Advancing Brain-Computer Interface

A brain-Computer interface (BCI), also known as brain-machine interface (BMI), utilizes neurophysiological correlates of voluntary cognitive tasks to facilitate direct communication between human brain and computing devices without the involvement of neuro-muscular pathways. This emerging research area has the potential to contribute significantly to enhancing the accessibility of ICT systems for the elderly and disabled people. It is, in general, progressing in two main areas: BCI for communication for improving independence & quality of life of severely disabled people such as sufferers of motor neurone disease (MND) and spinal chord injury, and BCI for rehabilitation purposes, e.g. motor restoration in paralysis due to stroke. Current BCI systems however, lack sufficient robustness and the performance variability among users is quite high. One of the critical limitations is because of the non-stationary characteristics of the brain’s neurophysiological responses, which makes it very hard to extract timeinvariant stable features unique to voluntary cognitive tasks. Under these inherent limitations, devising realworld BCI applications for constant use is a real challenge. The workshop aims to discuss recent developments in robust BCI design and practical real-world applications made possible through advances in one or more BCI design phases: paradigm design, invasive and non-invasive brain signal selection and acquisition, signal pre-processing, feature selection and extraction, feature classification, and application