Data-driven visualization of multichannel EEG coherence networks based on community structure analysis
Sign Up to like & getrecommendations! Published in 2018 at "Applied Network Science"
DOI: 10.1007/s41109-018-0096-x
Abstract: An electroencephalography (EEG) coherence network is a representation of functional brain connectivity, and is constructed by calculating the coherence between pairs of electrode signals as a function of frequency. Typical visualizations of coherence networks use… read more here.
Keywords: coherence; analysis; coherence networks; multichannel eeg ... See more keywords
Binary classification of multichannel-EEG records based on the ϵ-complexity of continuous vector functions
Sign Up to like & getrecommendations! Published in 2017 at "Computer methods and programs in biomedicine"
DOI: 10.1016/j.cmpb.2017.09.001
Abstract: BACKGROUND AND OBJECTIVE A crucial step in a classification of electroencephalogram (EEG) records is the feature selection. The feature selection problem is difficult because of the complex structure of EEG signals. To classify the EEG… read more here.
Keywords: classification; feature; complexity; eeg records ... See more keywords
Entropy-Based Emotion Recognition from Multichannel EEG Signals Using Artificial Neural Network
Sign Up to like & getrecommendations! Published in 2022 at "Computational Intelligence and Neuroscience"
DOI: 10.1155/2022/6000989
Abstract: Humans experience a variety of emotions throughout the course of their daily lives, including happiness, sadness, and rage. As a result, an effective emotion identification system is essential for electroencephalography (EEG) data to accurately reflect… read more here.
Keywords: neural network; emotion; artificial neural; emotion recognition ... See more keywords