详细信息
Automatic reference selection for quantitative EEG interpretation: Identification of diffuse/localised activity and the active earlobe reference, iterative detection of the distribution of EEG rhythms ( SCI-EXPANDED收录 EI收录)
文献类型:期刊文献
英文题名:Automatic reference selection for quantitative EEG interpretation: Identification of diffuse/localised activity and the active earlobe reference, iterative detection of the distribution of EEG rhythms
作者:Wang, Bei[1];Wang, Xingyu[1];Ikeda, Akio[2];Nagamine, Takashi[3];Shibasaki, Hiroshi[4];Nakamura, Masatoshi[5]
机构:[1]E China Univ Sci & Technol, Minist Educ, Key Lab Adv Control & Optimizat Chem Proc, Shanghai 200237, Peoples R China;[2]Kyoto Univ, Dept Neurol, Kyoto 6068501, Japan;[3]Sapporo Med Univ, Dept Syst Neurosci, Sapporo, Hokkaido 0608556, Japan;[4]Takeda Gen Hosp, Kyoto 6011495, Japan;[5]Saga Univ, Inst Adv Res & Educ, Res Inst Syst Control, Saga 8400047, Japan
年份:2014
卷号:36
期号:1
起止页码:88
外文期刊名:MEDICAL ENGINEERING & PHYSICS
收录:;EI(收录号:20151000598161);WOS:【SCI-EXPANDED(收录号:WOS:000330261200013)】;
基金:This study is supported by Nation Nature Science Foundation of China 61074113; Scientific Research Foundation for the Returned Overseas Chinese Scholars, State Education Ministry; Medical Cooperation Project by Shanghai Municipal Science and Technology Commission 12DZ1940903; Shanghai Leading Academic Discipline Project B504.
语种:英文
外文关键词:Automatic reference selection; Averaged reference; Quantitative EEG interpretation; Digital recording technique
摘要:EEG (Electroencephalograph) interpretation is important for the diagnosis of neurological disorders. The proper adjustment of the montage can highlight the EEG rhythm of interest and avoid false interpretation. The aim of this study was to develop an automatic reference selection method to identify a suitable reference. The results may contribute to the accurate inspection of the distribution of EEG rhythms for quantitative EEG interpretation. The method includes two pre-judgements and one iterative detection module. The diffuse case is initially identified by pre-judgement 1 when intermittent rhythmic waveforms occur over large areas along the scalp. The earlobe reference or averaged reference is adopted for the diffuse case due to the effect of the earlobe reference depending on pre-judgement 2. An iterative detection algorithm is developed for the localised case when the signal is distributed in a small area of the brain. The suitable averaged reference is finally determined based on the detected focal and distributed electrodes. The presented technique was applied to the pathological EEG recordings of nine patients. One example of the diffuse case is introduced by illustrating the results of the pre-judgements. The diffusely intermittent rhythmic slow wave is identified. The effect of active earlobe reference is analysed. Two examples of the localised case are presented, indicating the results of the iterative detection module. The focal and distributed electrodes are detected automatically during the repeating algorithm. The identification of diffuse and localised activity was satisfactory compared with the visual inspection. The EEG rhythm of interest can be highlighted using a suitable selected reference. The implementation of an automatic reference selection method is helpful to detect the distribution of an EEG rhythm, which can improve the accuracy of EEG interpretation during both visual inspection and automatic interpretation. (C) 2013 IPEM. Published by Elsevier Ltd. All rights reserved.
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