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| Prejudgments for Reference Potential Determination to Quantitative EEG Interpretation: Amplitude Distribution and Ear-lobe Activation |
| WANG Bei1, WANG Xing-yu1, Akio Ikeda2, Takashi Nagamine3, Hiroshi Shibasaki4, Masatoshi Nakamura5 |
1. Department of Automation, College of Information Science and Technology, East China University of Science and Technology, Shanghai 200237, China;
2. Department of Neurology, Kyoto University, Kyot0 606-8501, Japan;
3. Department of System Neuroscience, Sapporo Medical University, Hokkaid0 060-8556, Japan;
4. Takeda General Hospital, Kyot0 601-1495, Japan;
5. Research Institute of Systems Control Institute for Advanced Research and Education, Saga University, Saga 840-0047, Japan |
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Abstract This paper presents an automatic techruque of suitable reference potential selection for quantitative EEG interpretation. The 16-channels EEG recording under mono-polar derivation is analyzed. There are two prejudgments defined for checking the amplitude distribution and ear lobe activation. After prejudgments, the EEG is classified into several cases in cluding diffused case, non-diffused case, and artifact contami nation case. Due to the cases, an automatic reference selection method is applied in order to find out suitable reference potential. Finally, the referential derivation constructed according to the obtained reference potential, is evaluated for further EEG rhythm analysis. The presented technique can high light the EEG rhythm of interest, which is useful for quantitative EEG interpretation by both visual inspection and automatic evaluation.
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Received: 05 April 2019
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| Fund:National Natural Science Foundation of China; grant number: 61074113; grant sponsor: Shanghai Leading Academic Discipline Project; grant number: B504; grant sponsor: Fundamental Research Funds for the Central Universities; grant number: WH0914028 |
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Corresponding Authors:
WANG Bei. E-mail: beiwang@ecust.edu.cn
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[1] Nakamura M, Shibasaki H, Imajoh K, et al.Automatic EEG interpretation: a new computer-assisted systemfor the automatic integrative interpretation of awake background EEG[J]. Electroencephalogr Clinical Neurophysiology, 1992, 82: 423-431.
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[4] Wang B, Wang X, Ikeda A, et al.Automatic detection of EEG rhythms topographical distribution based on iterative adjustment of averaged reference potential[J]. Artificial Life and Robotics, 2011,16(2): 243-247. |
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