脑电图
临床神经生理学
计算机科学
工件(错误)
标准化
可靠性(半导体)
模式识别(心理学)
人工智能
医学物理学
心理学
医学
神经科学
功率(物理)
物理
量子力学
操作系统
作者
Thomas F. Collura,David Cantor,Dan Chartier,Robert Crago,Allison Hartzoge,Merlyn Hurd,Cynthia Kerson,Joel F. Lubar,John K. Nash,Leslie S. Prichep,Tanju Sürmeli,Tiff Thompson,Mary Fran Tracy,Robert P. Turner
标识
DOI:10.1177/15500594241308654
摘要
Quantitative electroencephalogram (QEEG) is a technology which has grown exponentially since the foundational publication by in Science in 1997, introducing the use of age-regressed metrics to quantify characteristics of the EEG signal, enhancing the clinical utility of EEG in neuropsychiatry. Essential to the validity and reliability of QEEG metrics is standardization of multi-channel EEG data acquisition which follows the standards set forth by the American Clinical Neurophysiology Society including accurate management of artifact and facilitation of proper visual inspection of EEG paroxysmal events both of which are expanded in this guideline. Additional requirements on the selection of EEG, quality reporting, and submission of the EEG to spectral, statistical, and topographic analysis are proposed. While there are thousands of features that can be mathematically derived using QEEG, there are common features that have been most recognized and most validated in clinical use and these along with other mathematical tools, such as low resolution electromagnetic tomographic analyses (LORETA) and classifier functions, are reviewed and cautions are noted. The efficacy of QEEG in these applications depends strongly on the quality of the acquired EEG, and the correctness of subsequent inspection, selection, and processing. These recommendations which are described in the following sections as minimum standards for the use of QEEG are supported by the International QEEG Certification Board (IQCB).
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