آشکارسازی حرکت پا در سیستم واسط مغز-رایانه کاربرفرما با استفاده از روش طبقه‌بندی مبتنی بر نمایش تنک سیگنال

نوع مقاله: مقاله کامل پژوهشی

نویسندگان

1 دانشجوی دکتری مهندسی پزشکی، گروه بیوالکتریک، دانشکده مهندسی برق و کامپیوتر، دانشگاه تربیت مدرس

2 دانشیار، گروه بیوالکتریک، دانشکده مهندسی برق و کامپیوتر، دانشگاه تربیت مدرس

10.22041/ijbme.2012.13112

چکیده

سیستم‌های BCIکاربرفرما در مقایسه با سیستمهای BCIسنکرون، ارتباط طبیعی‌تر کاربر را با فضای خارج امکان‌پذیر می‌کنند. آشکارسازی بازه‌های وقوع حرکت در سیگنال پیوسته EEGمسأله‌ای کلیدی در طراحی سیستم‌های BCI  کاربرفرما مبتنی بر حرکت است. در این مقاله با استفاده از ویژگی بعد فرکتالی در باندفرکانسی 6 تا 36 هرتز و طراحی طبقه‌بند مبتنی بر نمایش تنک سیگنال، پدیده نورولوژیک همزمانی وابسته به رخداد (ERS)- که بلافاصله پس از وقوع حرکت پا در سیگنال EEGاتفاق می‌افتد- با دقت قابل قبولی از سیگنال پس‌زمینه تشخیص داده شد. روش پیشنهادی این مقاله، بر سیگنال EEGتک کانال ثبت شده از 7 کاربر حین انجام حرکت پا اعمال شد و متوسط=90%   TPRavr  و  FPRavr=5%برای همه افراد بدست آمد.

کلیدواژه‌ها

موضوعات


عنوان مقاله [English]

Foot movement onset detection in self-paced BCIs using sparse representation based classifier

نویسندگان [English]

  • Rahele Mohammadi 1
  • Ali Mahloojifar 2
1 PhD student of Biomedical Engineering, Electrical and Computer Eng. College, Tarbiat Modares University
2 Associate Professor, Biomedical Engineering department, Electrical and Computer Eng. College, Tarbiat Modares University
چکیده [English]

Self-paced BCI systems are more natural for real-life applications since these systems allow the user to control the system when desired. Detection of event periods in continuous EEG signal is one of the most important challenges in designing self-paced BCIs. In this paper, the Event related synchronization (ERS) is extracted from idle EEG signal using fractal dimensions in frequency range from 6 to 36 Hz and sparse representation based classifier. Our proposed method applied on EEG signal recorded during executing foot movement in 7 subjects. The average true positive rate and false positive rate equal to 90% and 5% were achieved.

کلیدواژه‌ها [English]

  • Self-paced Brain Computer Interface
  • Electroencephalogram signal
  • Sparse signal representation
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