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AnEEG: leveraging deep learning for effective artifact removal in EEG data
Nature
In neuroscience and clinical diagnostics, electroencephalography (EEG) is a crucial instrument for capturing neural activity. However, this signal is...
4 days ago
A MultiModal Vigilance (MMV) dataset during RSVP and SSVEP brain-computer interface tasks
Nature
In this report, we describe a MultiModal Vigilance (MMV) dataset comprising seven physiological signals acquired during two Brain-Computer Interface (BCI)...
2 months ago
Customizable automated cleaning of multichannel sleep EEG in SleepTrip
Frontiers
While standard polysomnography has revealed the importance of the sleeping brain in health and disease, more specific insight into the relevant brain...
2 months ago
Current Status, Challenges, and Possible Solutions of EEG-Based Brain-Computer Interface: A Comprehensive Review
Frontiers
Brain-Computer Interface (BCI), in essence, aims at controlling different assistive devices through the utilization of brain waves.
3 months ago
Motion Artifact Removal Techniques for Wearable EEG and PPG Sensor Systems
Frontiers
Removal of motion artifacts is a critical challenge, especially in wearable electroencephalography (EEG) and photoplethysmography (PPG) devices that are...
3 months ago
The PREP pipeline: standardized preprocessing for large-scale EEG analysis
Frontiers
The technology to collect brain imaging and physiological measures has become portable and ubiquitous, opening the possibility of large-scale analysis of...
3 months ago
TMSEEG: A MATLAB-Based Graphical User Interface for Processing Electrophysiological Signals during Transcranial Magnetic Stimulation
Frontiers
Concurrent recording of electroencephalography (EEG) during transcranial magnetic stimulation (TMS) is an emerging and powerful tool for studying brain...
3 months ago
Optimizing EEG ICA decomposition with data cleaning in stationary and mobile experiments
Nature
Electroencephalography (EEG) studies increasingly utilize more mobile experimental protocols, leading to more and stronger artifacts in the recorded data.
4 months ago
Eye State Identification Utilizing EEG Signals: A Combined Method Using Self-Organizing Map and Deep Belief Network
Wiley Online Library
Measuring brain activity through Electroencephalogram (EEG) analysis for eye state prediction has attracted attention from machine learning researchers.
4 months ago
EEG complexity measures for detecting mind wandering during video-based learning
Nature
This study explores the efficacy of various EEG complexity measures in detecting mind wandering during video-based learning.
6 months ago