Continuous EEG classification during motor imagery - Simulation of an asynchronous BCI

被引：187

作者：

Townsend, G ^{[1
]}

Graimann, B

Pfurtscheller, G

机构：

[1] Algoma Univ, Dept Comp Sci, Sault Ste Marie, ON P6A 2G4, Canada

[2] Graz Univ Technol, Inst Biomed Engn, Dept Med Informat, A-8012 Graz, Austria

来源：

IEEE TRANSACTIONS ON NEURAL SYSTEMS AND REHABILITATION ENGINEERING | 2004年 / 12卷 / 02期

关键词：

asynchronous brain-computer interface (BCI); BCI; receiver operating characteristic (ROC); synchronous BCI; true-false (TF) differences;

D O I：

10.1109/TNSRE.2004.827220

中图分类号：

R318 [生物医学工程];

学科分类号：

0831 ;

摘要：

Nearly all electroencephalogram (EEG)-based brain-computer interface (BCI) systems operate in a cue-paced or synchronous mode. This means that the onset of mental activity (thought) is externally-paced and the EEG has to be analyzed in predefined time windows. In the near future, BCI systems that allow the user to intend a specific mental pattern 'whenever she/he wishes to produce such patterns will also become important. An asynchronous BCI is characterized by continuous analyzing and classification of EEG data. Therefore, it is important to maximize the hits (true positive rate) during an intended mental task and to minimize the false positive detections in the resting or idling state. EEG data recorded during right/left motor imagery is used to simulate an asynchronous BCI. To optimize the classification results,a. refractory period and a dwell time are introduced.

引用

页码：258 / 265

页数：8

共 13 条

[1] A spelling device for the paralysed [J].

Birbaumer, N ;

Ghanayim, N ;

Hinterberger, T ;

Iversen, I ;

Kotchoubey, B ;

Kübler, A ;

Perelmouter, J ;

Taub, E ;

Flor, H .

NATURE, 1999, 398 (6725) :297-298

[2]

Duda R. O., 2000, PATTERN CLASSIFICATI

[3] TALKING OFF THE TOP OF YOUR HEAD - TOWARD A MENTAL PROSTHESIS UTILIZING EVENT-RELATED BRAIN POTENTIALS [J].

FARWELL, LA ;

DONCHIN, E .

ELECTROENCEPHALOGRAPHY AND CLINICAL NEUROPHYSIOLOGY, 1988, 70 (06) :510-523

[4]

Fukunaga K., 1972, Introduction to statistical pattern recognition

[5] Rapid prototyping of an EEG-based brain-computer interface (BCI) [J].

Guger, C ;

Schlögl, A ;

Neuper, C ;

Walterspacher, D ;

Strein, T ;

Pfurtscheller, G .

IEEE TRANSACTIONS ON NEURAL SYSTEMS AND REHABILITATION ENGINEERING, 2001, 9 (01) :49-58

[6] Real-time EEG analysis with subject-specific spatial patterns for a brain-computer interface (BCI) [J].

Guger, C ;

Ramoser, H ;

Pfurtscheller, G .

IEEE TRANSACTIONS ON REHABILITATION ENGINEERING, 2000, 8 (04) :447-456

[7] A direct brain interface based on event-related potentials [J].

Levine, SP ;

Huggins, JE ;

BeMent, SL ;

Kushwaha, RK ;

Schuh, LA ;

Rohde, MM ;

Passaro, EA ;

Ross, DA ;

Elisevich, KV ;

Smith, BJ .

IEEE TRANSACTIONS ON REHABILITATION ENGINEERING, 2000, 8 (02) :180-185

[8] A brain-controlled switch for asynchronous control applications [J].

Mason, SG ;

Birch, GE .

IEEE TRANSACTIONS ON BIOMEDICAL ENGINEERING, 2000, 47 (10) :1297-1307

[9] Designing optimal spatial filters for single-trial EEG classification in a movement task [J].

Müller-Gerking, J ;

Pfurtscheller, G ;

Flyvbjerg, H .

CLINICAL NEUROPHYSIOLOGY, 1999, 110 (05) :787-798

[10] Motor imagery and direct brain-computer communication [J].

Pfurtscheller, G ;

Neuper, C .

PROCEEDINGS OF THE IEEE, 2001, 89 (07) :1123-1134

← 1 2 →