Brain–computer interfaces are used for direct two-way communication between the human
brain and the computer. Brain signals contain valuable information about the mental state …

With the increase in biosensors and data collection devices in the healthcare industry,
artificial intelligence and machine learning have attracted much attention in recent years. In …

Decoding text stimuli from cognitive signals (eg fMRI) enhances our understanding of the
human language system, paving the way for building versatile Brain-Computer Interface …

Current wavelet thresholding methods for cardiogram signals captured by flexible wearable
sensors face a challenge in achieving both accurate thresholding and real-time signal …

Preprocessing electroencephalographic (EEG) signals during computer-mediated Cognitive
Load tasks is crucial in Human-Computer Interaction (HCI). This process significantly …

An efficient processing approach is essential for increasing identification accuracy since the
electroencephalogram (EEG) signals produced by the Brain–Computer Interface (BCI) …

Fetal alcohol spectrum disorders (FASD) are spectrum of neurodevelopmental conditions
associated with prenatal alcohol exposure. The FASD manifests mostly with facial …

Electroencephalography (EEG) has been and is still widely used in brain function research.
EEG has advantages over other neuroimaging modalities. First, it not only directly images …

Alzheimer's disease (AD) is a prevalent neurodegenerative disorder and a leading cause of
dementia. Aging is a significant risk factor for AD, emphasizing the importance of early …

In this paper Naive Bayesian classifiers were applied for the purpose of differentiation
between the EEG signals recorded from children with Fetal Alcohol Syndrome Disorders …