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Mean Threshold and Arnn Algorithms for Classification of Eeg Commands

Mean Threshold and Arnn Algorithms for Classification of Eeg Commands

Mean Threshold and Arnn Algorithms for Classification of Eeg Commands
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Mean Threshold and Arnn Algorithms for Classification of Eeg Commands Papeback -

by Thanh Hai Nguyen (Editor)

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VDM Verlag Dr. Mueller Aktiengesellschaft & Co. KG , pp. 52 . Papeback. New.
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Details

  • Title Mean Threshold and Arnn Algorithms for Classification of Eeg Commands
  • Author Thanh Hai Nguyen (Editor)
  • Binding Papeback
  • Condition New
  • Pages 52
  • Volumes 1
  • Language ENG
  • Publisher VDM Verlag Dr. Mueller Aktiengesellschaft & Co. KG
  • Publication date pp. 52
  • Bookseller's Inventory # 6128421133
  • ISBN 9783659572142 / 3659572144
  • Weight 0.2 lbs (0.09 kg)
  • Dimensions 9 x 6 x 0.12 in (22.86 x 15.24 x 0.30 cm)
  • Category Music/Songbooks
  • Quantity available 4

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Reader reviews for Mean Threshold and Arnn Algorithms for Classification of Eeg Commands

From the publisher

This book introduces two Autoregressive Neural Network (ARNN) and mean threshold methods for recognizing eye commands for control of an electrical wheelchair using Electroencephalogram (EEG) technology. Eye movements such as "eyes open", "eyes blink", "glancing left" and "glancing right" . A Hamming low pass filter was applied to remove artifacts of eye signals for extracting the frequency ranges. An AR model was employed to produce coefficients, containing features of the EEG eye signals. The coefficients obtained were inserted the input layer of a neural network model to classify the eye activities. In addition, a mean threshold algorithm was applied for classifying eye movements. In comparison of two recognition methods, the purpose was to find the better one for applying in the electrical wheelchair.
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