Brain-Computer Interfaces for Goal orientated Control of a Virtual Smart Home Environment

被引:0
作者
Edlinger, Guenter [1 ]
Holzner, Clemens [1 ]
Guger, Christoph [1 ]
Groenegress, C. [2 ]
Slater, Mel [2 ]
机构
[1] G Tec Med Engn GmbH, Guger Technol OEG, Graz, Austria
[2] Univ Politecn Cataluna, Ctr Realitat Virtual CRV, Barcelona, Spain
来源
2009 4TH INTERNATIONAL IEEE/EMBS CONFERENCE ON NEURAL ENGINEERING | 2009年
关键词
Brain-Computer Interface; P300; evoked potential; Virtual Environment;
D O I
暂无
中图分类号
R318 [生物医学工程];
学科分类号
0831 ;
摘要
A. brain-computer interface (BCI) is a new communication channel between the human brain and a digital computer. The ambitious goal of a BCI is finally the restoration of movements, communication and environmental control for handicapped people. However, in more recent research also BCI control in combination with Virtual Environments (VE) gains more and more interest. Within this study we present experiments combining BCI systems and VE for navigation and control purposes just by thoughts. A comparison of the applicability and reliability of different BCI types based on event related potentials (P300 approach) will be presented. In contrast to other BCI approaches yielding only 2-3 degrees of freedom this study is focused on a BCI system that can be realized for Virtual Reality (VR) control with a high degree of freedom and high information transfer rate. Therefore a P300 based human computer interface has been developed in a VR implementation of a smart home for controlling the environment (television, music, telephone calls) and navigation control in the house. Results show that the new P300 based BCI system allows a very reliable control of the VR system. Of special importance is the possibility to select very rapidly the specific command out of many different choices. This eliminates the usage of decision trees as previously done with BCI systems.
引用
收藏
页码:456 / +
页数:2
相关论文
共 8 条
  • [1] A spelling device for the paralysed
    Birbaumer, N
    Ghanayim, N
    Hinterberger, T
    Iversen, I
    Kotchoubey, B
    Kübler, A
    Perelmouter, J
    Taub, E
    Flor, H
    [J]. NATURE, 1999, 398 (6725) : 297 - 298
  • [2] EDLINGER G, 2005, ENG MED BIOL SOC 200, P5347
  • [3] Rapid prototyping of an EEG-based brain-computer interface (BCI)
    Guger, C
    Schlögl, A
    Neuper, C
    Walterspacher, D
    Strein, T
    Pfurtscheller, G
    [J]. IEEE TRANSACTIONS ON NEURAL SYSTEMS AND REHABILITATION ENGINEERING, 2001, 9 (01) : 49 - 58
  • [4] A comparison of classification techniques for the P300 Speller
    Krusienski, Dean J.
    Sellers, Eric W.
    Cabestaing, Francois
    Bayoudh, Sabri
    McFarland, Dennis J.
    Vaughan, Theresa M.
    Wolpaw, Jonathan R.
    [J]. JOURNAL OF NEURAL ENGINEERING, 2006, 3 (04) : 299 - 305
  • [5] McMillan G.R., 1995, P RESNA 95 ANN C VAN, P693
  • [6] Robust classification of EEG signal for brain-computer interface
    Thulasidas, M
    Guan, C
    Wu, JK
    [J]. IEEE TRANSACTIONS ON NEURAL SYSTEMS AND REHABILITATION ENGINEERING, 2006, 14 (01) : 24 - 29
  • [7] Vaughan T M, 1996, IEEE Trans Rehabil Eng, V4, P425, DOI 10.1109/86.547945
  • [8] ZHANG H, 2005, ENG MED BIOL SOC 200, P5347