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 …

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 …

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 …

Healthcare data analysis has emerged as one of the most promising fields of study in recent
years. There are different types of data in the healthcare industry, such as medical test …

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 …