Quantitative electroencephalogram (qEEG) plays a significant role in EEG-based clinical diagnosis and studies of brain function. In past decades, various qEEG methods have been extensively studied. This article provides a detailed review of the advances in this field. qEEG methods are generally classified into linear and nonlinear approaches. The traditional qEEG approach is based on spectrum analysis, which hypothesizes that the EEG is a stationary process. EEG signals are nonstationary and nonlinear, especially in some pathological conditions. Various time-frequency representations and time-dependent measures have been proposed to address those transient and irregular events in EEG. With regard to the nonlinearity of EEG, higher order statistics and chaotic measures have been put forward. In characterizing the interactions across the cerebral cortex, an information theory-based measure such as mutual information is applied. To improve the spatial resolution, qEEG analysis has also been combined with medical imaging technology (e.g., CT, MR, and PET). With these advances, qEEG plays a very important role in basic research and clinical studies of brain injury, neurological disorders, epilepsy, sleep studies and consciousness, and brain function.

中文翻译：

---

定量脑电图分析方法的进展。

定量脑电图（qEEG）在基于EEG的临床诊断和脑功能研究中发挥重要作用。在过去的几十年中，已经广泛研究了各种qEEG方法。本文详细介绍了该领域的进展。qEEG方法通常分为线性方法和非线性方法。传统的qEEG方法基于频谱分析，该分析假设EEG是平稳过程。脑电信号是不稳定的和非线性的，尤其是在某些病理情况下。已经提出了各种时频表示和时间相关的措施来解决EEG中的那些瞬时和不规则事件。关于脑电的非线性，提出了高阶统计和混沌措施。在表征整个大脑皮层的相互作用时，将应用基于信息论的度量，例如互信息。为了提高空间分辨率，qEEG分析也已与医学成像技术（例如CT，MR和PET）相结合。有了这些进展，qEEG在脑损伤，神经系统疾病，癫痫，睡眠研究和意识以及脑功能的基础研究和临床研究中起着非常重要的作用。