自回归模型在脑电活动地形图模式识别中的应用。
An application of autoregressive model to pattern discrimination of brain electrical activity mapping.
作者信息
Ogawa T, Sonoda H, Ishiwa S, Shigeta Y
机构信息
Department of Pediatrics, Oita Medical University, Japan.
出版信息
Brain Topogr. 1993 Fall;6(1):3-11. doi: 10.1007/BF01234121.
PMID:8260324
Abstract
Using the autoregressive model, we developed a method of illustrating significant regional differences between two records of brain electrical activity mapping. This new approach of brain electrical activity mapping analysis through a statistical taxonomy may be clinically useful for evaluation of the normal development of EEG in children and for localizing functional brain abnormality.
摘要
利用自回归模型，我们开发了一种方法，用于说明脑电活动图谱的两条记录之间的显著区域差异。这种通过统计分类法进行脑电活动图谱分析的新方法，在临床上可能有助于评估儿童脑电图的正常发育以及定位脑功能异常。
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