Motor imagery task classification using a signal-dependent orthogonal transform based feature extraction

Mostefa Mesbah, Aida Khorshidtalab, Hamza Baali, Ahmed Al-Ani*

*المؤلف المقابل لهذا العمل

نتاج البحث: Conference contribution

5 اقتباسات (Scopus)

ملخص

In this paper, we present the results of classifying electroencephalographic (EEG) signals into four motor imagery tasks using a new method for feature extraction. This method is based on a signal-dependent orthogonal transform, referred to as LP-SVD, defined as the left singular vectors of the LPC filter impulse response matrix. Using a logistic tree based model classifier, the extracted features are mapped into one of four motor imagery movements, namely left hand, right hand, foot, and tongue. The proposed technique-based classification performance was benchmarked against those based on two widely used linear transform for feature extraction methods, namely discrete cosine transform (DCT) and adaptive autoregressive (AAR). By achieving an accuracy of 67.35 %, the LP-SVD based method outperformed the other two by large margins (+25 % compared to DCT and +6 % compared to AAR-based methods).

اللغة الأصليةEnglish
عنوان منشور المضيفNeural Information Processing - 22nd International Conference, ICONIP 2015, Proceedings
المحررونWeng Kin Lai, Qingshan Liu, Tingwen Huang, Sabri Arik
ناشرSpringer Verlag
الصفحات1-9
عدد الصفحات9
رقم المعيار الدولي للكتب (المطبوع)9783319265346
المعرِّفات الرقمية للأشياء
حالة النشرPublished - 2015
الحدث22nd International Conference on Neural Information Processing, ICONIP 2015 - Istanbul, Turkey
المدة: نوفمبر ٩ ٢٠١٥نوفمبر ١٢ ٢٠١٥

سلسلة المنشورات

الاسمLecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
مستوى الصوت9490
رقم المعيار الدولي للدوريات (المطبوع)0302-9743
رقم المعيار الدولي للدوريات (الإلكتروني)1611-3349

Other

Other22nd International Conference on Neural Information Processing, ICONIP 2015
الدولة/الإقليمTurkey
المدينةIstanbul
المدة١١/٩/١٥١١/١٢/١٥

ASJC Scopus subject areas

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