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The dream of controlling and guiding computer-based systems using human brain signals has slowly but steadily become a reality. The available technology allows real-time implementation of systems that measure neuronal activity, convert their signals, and t ...
Brain-computer interfaces (BCIs) aim to provide a new channel of communication by enabling the subject to control an external systems by using purely mental commands. One method of doing this without invasive surgical procedures is by measuring the electri ...
To be correctly mastered, Brain-Computer Interfaces (BCIs) need an uninterrupted flow of feedback to the user. This feedback is usually delivered through the visual channel. Our aim is to explore the benefits of vibrotactile feedback during users� traini ...
A Brain-Computer Interface (BCI) allow direct expression of its user�s will by interpreting signals which directly reflect the brain�s activity, thus bypassing the natural efferent channels (nerves and muscles). To be correctly mastered, it is needed t ...
Brain-Computer Interfaces (BCIs) need an uninterrupted flow of feedback to the user, which is usually delivered through the visual channel. Our aim is to explore the benefits of vibrotactile feedback during users� training and control of EEG-based BCI ap ...
Feedback plays an important role when learning to use a Brain-Computer Interface (BCI). Here we compare visual and haptic feedback in a short experiment. By imagining left and right hand movements, six subjects tried to control a BCI with the help of eithe ...
The Electroencephalogram (EEG) is a recording of the electrical potentials generated by brain activity on the scalp. It has been used for decades as a non-invasive tool both in fundamental brain research and in clinical diagnosis. But it is now widely used ...
A Brain-Computer Interface (BCI) is a system that allows its users to control external devices with brain activity. Although the proof-of-concept was given decades ago, the reliable translation of user intent into device control commands is still a major c ...
Brain-computer interfaces, as any other interaction modality based on physiological signals and body channels (e.g., muscular activity, speech and gestures), are prone to errors in the recognition of subject's intent. In this paper we exploit a unique feat ...
Gradient boosting is a machine learning method, that builds one strong classifier from many weak classifiers. In this work, an algorithm based on gradient boosting is presented, that detects event-related potentials in single electroencephalogram (EEG) tri ...