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Motor imagery EEG decoding based on multi-scale hybrid networks and feature enhancement
X Tang, C Yang, X Sun, M Zou… - IEEE Transactions on …, 2023 - ieeexplore.ieee.org
Motor Imagery (MI) based on Electroencephalography (EEG), a typical Brain-Computer
Interface (BCI) paradigm, can communicate with external devices according to the brain's …
Interface (BCI) paradigm, can communicate with external devices according to the brain's …
Diagnosis of Alzheimer's disease via resting-state EEG: integration of spectrum, complexity, and synchronization signal features
X Zheng, B Wang, H Liu, W Wu, J Sun… - Frontiers in Aging …, 2023 - frontiersin.org
Background Alzheimer's disease (AD) is the most common neurogenerative disorder,
making up 70% of total dementia cases with a prevalence of more than 55 million people …
making up 70% of total dementia cases with a prevalence of more than 55 million people …
[HTML][HTML] Functional connectivity of EEG is subject-specific, associated with phenotype, and different from fMRI
A variety of psychiatric, behavioral and cognitive phenotypes have been linked to brain
''functional connectivity''--the pattern of correlation observed between different brain regions …
''functional connectivity''--the pattern of correlation observed between different brain regions …
Frontoparietal theta-gamma interactions track working memory enhancement with training and tDCS
Despite considerable interest in enhancing, preserving, and rehabilitating working memory
(WM), efforts to elicit sustained behavioral improvements have been met with limited …
(WM), efforts to elicit sustained behavioral improvements have been met with limited …
EEG based automated detection of seizure using machine learning approach and traditional features
The detection of epileptic seizures is key for neurologists to initiate the right treatment at the
earliest. However, the traditional methods are dependent on manual diagnosis which are …
earliest. However, the traditional methods are dependent on manual diagnosis which are …
Learning DenseNet features from EEG based spectrograms for subject independent emotion recognition
Subject-independent emotion recognition (SIER) using electroencephalogram (EEG)
signals has always been a challenge among the biomedical research community. One of the …
signals has always been a challenge among the biomedical research community. One of the …
Neural circuits of idiopathic normal pressure hydrocephalus: a perspective review of brain connectivity and symptoms meta-analysis
Idiopathic normal pressure hydrocephalus (iNPH) is a prevalent reversible neurological
disorder characterized by impaired locomotion, cognition and urinary control with …
disorder characterized by impaired locomotion, cognition and urinary control with …
[HTML][HTML] The emergence of a theta social brain network during infancy
Infants' socio-cognitive ability develops dramatically during the first year of life. From the
perspective of ontogeny, the early development of social behavior allows for parent-child …
perspective of ontogeny, the early development of social behavior allows for parent-child …
Functional connectivity analysis on electroencephalography signals reveals potential biomarkers for treatment response in major depression
SS Huang, YH Yu, HH Chen, CC Hung, YT Wang… - BMC psychiatry, 2023 - Springer
Background The treatment efficacy varies across individual patients with major depressive
disorder (MDD). It lacks robust electroencephalography (EEG) markers for an …
disorder (MDD). It lacks robust electroencephalography (EEG) markers for an …
Comprehensive review of eeg-based algorithms for mental stress analysis
SA Patil, AN Paithane - 2023 7th International Conference On …, 2023 - ieeexplore.ieee.org
Electroencephalography (EEG) as a tool for analyzing mental stress has recently gained
significant attention. The field of neuroscience employs electroencephalography (EEG) to …
significant attention. The field of neuroscience employs electroencephalography (EEG) to …