Frequency decomposition and phase synchronization of the visual evoked potential using the empirical mode decomposition
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Byuckjin Lee
Abstract
Objectives
The phase characteristics of the representative frequency components of the Electroencephalogram (EEG) can be a means of understanding the brain functions of human senses and perception. In this paper, we found out that visual evoked potential (VEP) is composed of the dominant multi-band component signals of the EEG through the experiment.
Methods
We analyzed the characteristics of VEP based on the theory that brain evoked potentials can be decomposed into phase synchronized signals. In order to decompose the EEG signal into across each frequency component signals, we extracted the signals in the time-frequency domain with high resolution using the empirical mode decomposition method. We applied the Hilbert transform (HT) to extract the signal and synthesized it into a frequency band signal representing VEP components. VEP could be decomposed into phase synchronized δ, θ, α, and β frequency signals. We investigated the features of visual brain function by analyzing the amplitude and latency of the decomposed signals in phase synchronized with the VEP and the phase-locking value (PLV) between brain regions.
Results
In response to visual stimulation, PLV values were higher in the posterior lobe region than in the anterior lobe. In the occipital region, the PLV value of theta band was observed high.
Conclusions
The VEP signals decomposed into constituent frequency components through phase analysis can be used as a method of analyzing the relationship between activated signals and brain function related to visual stimuli.
Funding source: This research was supported by the Bio & Medical Technology Development Program of the National Research Foundation(NRF) funded by the Ministry of Science and ICT.
Award Identifier / Grant number: (NRF-2018M3A9H6081483)
Acknowledgment
We thank all participants and anonymous reviewers for invaluable assistance with this article. This research was supported by the Bio & Medical Technology Development Program of the National Research Foundation(NRF) funded by the Ministry of Science and ICT (NRF-2018M3A9H6081483).
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Conflict of interest statement: The authors declare no conflict of interest.
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Articles in the same Issue
- Frontmatter
- Research articles
- A nonlinear dynamical approach to analysis of emotions using EEG signals based on the Poincaré map function and recurrence plots
- Frequency decomposition and phase synchronization of the visual evoked potential using the empirical mode decomposition
- A novel motion coupling coding method for brain-computer interfaces
- Electrocardiography (ECG) analysis and a new feature extraction method using wavelet transform with scalogram analysis
- A novel non-invasive method for estimating the local wave speed at a single site in the internal carotid artery
- Classification of standing and sitting phases based on in-socket piezoelectric sensors in a transfemoral amputee
- The performance of a low-cost bio-amplifier on 3D human arm movement reconstruction
- Mathematical model of patella T-reflex and clinical evaluation with Ashworth scales
- Replication of left ventricular haemodynamics with a simple planar mitral valve model
- Detection of skin cancer with adaptive fuzzy classifier using improved whale optimization
- Titanium coating: introducing an antibacterial and bioactive chitosan-alginate film on titanium by spin coating
- Osteoclast and osteoblast response to strontium-doped struvite coatings on titanium for improved bone integration
- Does preconditioning lower the rupture resistance of chorioamniotic membrane?
