IJE TRANSACTIONS B: Applications Vol. 31, No. 5 (May 2018) 719-728    Article in Press

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R. Ingle and R. Awale
( Received: September 24, 2017 – Accepted in Revised Form: December 28, 2017 )

Abstract    In this paper, unique approach is presented for the electroencephalography (EEG) signals analysis. This is based on Eigen values distribution of a matrix which is called as scaled Hankel matrix. This gives us a way to find out the number of Eigen values essential for noise reduction and extraction of signal in singular spectrum analysis. This paper gives us an approach to classify the EEG signals between normal condition (Controlled) and meditation condition, the extraction of various patterns, the EEG signal filtering and the noise removal from the signals. Different parameters are used as features for classification during subject’s normal EEG segments and at the time of practicing Meditation. The results showed positive approach for noise removal in both EEG signals.


Keywords    Singular Spectrum Analysis; Eigen values; EEG


چکیده    در این مقاله روش منحصر به فرد برای تحلیل سیگنال الکتروانسفالوگرافی (EEG) ارائه شده است. این براساس توزیع ارزش Eigen یک ماتریس است که به عنوان ماتریس مقیاس Hankel نامیده می شود. این ماتریس به ما امکان می دهد تا تعداد مقادیر Eigen مورد نیاز برای کاهش نویز و استخراج سیگنال در تجزیه و تحلیل طیف منحصر به فرد را پیدا کند. این مقاله روشی را برای طبقه بندی سیگنال های EEG بین وضعیت عادی (کنترل شده) و شرایط مراقبه، استخراج الگوهای مختلف، فیلتر کردن سیگنال EEG و حذف نویز از سیگنال ارائه می دهد. پارامترهای مختلف به عنوان ویژگی هایی برای طبقه بندی در بخش های طبیعی EEG طبیعی و در زمان تمرین مدیتیشن استفاده می شود. نتایج نشان داد که روش حذف صوتی در هر دو سیگنال EEG مثبت است.


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