Systematic review on resting‐state EEG for Alzheimer's disease diagnosis and progression assessment
Alzheimer's disease (AD) is a neurodegenerative disorder that accounts for nearly 70% of
the more than 46 million dementia cases estimated worldwide. Although there is no cure for …
the more than 46 million dementia cases estimated worldwide. Although there is no cure for …
A survey of machine learning techniques in physiology based mental stress detection systems
SS Panicker, P Gayathri - Biocybernetics and Biomedical Engineering, 2019 - Elsevier
Various automated/semi-automated medical diagnosis systems based on human physiology
have been gaining enormous popularity and importance in recent years. Physiological …
have been gaining enormous popularity and importance in recent years. Physiological …
Which reference should we use for EEG and ERP practice?
Which reference is appropriate for the scalp ERP and EEG studies? This unsettled problem
still inspires unceasing debate. The ideal reference should be the one with zero or constant …
still inspires unceasing debate. The ideal reference should be the one with zero or constant …
[HTML][HTML] The role of electroencephalography electrical reference in the assessment of functional brain–heart interplay: From methodology to user guidelines
Background The choice of EEG reference has been widely studied. However, the choice of
the most appropriate re-referencing for EEG data is still debated. Moreover, the role of EEG …
the most appropriate re-referencing for EEG data is still debated. Moreover, the role of EEG …
MMSFL-OWFB: A novel class of orthogonal wavelet filters for epileptic seizure detection
The optimal filters with minimal bandwidth are highly desirable in many applications such as
communication and biomedical signal processing. In this study, we design optimally …
communication and biomedical signal processing. In this study, we design optimally …
A large scale screening study with a SMR-based BCI: Categorization of BCI users and differences in their SMR activity
Brain-Computer Interfaces (BCIs) are inefficient for a non-negligible part of the population,
estimated around 25%. To understand this phenomenon in Sensorimotor Rhythm (SMR) …
estimated around 25%. To understand this phenomenon in Sensorimotor Rhythm (SMR) …
Diagnosis of Alzheimer's Disease by Time‐Dependent Power Spectrum Descriptors and Convolutional Neural Network Using EEG Signal
Using strategies that obtain biomarkers where early symptoms coincide, the early detection
of Alzheimer's disease and its complications is essential. Electroencephalogram is a …
of Alzheimer's disease and its complications is essential. Electroencephalogram is a …
Epileptic seizure prediction by the detection of seizure waveform from the pre-ictal phase of EEG signal
Epilepsy is a significant burden on our society till now, due to appropriate healthcare
treatment, cost of therapy, the spontaneous and unpredictable occurrence of seizures. There …
treatment, cost of therapy, the spontaneous and unpredictable occurrence of seizures. There …
[HTML][HTML] Dementia ConnEEGtome: towards multicentric harmonization of EEG connectivity in neurodegeneration
The proposal to use brain connectivity as a biomarker for dementia phenotyping can be
potentiated by conducting large-scale multicentric studies using high-density …
potentiated by conducting large-scale multicentric studies using high-density …
Electrical source Imaging of somatosensory evoked potentials from intracranial EEG signals
A Kalina, P Jezdik, P Fabera, P Marusic, J Hammer - Brain Topography, 2023 - Springer
Stereoelectroencephalography (SEEG) records electrical brain activity with intracerebral
electrodes. However, it has an inherently limited spatial coverage. Electrical source imaging …
electrodes. However, it has an inherently limited spatial coverage. Electrical source imaging …