This paper presents a method to recover task-related sources from a multi-class BrainComputer Interface (BCI) based on motor imagery. Our method gathers two common approaches to tackle the multi-class problem: 1) the supervised approach of Common Spatial Pattern (CSP) to discriminate between different tasks; 2) the criterion of statistical independence of non-stationary sources used in Independ...

The investigation of innovative HumanComputer Interfaces (HCI) provides a challenge for future multimedia research and development. BrainComputer Interfaces (BCI) exploit the ability of human communication and control bypassing the classical neuromuscular communication channels. In general, BCIs offer a possibility of communication for people with severe neuromuscular disorders, such as Amyotro...

Brain Computer Interface (BCI) has been recently increased in research. Functional Near Infrared Spectroscope (fNIRs) is one the latest technologies which utilize light in the near-infrared range to determine brain activities. Because near infrared technology allows design of safe, portable, wearable, non-invasive and wireless qualities monitoring systems, fNIRs monitoring of brain hemodynamics...

We present a novel typewriter application ‘Hex-o-Spell’ that is specifically tailored to the characteristics of direct brain-to-computer interaction. The high bandwidth at which a user may perceive information from the display is used in an appealing visualization based on hexagons. On the other hand the control of the application is possible at low bandwidth using only two control commands (me...

Ambient intelligence has acquired a relevant presence in assistive technologies. Context-awareness, the ability to perceive situations and to act providing suitable responses, plays a key role in such presence. BrainAble, an ongoing European project, aims at raising the autonomy of people with functional diversity, facilitating and enhancing the interaction with their environment. Brain-compute...

Brain imaging techniques contribute to developments of neuro-economics and braincomputer interface (BCI). Although most of BCI systems were designed for assisting human motions, some BCIs were proposed as a system for assisting individual decision-making. However, due to lack of accuracy that the BCIs discriminate targets, their performance is still not enough for practical use. Hence, we propo...

This paper presents the results of a user experiment designed to measure the impact of visual distractions when making use of steady-state visually evoked potential (SSVEP)-based braincomputer interfaces (BCI). Also the user experience when using such an interface is measured. A set of small applications was developed to simulate such a BCI using a gaze tracker. The impact of visual distraction...

The Common Spatial Pattern (CSP) algorithm is a popular method for calculating spatial lters in motor imagery braincomputer interface system. However, the performance of CSP is in uenced by several factors such as the selection of channels, time window length, frequency band and etc.. One of the existing problems is that some above parameters for CSP is tuned manually in most of papers in the l...

Therapeutic methods based on efferent signals from the patients’ brain have been studied extensively in the field of brain-computer interfaces and applied to paralysed and stroke patients. Invasive stimulation is used as a therapeutic tool for patients with Parkinson disease, intractable chronic pain and other neurological diseases. We give a short review of currently used applications for cort...

In this publication, we present a Motor Imagery (MI) based BrainComputer Interface (BCI) for neurologic rehabilitation. The BCI is able to control two different feedback devices. The first one is a rehabilitation robot, moving the fingers of the affected hand according to the detected MI. The second one presents feedback via virtual reality (VR) to the subject. The latter one visualizes two han...