Brain Imaging and Machine Learning for Brain-Computer Interface

Abstract

Human-computer interfaces are in continuous development, from keyboard, mouse, touch screen, to voice dictation, gesture recognition, etc. The aim is to facilitate the interaction between the human brain and the resources offered by a machine or a computer. Recently, a wider interest has emerged in directly interfacing the brain and the computer. The development of methods that combine the nervous system with artificial devices is attracting a growing interest from clinical research, because the interaction between brain and machines may lead to novel prosthetic devices or to a more efficient use of computer resources by breaking the barriers imposed at present by the classical human-machine interfaces. Individuals with impaired motor control may be disabled in the performance of their daily activities. Their motor performance, however, can be supported by artificial motor control systems. Such motor support systems may also assist healthy individuals in performing their tasks. One can also imagine interacting with different systems in parallel, or developing newer software tools without the need to physically typing the code.