Shah A K, Agarwal R, Carhuapoma J R, Loeb J A
Department of Neurology, Wayne State University/ Detroit Medical Center, Detroit, MI 48201, USA.
Neurocrit Care. 2006;5(2):124-33. doi: 10.1385/ncc:5:2:124.
Recent advances in continuous electroencephalogram (EEG) monitoring with digital EEG acquisition, storage, and quantitative analysis allow uninterrupted assessment of cerebral cortical activity in critically ill neurological-neurosurgical patients. Early recognition of worsening brain function can prove of vital importance as one can initiate measures aimed to prevent further brain damage. Although continuous EEG monitoring provides adequate spatial and temporal resolution and is able to continuously assess brain function in these critically ill patients, it requires a trained electroencephalographer to interpret the massive amounts of data generated. This limitation impedes the widespread use of EEG in assessing real-time brain function in critically ill patients. Here, we demonstrate the utility of a novel method of automated EEG analysis that segments and extracts EEG features, classifies and groups them according to various patterns, and then presents them in a compressed fashion. This permits real-time viewing of several hours of EEG on a single page. Examples are presented from three patients, two with recurrent seizures and one with diagnosis of subarachnoid hemorrhage. These patients illustrate the ability of this novel method to detect important real-time physiological changes in brain function that could enable early interventions aimed to prevent irreversible brain damage.
数字脑电图采集、存储和定量分析技术在连续脑电图（EEG）监测方面的最新进展，使得对重症神经科-神经外科患者的大脑皮质活动能够进行不间断评估。尽早识别脑功能恶化至关重要，因为这样可以启动旨在预防进一步脑损伤的措施。尽管连续脑电图监测提供了足够的空间和时间分辨率，并且能够持续评估这些重症患者的脑功能，但它需要训练有素的脑电图技术人员来解读所产生的大量数据。这一局限性阻碍了脑电图在评估重症患者实时脑功能方面的广泛应用。在此，我们展示了一种新型自动脑电图分析方法的效用，该方法对脑电图特征进行分割和提取，根据各种模式对其进行分类和分组，然后以压缩形式呈现。这使得能够在单页上实时查看数小时的脑电图。文中给出了三名患者的实例，两名患有复发性癫痫，一名诊断为蛛网膜下腔出血。这些患者说明了这种新方法检测脑功能重要实时生理变化的能力，这些变化能够促成旨在预防不可逆脑损伤的早期干预。
