title: 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.
abstract: 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.
authors.affiliation: Key Laboratory of Advanced Control and Optimization for Chemical Processes, Ministry of Education, East China University of Science and Technology, Shanghai 200237, China. Electronic address: beiwang@ecust.edu.cn.
authors.forename: Bei
authors.initials: B
authors.lastname: Wang
authors.affiliation: Key Laboratory of Advanced Control and Optimization for Chemical Processes, Ministry of Education, East China University of Science and Technology, Shanghai 200237, China.
authors.forename: Xingyu
authors.initials: X
authors.lastname: Wang
authors.affiliation: Department of Neurology, Kyoto University, Kyoto 606-8501, Japan.
authors.forename: Akio
authors.initials: A
authors.lastname: Ikeda
authors.affiliation: Department of System Neuroscience, Sapporo Medical University, Hokkaido 060-8556, Japan.
authors.forename: Takashi
authors.initials: T
authors.lastname: Nagamine
authors.affiliation: Takeda General Hospital, Kyoto 601-1495, Japan.
authors.forename: Hiroshi
authors.initials: H
authors.lastname: Shibasaki
authors.affiliation: Research Institute of Systems Control, Institute for Advanced Research and Education, Saga University, Saga 840-0047, Japan.
authors.forename: Masatoshi
authors.initials: M
authors.lastname: Nakamura
mesh_terms: D001331:Automation; D004569:Electroencephalography / Q000379:methods* / Q000592:standards; D006801:Humans; D012015:Reference Standards; D012535:Scalp; D012815:Signal Processing, Computer-Assisted
keywords: Automatic reference selection; Averaged reference; Digital recording technique; Quantitative EEG interpretation