This study aimed to construct a novel multimodal model by fusing different
electroencephalogram (EEG) data sources, which were under neutral, negative and positive …

Monitoring human brain activity has great potential in helping us understand the functioning
of our brain, as well as in preventing mental disorders and cognitive decline and improve …

Objective. High-density electroencephelography (EEG) can provide an insight into human
brain function during real-world activities with walking. Some recent studies have used EEG …

Driver drowsiness is a major cause of mortality in traffic accidents worldwide.
Electroencephalographic (EEG) signal, which reflects the brain activities, is more directly …

Recent mobile brain/body imaging (MoBI) techniques based on active electrode scalp
electroencephalogram (EEG) allow the acquisition and real-time analysis of brain dynamics …

Brain waves obtained by Electroencephalograms (EEG) recording are an important
research area in medical and health and brain computer interface (BCI). Due to the nature of …

In order to detect human operator performance degradation or breakdown, this paper
proposes an adaptive support vector machine-based method to classify operator mental …

There is a growing interest in data fusion oriented to identification and authentication from
biometric traits and physiological signals, because of its capacity for combining multiple …

In the construction environment with high attention requirements, distraction is the main
cause of unsafe behavior and safety performance degradation. However, few studies have …

In this paper, we present the design and implementation of a wireless, wearable brain
machine interface (BMI) system dedicated to signal sensing and processing for driver …