کد مقاله | کد نشریه | سال انتشار | مقاله انگلیسی | نسخه تمام متن |
---|---|---|---|---|
4336719 | 1295225 | 2008 | 9 صفحه PDF | دانلود رایگان |
عنوان انگلیسی مقاله ISI
Machine learning for real-time single-trial EEG-analysis: From brain–computer interfacing to mental state monitoring
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کلمات کلیدی
موضوعات مرتبط
علوم زیستی و بیوفناوری
علم عصب شناسی
علوم اعصاب (عمومی)
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چکیده انگلیسی
Machine learning methods are an excellent choice for compensating the high variability in EEG when analyzing single-trial data in real-time. This paper briefly reviews preprocessing and classification techniques for efficient EEG-based brain–computer interfacing (BCI) and mental state monitoring applications. More specifically, this paper gives an outline of the Berlin brain–computer interface (BBCI), which can be operated with minimal subject training. Also, spelling with the novel BBCI-based Hex-o-Spell text entry system, which gains communication speeds of 6–8 letters per minute, is discussed. Finally the results of a real-time arousal monitoring experiment are presented.
ناشر
Database: Elsevier - ScienceDirect (ساینس دایرکت)
Journal: Journal of Neuroscience Methods - Volume 167, Issue 1, 15 January 2008, Pages 82–90
Journal: Journal of Neuroscience Methods - Volume 167, Issue 1, 15 January 2008, Pages 82–90
نویسندگان
Klaus-Robert Müller, Michael Tangermann, Guido Dornhege, Matthias Krauledat, Gabriel Curio, Benjamin Blankertz,