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 ...
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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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PLEASE NOTE, WE DO NOT SHIP TO DENMARK. New Book. Shipped from UK in 4 to 14 days. Established seller since 2000. Please note we cannot offer an expedited shipping service from the UK.
Choose your shipping method in Checkout. Costs may vary based on destination.
Seller's Description:
PLEASE NOTE, WE DO NOT SHIP TO DENMARK. New Book. Shipped from UK in 4 to 14 days. Established seller since 2000. Please note we cannot offer an expedited shipping service from the UK.
