Brain neurotrauma: molecular, neuropsychological, and rehabilitation aspects
FH Kobeissy - 2015 - books.google.com
With the contribution from more than one hundred CNS neurotrauma experts, this book
provides a comprehensive and up-to-date account on the latest developments in the area of …
provides a comprehensive and up-to-date account on the latest developments in the area of …
Techniques and countermeasures for preventing insider threats
RA Alsowail, T Al-Shehari - PeerJ Computer Science, 2022 - peerj.com
With the wide use of technologies nowadays, various security issues have emerged. Public
and private sectors are both spending a large portion of their budget to protect the …
and private sectors are both spending a large portion of their budget to protect the …
[HTML][HTML] Cross-subject EEG channel selection method for lower limb brain-computer interface
Lower limb motor imagery (MI) classification is a challenging research topic in the area of
brain-computer interfaces (BCIs), and entails numerous signal channels to provide sufficient …
brain-computer interfaces (BCIs), and entails numerous signal channels to provide sufficient …
Auditory deep sleep stimulation in older adults at home: a randomized crossover trial
Background Auditory stimulation has emerged as a promising tool to enhance non-
invasively sleep slow waves, deep sleep brain oscillations that are tightly linked to sleep …
invasively sleep slow waves, deep sleep brain oscillations that are tightly linked to sleep …
A logistic binary Jaya optimization-based channel selection scheme for motor-imagery classification in brain-computer interface
A Tiwari - Expert Systems with Applications, 2023 - Elsevier
BCI systems use motor imagery to allow users to control external devices through their brain
activity. They extract neural signals from the brain using a large number of EEG channels …
activity. They extract neural signals from the brain using a large number of EEG channels …
EEG-Based Parkinson's Disease Recognition Via Attention-based Sparse Graph Convolutional Neural Network
Parkinson's disease (PD) is a complicated neurological ailment that affects both the physical
and mental wellness of elderly individuals which makes it problematic to diagnose in its …
and mental wellness of elderly individuals which makes it problematic to diagnose in its …
Neurodesk: an accessible, flexible and portable data analysis environment for reproducible neuroimaging
Neuroimaging research requires purpose-built analysis software, which is challenging to
install and may produce different results across computing environments. The community …
install and may produce different results across computing environments. The community …
Electroencephalogram aperiodic power spectral slope can be reliably measured and predicts ADHD risk in early development
The aperiodic exponent of the electroencephalogram (EEG) power spectrum has received
growing attention as a physiological marker of neurodevelopmental psychopathology …
growing attention as a physiological marker of neurodevelopmental psychopathology …
Deep learning for detecting multi-level driver fatigue using physiological signals: A comprehensive approach
A large share of traffic accidents is related to driver fatigue. In recent years, many studies
have been organized in order to diagnose and warn drivers. In this research, a new …
have been organized in order to diagnose and warn drivers. In this research, a new …
Early diagnosis of Parkinson's disease using EEG, machine learning and partial directed coherence
APS De Oliveira, MA De Santana… - Research on Biomedical …, 2020 - Springer
Background Parkinson's disease (PD) is a neurodegenerative disease, which has an
upward progression. In advanced stages, motor symptoms cause functional impairment to …
upward progression. In advanced stages, motor symptoms cause functional impairment to …