Brain-computer interface: Advancement and challenges
Brain-Computer Interface (BCI) is an advanced and multidisciplinary active research domain
based on neuroscience, signal processing, biomedical sensors, hardware, etc. Since the …
based on neuroscience, signal processing, biomedical sensors, hardware, etc. Since the …
How to successfully classify EEG in motor imagery BCI: a metrological analysis of the state of the art
Objective. Processing strategies are analyzed with respect to the classification of
electroencephalographic signals related to brain-computer interfaces (BCIs) based on motor …
electroencephalographic signals related to brain-computer interfaces (BCIs) based on motor …
Exploiting pretrained CNN models for the development of an EEG-based robust BCI framework
Identifying motor and mental imagery electroencephalography (EEG) signals is imperative to
realizing automated, robust brain-computer interface (BCI) systems. In the present study, we …
realizing automated, robust brain-computer interface (BCI) systems. In the present study, we …
Alcoholic EEG signals recognition based on phase space dynamic and geometrical features
Alcoholism is a severe disorder that leads to brain problems and associated cognitive,
emotional and behavioral impairments. This disorder is typically diagnosed by a …
emotional and behavioral impairments. This disorder is typically diagnosed by a …
Schizophrenia recognition based on the phase space dynamic of EEG signals and graphical features
Schizophrenia is a mental disorder that causes adverse effects on the mental capacity of a
person, emotional inclinations, and quality of personal and social life. The official statistics …
person, emotional inclinations, and quality of personal and social life. The official statistics …
Depression recognition based on the reconstruction of phase space of EEG signals and geometrical features
Depression is a mental disorder that continues to make life difficult or impossible for a
depressed person and, if left untreated, can lead to dangerous activities such as self-harm …
depressed person and, if left untreated, can lead to dangerous activities such as self-harm …
A new framework for automatic detection of motor and mental imagery EEG signals for robust BCI systems
Nonstationary signal decomposition (SD) is a primary procedure to extract monotonic
components or modes from electroencephalogram (EEG) signals for the development of …
components or modes from electroencephalogram (EEG) signals for the development of …
Classification of normal and depressed EEG signals based on centered correntropy of rhythms in empirical wavelet transform domain
A widespread brain disorder of present days is depression which influences 264 million of
the world's population. Depression may cause diverse undesirable consequences, including …
the world's population. Depression may cause diverse undesirable consequences, including …
[PDF][PDF] Depression Detection Based on Geometrical Features Extracted from SODP Shape of EEG Signals and Binary PSO.
Accepted: 13 December 2020 Late detection of depression is having detrimental
consequences including suicide thus there is a serious need for an accurate computer …
consequences including suicide thus there is a serious need for an accurate computer …
Exploiting feature selection and neural network techniques for identification of focal and nonfocal EEG signals in TQWT domain
For drug resistance patients, removal of a portion of the brain as a cause of epileptic
seizures is a surgical remedy. However, before surgery, the detailed analysis of the epilepsy …
seizures is a surgical remedy. However, before surgery, the detailed analysis of the epilepsy …