کنترل صندلی چرخ‌دار بر پایه سیگنال‌های EEG به‌وسیله واسط مغز و ماشین

نوع مقاله : مقاله پژوهشی

نویسندگان

دانشگاه تبریز - دانشکده مهندسی برق و کامپیوتر

چکیده

چالش اصلی سیستم‌های واسط مغز و ماشین (BCI) دوکلاسه، پایین بودن پهنای باند کانال ارتباطی آن‌ها است. مخصوصاً این مسئله برای کنترل دستگاه‌های کمکی شبیه صندلی چرخ‌دار یا ربات متحرک که نیازمند دستورات حرکتی چندگانه هستند، مهم است.  
هدف این تحقیق، کنترل کردن صندلی چرخ‌دار توسط سیستم واسط مغز و ماشین با استفاده از سیگنال‌های (EEG) مبتنی بر الگوهای ذهنی (SSVEP) است. این کنترل ذهنی باید مخصوصاً برای افراد ناتوان امنیت بالا و دقت قابل قبولی داشته باشد. سیگنال ذهنی SSVEP پنجره‌گذاری می‌شود و سپس در مرحله پیش‌پردازش برای کاهش نویز و مصنوعات از یک فیلتر میان‌گذر عبور داده می‌شود.استخراج ویژگی از سه روش (FFT)، (IT-CCA) و روش بهبودیافته مبتنی بر ترکیب IT-CCA و فیلتربانک انجام می‌شود. محاسبه دقت و نرخ انتقال اطلاعات هر سه روش نشان می‌دهد که روش بهبودیافته مبتنی بر ترکیب IT-CCA و فیلتربانک بهترین عملکرد را دارد. در پایان صندلی چرخ‌دار و محیط فیزیکی آن در نرم‌افزار شبیه‌سازی ربات Webots طراحی و با ارسال و اجرای دستورات دوازده‌گانه مانور حرکتی صندلی چرخ‌دار بررسی می‌شود.

کلیدواژه‌ها

عنوان مقاله [English]

EEG-Based Wheelchair Control Through a Brain–Computer Interface

نویسندگان [English]

  • Khadijeh Hassanpour
  • Hadi Seyadarabi
  • Sabalan Daneshvar
Faculty of Electrical and Computer Engineering, University of Tabriz
چکیده [English]

A major challenge in two-class brain-computer interface (BCI) systems is the low bandwidth of the communication channel, especially this is important for controlling assistive devices such as a wheelchair or a mobile robot which requires multiple motion commands. The goal of this research is EEG-based wheelchair control through a SSVEP-based BCI. This brain control must provide high security and accuracy particularly for disabled people. SSVEP brain signal is windowed and for reducing noise and artifacts passed through a bandpass filter in preprocessing stage. Three methods including FFT algorithm, IT-CCA and an improved method based on combination of IT-CCA and Filter-bank are used for feature extraction. Computing Accuracy and ITR for three methods represents that improved method based on combination of IT-CCA and Filter-bank has the best performance. Finally the wheelchair and its physical environment are designed by Webots robotic simulation software and by sending and performing multiple commands, wheelchair motivation maneuver is completed.

کلیدواژه‌ها [English]

  • Brain-computer interface (BCI)
  • Electroencephalography (EEG)
  • steady state visual evoked potential (SSVEP)
  • brain-controlled mobile robot
  • wheelchair

مراجع

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