Electroencephalography (EEG) has been widely used for studying brain function. As cortical
signals recorded by the EEG are very weak, they are often obscured by motion artifacts and …

Electroencephalography (EEG) is a proficient way to record brain activity with the help of
electrodes positioned on the scalp's surface. EEG is chosen in many domains, including …

Reminiscence and conversation between older adults and younger volunteers using past
photographs are very effective in improving the emotional state of older adults and …

A hybrid method is proposed for removing artifacts from electroencephalographic (EEG)
signals. This relies on the integration of artifact subspace reconstruction (ASR) with …

In this research work, a machine learning model is proposed with only those features which
are significantly contributing in prediction using multiple linear regression. The other …

Removing different types of artifacts from the electroencephalography (EEG) recordings is a
critical step in performing EEG signal analysis and diagnosis. Most of the existing algorithms …

Various supervised embedded methods have been proposed to select discriminative
features from original ones, such as Feature Selection with Orthogonal Regression (FSOR) …

This paper presents an EEG artifacts detection and removal system (ARDER). It effectively
removes several types of artifacts including ocular, muscle and transmission-line by utilizing …

Electroencephalogram signals are widely used in neuroscience and brain-computer
interfaces. The EEG signals are relatively weak, so the devices for acquiring the EEG signals …

The recorded electroencephalogram (EEG) are often contaminated by electromyogenic
(EMG) artifacts. This inhibits the further analysis/processing of EEG signal, for corrupting …