FNIRS pre-processing and processing methodologies are very important—how a researcher
chooses to process their data can change the outcome of an experiment. The purpose of this …

This research presents a brain-computer interface (BCI) framework for brain signal
classification using deep learning (DL) and machine learning (ML) approaches on functional …

Introduction: Drowsy driving is a significant factor causing dire road crashes and casualties
around the world. Detecting it earlier and more effectively can significantly reduce the lethal …

In this study, a channel and feature selection methodology is devised for brain‐computer
interface (BCI) applications using functional near‐infrared spectroscopy (fNIRS). A graph …

We investigate the utility of functional near-infrared spectroscopy (fNIRS) for workload-based
adaptive automation through the lens of multiple resource theory. We focus on the criteria of …

In recent decades, the brain–computer interface (BCI) has emerged as a leading area of
research. The feature selection is vital to reduce the dataset's dimensionality, increase the …

The existing research on white feather broiler health monitoring technology concentrate on
the selection of classification algorithms and optimization of internal parameters, ignoring …

Background Advances in neuroimaging have significantly enhanced our understanding of
brain function, providing critical insights into the diagnosis and management of disorders of …

The complex internal structure and heterogeneous composition material of aerospace
equipment make it difficult to apply traditional acoustic emission source localization methods …

The importance of both general and sport-specific perceptual-cognitive abilities in soccer
players has been investigated in several studies. Although these perceptual-cognitive skills …