The EEG analysis method for obtaining the feeling

2008 ◽  
Author(s):  
Yohei Tomita ◽  
Shin-ichi Ito ◽  
Yasue Mitsukura
Keyword(s):  
Eeg Analysis ◽  
Analysis Method

Model-Based EEG Analysis: Proposal and Verification of Mathematical Model for Application to Neurotechnology

2019 ◽  
Author(s):  
Kenyu Uehara ◽  
Takashi Saito
Keyword(s):  
Mathematical Model ◽  
Binary Classification ◽  
Least Square ◽  
Mental Condition ◽  
Support Vector ◽  
Model Parameters ◽  
Eeg Analysis ◽  
Analysis Method ◽  
Model Based ◽  
Proposed Model

Abstract We have modeled dynamics of EEG with one degree of freedom nonlinear oscillator and examined the relationship between mental state of humans and model parameters simulating behavior of EEG. At the IMECE conference last year, Our analysis method identified model parameters sequentially so as to match the waveform of experimental EEG data of the alpha band using one second running window. Results of temporal variation of model parameters suggested that the mental condition such as degree of concentration could be directly observed from the dynamics of EEG signal. The method of identifying the model parameters in accordance with the EEG waveform is effective in examining the dynamics of EEG strictly, but it is not suitable for practical use because the analysis (parameter identification) takes a long time. Therefore, the purpose of this study is to test the proposed model-based analysis method for general application as a neurotechnology. The mathematical model used in neuroscience was improved for practical use, and the test was conducted with the cooperation of four subjects. model parameters were experimentally identified approximately every one second by using least square method. We solved a binary classification problem of model parameters using Support Vector Machine. Results show that our proposed model-based EEG analysis is able to discriminate concentration states in various tasks with an accuracy of over 80%.

scholarly journals A novel integrated MEG and EEG analysis method for dipolar sources

NeuroImage ◽  
2007 ◽  
Vol 37 (3) ◽  
pp. 731-748 ◽  
Author(s):  
Ming-Xiong Huang ◽  
Tao Song ◽  
Donald J. Hagler ◽  
Igor Podgorny ◽  
Veikko Jousmaki ◽  
...  
Keyword(s):  
Eeg Analysis ◽  
Analysis Method

An Optimal Smooth Model based EEG Analysis Method

2021 ◽  
Author(s):  
Chao Chen ◽  
Tianxu Shang ◽  
Abdelkader Nasreddine Belkacem ◽  
Shanting Zhang ◽  
Lin Lu ◽  
...  
Keyword(s):  
Eeg Analysis ◽  
Analysis Method ◽  
Model Based ◽  
Smooth Model

Electroencephalographic Evaluation in Fibromyalgia: A Systematic Review

2021 ◽  
pp. 155005942199712
Author(s):  
Géssika Araújo de Melo ◽  
Marcela Laís Lima Holmes Madruga ◽  
Nelson Torro
Keyword(s):  
Systematic Review ◽  
Systematic Reviews ◽  
Database Search ◽  
Promising Method ◽  
Eeg Analysis ◽  
Analysis Method ◽  
Exclusion Criteria ◽  
Meta Analyses ◽  
Electroencephalogram Eeg

Introduction. The evaluation of individuals with fibromyalgia is challenging. Electroencephalography is a promising resource for identifying physiological biomarkers in fibromyalgia, contributing to its diagnosis. Objective. To review studies involving the use of electroencephalography to evaluate individuals with fibromyalgia. Method. A systematic review of studies published in the PubMed, Lilacs, and SciELO databases from 2001 to 2020 was conducted. The keywords used were electroencephalogram, electroencephalography, and fibromyalgia. The database search complied with the preferred reporting items for systematic reviews and meta-analyses (PRISMA) criteria. Results. A total of 136 articles were identified after a database search using the keywords “fibromyalgia” AND “electroencephalography”, and 131 articles were found using the keywords “fibromyalgia” AND “electroencephalogram” (EEG). In the end, 20 articles remained after applying the exclusion criteria. The data was organized into subcategories related to the form of use, protocols, electroencephalographic findings in patients with fibromyalgia, and the EEG analysis method. Conclusion. Electroencephalography is a promising method for identifying and characterizing biomarkers for fibromyalgia.

A Study of the Use of EEG Analysis to Evaluate the Depth of Anesthesia Using Bispectrum Analysis Method

2004 ◽  
Vol 46 (2) ◽  
pp. 139
Author(s):  
Seong Wan Baik ◽  
Sung Jin Lee ◽  
Joon Mo Park ◽  
Jae Hyun Kim ◽  
Cheol Hwan Kim ◽  
...  
Keyword(s):  
Depth Of Anesthesia ◽  
Eeg Analysis ◽  
Analysis Method

scholarly journals Proposal of the EEG Analysis Method Using the Individual Characteristic of the EEG

2004 ◽  
Vol 124 (6) ◽  
pp. 1259-1266 ◽  
Author(s):  
Shin-ichi Ito ◽  
Yasue Mitsukura ◽  
Minoru Fukumi ◽  
Norio Akamtsu
Keyword(s):  
Individual Characteristic ◽  
Eeg Analysis ◽  
Analysis Method ◽  
The Individual

Shall I Move My Right or My Left Hand?

2003 ◽  
Vol 17 (2) ◽  
pp. 69-86 ◽  
Author(s):  
Claudio Babiloni ◽  
Fabio Babiloni ◽  
Filippo Carducci ◽  
Febo Cincotti ◽  
Claudio Del Percio ◽  
...  
Keyword(s):  
Bimanual Coordination ◽  
Central Area ◽  
Eeg Analysis ◽  
Complementary Information ◽  
Left Hand ◽  
Mirror Movements ◽  
Related Potentials ◽  
Motor Acts ◽  
Abstract Event

Abstract Event-related desynchronization/synchronization (ERD/ERS) at alpha (10Hz), beta (20Hz), and gamma (40Hz) bands and movement-related potentials (MRPs) were investigated in right-handed subjects who were “free” to decide the side of unilateral finger movements (“fixed” side as a control). As a novelty, this “multi-modal” EEG analysis was combined with the evaluation of involuntary mirror movements, taken as an index of “bimanual competition.” A main issue was whether the decision regarding the hand to be moved (“free” movements) could modulate ERD/ERS or MRPs overlying sensorimotor cortical areas typically involved in bimanual tasks. Compared to “fixed” movements, “free” movements induced the following effects: (1) more involuntary mirror movements discarded from EEG analysis; (2) stronger vertex MRPs (right motor acts); (3) a positive correlation between these potentials and the number of involuntary mirror movements; (4) gamma ERS over central areas; and (5) preponderance of postmovement beta ERS over left central area (dominant hemisphere). These results suggest that ERD/ERS and MRPs provide complementary information on the cortical processes belonging to a lateralized motor act. In this context, the results on vertex MRPs would indicate a key role of supplementary/cingulate motor areas not only for bimanual coordination but also for the control of “bimanual competition” and involuntary mirror movements.

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