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Báo cáo hóa học: " Steady-State VEP-Based Brain-Computer Interface Control in an Immersive 3D Gaming Environment"

Tuyển tập báo cáo các nghiên cứu khoa học quốc tế ngành hóa học dành cho các bạn yêu hóa học tham khảo đề tài: Steady-State VEP-Based Brain-Computer Interface Control in an Immersive 3D Gaming Environment | EURASIP Journal on Applied Signal Processing 2005 19 3156-3164 2005 Hindawi Publishing Corporation Steady-State VEP-Based Brain-Computer Interface Control in an Immersive 3D Gaming Environment E. C. Lalor 1 S. P. Kelly 1 2 C. Finucane 3 R. Burke 4 R. Smith 1 R. B. Reilly 1 and G. McDarby1 1 School of Electrical Electronic and Mechanical Engineering University College Dublin Belfield Dublin 4 Ireland Emails ed.lalor@ee.ucd.ie ray.smith@ee.ucd.ie richard.reilly@ucd.ie gary.mcdarby@ee.ucd.ie 2 The Cognitive Neurophysiology Laboratory Nathan S. Kline Institute for Psychiatric Research Orangeburg NY 10962 USA Email skelly@nki.rfmh.org 3 Medical Physics and Bioengineering St. James s Hospital P. O. Box 580 Dublin 8 Ireland Email cfinucane@stjames.ie 4EOC Operations Center Microsoft Corporation Sandyford Industrial Estate Dublin 18 Ireland Email robert.burke@gmail.com Received 2 February 2004 Revised 19 October 2004 This paper presents the application of an effective EEG-based brain-computer interface design for binary control in a visually elaborate immersive 3D game. The BCI uses the steady-state visual evoked potential SSVEP generated in response to phasereversing checkerboard patterns. Two power-spectrum estimation methods were employed for feature extraction in a series of offline classification tests. Both methods were also implemented during real-time game play. The performance of the BCI was found to be robust to distracting visual stimulation in the game and relatively consistent across six subjects with 41 of 48 games successfully completed. For the best performing feature extraction method the average real-time control accuracy across subjects was 89 . The feasibility of obtaining reliable control in such a visually rich environment using SSVEPs is thus demonstrated and the impact of this result is discussed. Keywords and phrases EEG BCI SSVEP online classification overt attention. 1. INTRODUCTION The concept of a brain-computer interface BCI stems from a need