Rehabilitation through Brain Computer Interfaces - Classification and Feedback Study

Arnau Espinosa, Rupert Ortner, Danut Irimia, Christoph Guger

2012

Abstract

A Brain-Computer Interface (BCI) is a tool for reading and interpreting signals recorded directly from the user’s brain. Most brain-computer interfaces (BCI) are based on one of three types of electroencephalogram (EEG) signals: P300s, steady-state visually evoked potentials (SSVEPs), and event-related desynchronization (ERD). EEG is typically recorded non-invasively using active or passive electrodes mounted on the human scalp. In recent years, a variety of different BCIs for communication and control applications were developed. A quite new and promising idea is to utilize BCIs as a tool for stroke rehabilitation. The BCI detects the user's movement intention and provides online feedback to train the affected parts of the body to restore effective movement. This publication tries to optimize current BCI-strategies for stroke rehabilitation using immersive 3-D virtual reality feedback (VRFB). Other work has continued to show that higher density electrode systems can reveal subtleties of brain dynamics that are not obvious with fewer electrodes. Hence, we used a larger electrode montage than typical BCI studies.

Paper Citation

in Harvard Style

Espinosa A., Ortner R., Irimia D. and Guger C. (2012). Rehabilitation through Brain Computer Interfaces - Classification and Feedback Study . In Proceedings of the 4th International Joint Conference on Computational Intelligence - Volume 1: SSCN, (IJCCI 2012) ISBN 978-989-8565-33-4, pages 692-697. DOI: 10.5220/0004183906920697

in Bibtex Style

@conference{sscn12,
author={Arnau Espinosa and Rupert Ortner and Danut Irimia and Christoph Guger},
title={Rehabilitation through Brain Computer Interfaces - Classification and Feedback Study},
booktitle={Proceedings of the 4th International Joint Conference on Computational Intelligence - Volume 1: SSCN, (IJCCI 2012)},
year={2012},
pages={692-697},
publisher={SciTePress},
organization={INSTICC},
doi={10.5220/0004183906920697},
isbn={978-989-8565-33-4},
}

in EndNote Style

TY - CONF
JO - Proceedings of the 4th International Joint Conference on Computational Intelligence - Volume 1: SSCN, (IJCCI 2012)
TI - Rehabilitation through Brain Computer Interfaces - Classification and Feedback Study
SN - 978-989-8565-33-4
AU - Espinosa A.
AU - Ortner R.
AU - Irimia D.
AU - Guger C.
PY - 2012
SP - 692
EP - 697
DO - 10.5220/0004183906920697