(a-->b)。18名受试者的结果表明：在所有考虑的频段中，当睡眠状态从非快速眼动（NREM）转变为快速眼动（REM）时，Psi(a-->b)显著增加（p < 0.05）。同样，在NREM和REM宏观状态内，随着微观状态从背景状态向呼吸暂停/低通气和EEGA状态的变化，Psi(a-->b)也有显著变化（p < 0.1）。我们对这18名受试者进行的广泛统计分析表明，测量值Psi(a-->b)为SAHS事件期间大脑的功能不对称性提供了新的见解。
