کد مقاله کد نشریه سال انتشار مقاله انگلیسی نسخه تمام متن
6282667 1615145 2013 6 صفحه PDF دانلود رایگان
عنوان انگلیسی مقاله ISI
Classification of functional near-infrared spectroscopy signals corresponding to the right- and left-wrist motor imagery for development of a brain-computer interface
ترجمه فارسی عنوان
طبقه بندی سیگنال های اسپکتروسکوپی نزدیک به مادون قرمز که مربوط به تصاویر حرکتی راست و چپ مچ دست است برای توسعه یک رابط مغز و کامپیوتر
موضوعات مرتبط
علوم زیستی و بیوفناوری علم عصب شناسی علوم اعصاب (عمومی)
چکیده انگلیسی
This paper presents a study on functional near-infrared spectroscopy (fNIRS) indicating that the hemodynamic responses of the right- and left-wrist motor imageries have distinct patterns that can be classified using a linear classifier for the purpose of developing a brain-computer interface (BCI). Ten healthy participants were instructed to imagine kinesthetically the right- or left-wrist flexion indicated on a computer screen. Signals from the right and left primary motor cortices were acquired simultaneously using a multi-channel continuous-wave fNIRS system. Using two distinct features (the mean and the slope of change in the oxygenated hemoglobin concentration), the linear discriminant analysis classifier was used to classify the right- and left-wrist motor imageries resulting in average classification accuracies of 73.35% and 83.0%, respectively, during the 10 s task period. Moreover, when the analysis time was confined to the 2-7 s span within the overall 10 s task period, the average classification accuracies were improved to 77.56% and 87.28%, respectively. These results demonstrate the feasibility of an fNIRS-based BCI and the enhanced performance of the classifier by removing the initial 2 s span and/or the time span after the peak value.
ناشر
Database: Elsevier - ScienceDirect (ساینس دایرکت)
Journal: Neuroscience Letters - Volume 553, 11 October 2013, Pages 84-89
نویسندگان
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