مشاهده مشخصات مقاله
A Technique Based on Chaos for Brain Computer Interfacing
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نویسنده (ها) |
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A. Banitalebi
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S. K. Setarehdan
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G. A. Hossein-Zadeh
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مربوط به کنفرانس |
چهاردهمین کنفرانس بینالمللی سالانه انجمن کامپیوتر ایران |
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چکیده |
A user of Brain Computer Interface (BCI) system
must be able to control external computer devices with
brain activity. Although the proof-of-concept was
given decades ago, the reliable translation of user
intent into device control commands is still a major
challenge. There are problems associated with
classification of different BCI tasks. In this paper we
propose the use of chaotic indices of the BCI. We use
largest Lyapunov exponent, mutual information,
correlation dimension and minimum embedding
dimension as the features for the classification of EEG
signals which have been released by BCI Competition
IV. A multi-layer Perceptron classifier and a KMSVM(
support vector machine classifier based on kmeans
clustering) is used for classification process,
which lead us to an accuracy of 95.5%, for
discrimination between two motor imagery tasks. |
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قیمت |
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برای اعضای سایت : ۱٠٠,٠٠٠ ریال
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برای دانشجویان عضو انجمن : ۲٠,٠٠٠ ریال
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برای اعضای عادی انجمن : ۴٠,٠٠٠ ریال
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خرید مقاله
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