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1
Dynamic topological justification for flat electroencephalography
Published 2012“…Flat EEG is a way of viewing electroencephalography signals on the real plane. The wealth of information contained within makes it a great platform to study epileptic seizure. …”
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2
Topological properties of flat electroencephalography’s state space
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3
Topological properties of flat electroencephalography's state space
Published 2016Conference or Workshop Item -
4
The decomposition of electroencephalography signals during epileptic seizure
Published 2019“…This paper describes how elementary electroencephalography (EEG) signals can be decomposed by using Jordan-Chevalley decomposition theorem. …”
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5
Advanced fuzzy set: an application to flat electroencephalography image
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6
Elementary components of electroencephalography signals viewed as prime numbers
Published 2021Get full text
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7
Flat electroencephalography’s cluster centers movement tracking during epileptic seizure
Published 2018“…This dynamic process is often associated with electroencephalography (EEG), which is an electrophysical method to record the electrical activity of the brain. …”
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8
Edge detection of flat electroencephalography image via classical and fuzzy approach
Published 2016Conference or Workshop Item -
9
Contrast comparison of flat electroencephalography image: classical, fuzzy, and intuitionistic fuzzy set
Published 2015Conference or Workshop Item -
10
Development of brain signal processing interface software for Trackit-LabVIEW
Published 2009“…There are many digital electroencephalography (EEG) acquisition systems available nowadays for researchers due to the demand in the brain signal research. …”
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11
Sensory response through EEG interpretation on alpha wave and power spectrum
Published 2013“…At the end, the sensory response was recorded through the electroencephalography (EEG) and the range of wave was determined. …”
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12
Effects of visual feedback on coherence between human brain and muscle
Published 2003“…Previous studies of oscillatory interaction between signals of human motor cortex and its peripheral muscle using electroencephalography (EEG) and surface electromyography (EMG) observed rhythmic activities in the frequency band 15-35 Hz. …”
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13
Intuitionistic fuzzy set: feeg image representation
Published 2019“…Flat Electroencephalography (fEEG) is a technique that mapped high dimensional signal into low dimensional space. …”
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14
Fundamental study on brain signal for BCI-FES System Development
Published 2012“…This article presents an introduction into Electroencephalography (EEG) measurement and the simple experiment of EEG. …”
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15
Fundamental study on brain signal for bci-fes system development
Published 2012“…This article presents an introduction into Electroencephalography (EEG) measurement and the simple experiment of EEG. …”
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16
Selection probe of EEG using dynamic graph of autocatalytic set (ACS)
Published 2016“…Electroencephalography (EEG) machine is a medical equipment which is used to diagnose seizure. …”
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17
Time frequency analysis of electrooculograph (EOG) signal of eye movement potentials based on wavelet energy distribution
Published 2011“…In this study, we describe the identification electroencephalography (EOG) signals of eye movement potentials by using wavelet algorithm which gives a lot of information than FFT. …”
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18
Cortical functional connectivity by partial directed coherence in relation to creative thinking: A case study
Published 2021“…While sketching, the brain signals of the participants were captured using electroencephalography. Then, partial directed coherence was applied to analyze the information pathway. …”
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19
Stroke-related mild cognitive impairment detection during working memory tasks using EEG signal processing
Published 2017“…The aim of the present study was to reveal markers from the electroencephalography (EEG) using approximation entropy (ApEn) and permutation entropy (PerEn). …”
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20
Classification of motor imaginary EEG signals using machine learning
Published 2020“…In this work, we explore electroencephalography (EEG) signal classification, specifically for motor imagery (MI) tasks. …”
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