Event-related desynchronization/synchronization patterns during right/left motor imagery (MI) are effective features for an electroencephalogram-based brain-computer interface (BCI). As MI tasks are subject-specific, selection of subject-specific discriminative frequency components play a vital role in distinguishing these patterns. This paper proposes a new discriminative filter bank (FB) comm...

This paper summarizes the presentations and discussions at a workshop held during the Fourth International BCI Meeting charged with reviewing and evaluating the current state, limitations and future development of P300-based brain-computer interface (P300-BCI) systems. We reviewed such issues as potential users, recording methods, stimulus presentation paradigms, feature extraction and classifi...

Brain-computer interface (BCI) is combination of hardware and software systems that allows the severely or partially disabled persons to communicate with their surroundings. The study of brain activities precisely is an important step in BCI system. Many invasive and non-invasive neuro-imaging techniques are being conducted. In this paper, a comparative analysis of these different approaches ha...

The paper presents the Brain-Computer Interface (BCI) based home control system. The proposed system isused to facilitate the handicapped and needy persons. Neurosky headset is used to detect Electroencephalogram (EEG) signal from brain activity. Recognizing the brain activity for certain thoughts and eye blinking patterns, we managed to correlate them with the switching and regulation of certa...

Brain computer interface (BCI) research, carried out in our group, has focused on two aspects. In terms of signal processing, we focused on improving BCI performance by using advanced probabilistic machine learning approaches. On the other hand even the most advance signal processing can only recover information which is actually contained in the data. Hence a second central research direction ...

This paper discusses a time-dependent classification approach for single trial recognition of spatial covert visual attention for Brain–Computer Interface (BCI). Covert visual attention is a natural and intuitive mental task that does not require any external stimulation. The possibility to recognize it from single trials is essential for a future online close-loop BCI. Experimental results sho...

A Brain Computer Interface (BCI) is a communication system that receives neurological signals from the brain and translates them into control commands for electrical (e.g., computer mouse) and electromechanical (e.g., Wheelchair) devices. The development of such systems was intended originally to aid individuals with a condition called locked-in syndrome. Individuals with this condition have lo...

The majority of subjects who attempt to learn control of a brain-computer interface (BCI) can do so with adequate training. Much like when one learns to type or ride a bicycle, BCI users report transitioning from a deliberate, cognitively focused mindset to near automatic control as training progresses. What are the neural correlates of this process of BCI skill acquisition? Seven subjects were...

This thesis describes an SSVEP-based BCI implemented as a practical part of this work. One possible usage of a BCI that efficiently implements a communication channel between the brain and an external device would be to help severely disabled people to control devices that currently require pushing buttons, for example an electric wheelchair. The BCI implemented as a part of this thesis uses wi...

Abstract The recovery of hand motor function can effectively improve the living standard stroke patients and relieve their psychological anxiety. Traditional physical rehabilitation training is unable to target cause loss; therefore, effect not ideal. objective this study propose a system combining brain–computer interface (BCI), soft glove virtual reality (VR), explore its effectiveness on mov...