A brain-computer interface (BCI) is a system that allows an individual to communicate with computer or other external device using brain activity alone. Electroencephalography (EEG) common approach for detecting in BCI systems, as it provides non-invasive measure of high temporal resolution. Deep learning methods, such convolutional neural networks (CNNs), have been applied the analysis EEG dat...

Brain-Computer Interface (BCI) uses brain signals in order to provide a new method for communication between human and outside world. Feature extraction, selection and classification are among the main matters of concerns in signal processing stage of BCI. In this article, we present our findings about the most effective features and classifiers in some brain tasks. Six different groups of clas...

With the development of medical research and Human Computer Interaction, Brain Computer Interface (BCI), which is an interesting intersection between these two fields, is becoming a more and more popular topic. Various researches and commercial products have been created to support the applications of Brain Computer Interface. In this paper, a BCI based games is introduced to help people traini...

Brain Computer Interface (BCI) is a device that enables use of brain’s neural activity to communicate with others or other machines without direct physical contact. Brain Computer interface was initially used to help people affected by motor neuron diseases. BCI is accomplished through Electroencephalography (EEG) that measures the electrical activity produced by the neurons in the brain. The e...

A Brain Computer Interface (BCI) provides a communication path between human brain and the computer system. With the advancement in the areas of information technology and neurosciences, there has been a surge of interest in turning fiction into reality. The major goal of BCI research is to develop a system that allows disabled people to communicate with other persons and helps to interact with...

we present a novel and e±cient scheme that selects a minimal set of effective features and channels for detecting the p300 component of the event-related potential in the brain-computer interface (bci) paradigm. for obtaining a minimal set of effective features, we take the truncated coe±cients of discrete daubechies 4 wavelet, and for selecting the effective eeg channels, we utilize an improve...

We present the self-paced 3-class Graz brain-computer interface (BCI) which is based on the detection of sensorimotor electroencephalogram (EEG) rhythms induced by motor imagery. Self-paced operation means that the BCI is able to determine whether the ongoing brain activity is intended as control signal (intentional control) or not (non-control state). The presented system is able to automatica...

The study presented explores the extent to which tactile stimuli delivered to the ten digits of a BCI-naive subject can serve as a platform for a brain computer interface (BCI) that could be used in an interactive application such as robotic vehicle operation. The ten fingertips are used to evoke somatosensory brain responses, thus defining a tactile brain computer interface (tBCI). Experimenta...

In this paper we present an approach to control a real car with brain signals. To achieve this, we use a brain computer interface (BCI) which is connected to our autonomous car. The car is equipped with a variety of sensors and can be controlled by a computer. We implemented two scenarios to test the usability of the BCI for controlling our car. In the first scenario our car is completely brain...

This paper describes the current state of the work aimed towards an affective application of BCI to the task of complex data visual exploration. The developed technological approach exploits the idea of supporting tacit and complex domain-specific knowledge acquisition during the examination of visual images built using large input data sets. The presented experimental research on the complex n...