In recent years, brain-based technologies that capitalise on human abilities to facilitate
human–system/robot interactions have been actively explored, especially in brain robotics …

Continuous advancements in computing technology and artificial intelligence in the past
decade have led to improvements in driver monitoring systems. Numerous experimental …

Detecting drowsiness in drivers, especially multi-level drowsiness, is a difficult problem that
is often approached using neurophysiological signals as the basis for building a reliable …

Brain-Computer Interface (BCI), in essence, aims at controlling different assistive devices
through the utilization of brain waves. It is worth noting that the application of BCI is not …

Recognition of epileptic seizure type is essential for the neurosurgeon to understand the
cortical connectivity of the brain. Though automated early recognition of seizures from …

We present a machine learning based COVID-19 cough classifier which can discriminate
COVID-19 positive coughs from both COVID-19 negative and healthy coughs recorded on a …

Pilots of aircraft face varying degrees of cognitive workload even during normal flight
operations. Periods of low cognitive workload may be followed by periods of high cognitive …

In this study, electroencephalography-based data for emotion recognition analysis are
introduced. EEG signals were collected from 28 different subjects with a wearable and …

The robustness and computational load are the key challenges in motor imagery (MI) based
on electroencephalography (EEG) signals to decode for the development of practical brain …

A system for epileptic seizure detection in electroencephalography (EEG) is described in this
paper. One of the challenges is to distinguish rhythmic discharges from nonstationary …