Taxonomy on EEG artifacts removal methods, issues, and healthcare applications
Electroencephalogram (EEG) signals are progressively growing data widely known as
biomedical big data, which is applied in biomedical and healthcare research. The …
biomedical big data, which is applied in biomedical and healthcare research. The …
A Machine Learning‐Based Big EEG Data Artifact Detection and Wavelet‐Based Removal: An Empirical Approach
The electroencephalogram (EEG) signals are a big data which are frequently corrupted by
motion artifacts. As human neural diseases, diagnosis and analysis need a robust …
motion artifacts. As human neural diseases, diagnosis and analysis need a robust …
Gamma oscillatory complexity conveys behavioral information in hippocampal networks
The hippocampus and entorhinal cortex exhibit rich oscillatory patterns critical for cognitive
functions. In the hippocampal region CA1, specific gamma-frequency oscillations, timed at …
functions. In the hippocampal region CA1, specific gamma-frequency oscillations, timed at …
Empirical mode decomposition and its extensions applied to EEG analysis: a review
Empirical mode decomposition (EMD) provides an adaptive, data-driven approach to time–
frequency analysis, yielding components from which local amplitude, phase, and frequency …
frequency analysis, yielding components from which local amplitude, phase, and frequency …
Anatomical and physiological foundations of cerebello-hippocampal interaction
TC Watson, P Obiang, A Torres-Herraez, A Watilliaux… - elife, 2019 - elifesciences.org
Multiple lines of evidence suggest that functionally intact cerebello-hippocampal interactions
are required for appropriate spatial processing. However, how the cerebellum anatomically …
are required for appropriate spatial processing. However, how the cerebellum anatomically …
A wavelet-based artifact reduction from scalp EEG for epileptic seizure detection
This paper presents a method to reduce artifacts from scalp EEG recordings to facilitate
seizure diagnosis/detection for epilepsy patients. The proposed method is primarily based …
seizure diagnosis/detection for epilepsy patients. The proposed method is primarily based …
Improved EOG artifact removal using wavelet enhanced independent component analysis
Electroencephalography (EEG) signals are frequently contaminated with unwanted
electrooculographic (EOG) artifacts. Blinks and eye movements generate large amplitude …
electrooculographic (EOG) artifacts. Blinks and eye movements generate large amplitude …
Wavelet based empirical approach to mitigate the effect of motion artifacts from EEG signal
Physiological signal such as Electroencephalographic (EEG) is often corrupted by artifacts
during measurement and processing. These artifacts may corrupt the important …
during measurement and processing. These artifacts may corrupt the important …
Challenges of neural interfaces for stroke motor rehabilitation
C Vidaurre, N Irastorza-Landa… - Frontiers in Human …, 2023 - frontiersin.org
More than 85% of stroke survivors suffer from different degrees of disability for the rest of
their lives. They will require support that can vary from occasional to full time assistance …
their lives. They will require support that can vary from occasional to full time assistance …
Probability mapping based artifact detection and removal from single-channel EEG signals for brain–computer interface applications
Background Different types of artifacts in the electroencephalogram (EEG) signals can
considerably reduce the performance of the later-stage EEG analysis algorithms for making …
considerably reduce the performance of the later-stage EEG analysis algorithms for making …