Platform for analyzing multi-tasking capabilities during BCI operation
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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 ...
This paper is aimed to introduce IDIAP Brain Computer Interface (IBCI) research that successfully applied Ambience Intelligence (AmI) principles in designing intelligent brain-machine interactions. We proceed through IBCI applications describing how machin ...
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 ...
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 ...
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 ...
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 ...