Significance: Functional near-infrared spectroscopy (fNIRS) enables the measurement of
brain activity noninvasively. Optical neuroimaging with fNIRS has been shown to be …

In this paper, we have proposed a novel control strategy for a quadcopter control using brain
signals. A brain-computer interface (BCI) technology is developed using hybrid …

Objective. Despite the high prevalence of non-motor impairments reported in patients with
amyotrophic lateral sclerosis (ALS), little is known about the functional neural markers …

This paper proposes an electroencephalogram (EEG) based mental arithmetic task
classification using a stacked long short-term memory (LSTM) architecture for brain …

We investigated the use of a multimodal functional neuroimaging system in quantifying
mental workload of healthy human volunteers. We recorded behavioral performance …

Abstract The Hybrid-Brain Computer Interface (BCI) has shown improved performance,
especially in classifying multi-class data. Two non-invasive BCI modules are combined to …

For BCI systems, it is important to have an accurate and less complex architecture to control
a device with enhanced accuracy. In this paper, a novel methodology for more accurate …

Tens of millions of people suffer from depression worldwide. It is urgent to explore an
effective method for diagnosing depression. This study developed a novel of multimodal …

One of the pivotal issues which must be tackled when an effective brain-computer interface
(BCI) is to be designed, is to reduce the enormous space of features extracted from fNIRS …

Multimodal brain–computer interfaces (BCIs) that combine electrical features from
electroencephalography (EEG) and hemodynamic features from functional near-infrared …