Rapid prototyping of an EEG-based brain-computer interface (BCI)

Abstract

The Electroencephalogram (EEG) is modified by motor imagery and can be used by patients with severe motor impairments (e.g. late stage of Amyotrophic Lateral Sclerosis) to communicate with their environment. Such a direct connection between the brain and the computer is known as an EEGbased brain-computer interface (BCI). This paper describes a new type of BCI system that uses Rapid Prototyping to enable a fast transition of various types of parameter estimation and classification algorithms to real-time implementation and testing. Rapid Prototyping is possible by using Matlab, Simulink and the Real-time Workshop. It is shown how to automate real-time experiments and perform the interplay between on-line experiments and off-line analysis. The system is able to process multiple EEG channels on-line and operates under Windows 95 in real-time on a standard PC without an additional digital signal processor (DSP) board.The BCI can be controlled over the Internet, LAN or modem.This BCI was tested on 3 subjects whose task it was to imagine either left or right hand movement. A classification accuracy between 70 and 95 % could be achieved with two EEG channels after some sessions with feedback using an adaptive autoregressive (AAR) model and linear discriminant analysis (LDA).2

Classifying Event-Related Desynchronization in EEG, ECoG and MEG Signals

“…For a selection of EEG motor imagery studies, see Wolpaw et al (1997); Birch et al (2003);McFarland et al (1997); Guger et al (1999); Dornhege et al (2004a); Lal et al (2004).…”

Recent Trends in EMG-Based Control Methods for Assistive Robots

“…Therefore, in the integration of the human with a robot, the selection of a proper control input signal to reflect the correct motion intention would be very important. So far research is being carried out considering different biological signals such as Electromyography (EMG), Mechnanomyogram (MMG), Electroencephalography (EEG) Electrooculography (EOG) and Electrocorticogram (EcoG) [13,14,15] as the main input signal to the robot controller. Among them, the EMG signal, which is the measurement of the electrical activity of muscles at rest and during contraction, has obtained promising results in the case of controlling robotic prostheses and orthoses by correctly interpreting the human motion intention [16,17].…”

Combining Brain-Computer Interfaces and Haptics: Detecting Mental Workload to Adapt Haptic Assistance

“…For example, BCI-based spellers enable to spell letters by only using brain activity [2]. Another example is the use of BCI to send commands to prostheses, for example to open and close prostheses by imagination of hand movements [3]. BCI can also be used by healthy users, for instance for enhancing interaction with video games [4].…”