Title: Wireless autonomic neural network in EEG signal extraction management

Authors: Chiemela Onunka; Glen Bright; Riaan Stopforth

Addresses: Mechanical Engineering Department, University of KwaZulu-Natal, 4041, Durban, South Africa ' Mechanical Engineering Department, University of KwaZulu-Natal, 4041, Durban, South Africa ' Mechanical Engineering Department, University of KwaZulu-Natal, 4041, Durban, South Africa

Abstract: The use of autonomic neural network in the control of smart machines using bio-signals has created the need for advancements in autonomic neural network in EEG signal extraction management. The advancements made in using human cognition for robotic control have increased possibilities once imagined in the field of robotics. The focus of the study is on the application of wireless autonomic neural network in EEG signal extraction. The paper discusses the importance of autonomic neural network in brainwave extraction, transmission and management for robotic control. The prediction and extraction process is an important component of the EEG autonomic neural network.

Keywords: autonomic neural networks; EEG signal extraction; EEG signal management; smart machines; biosignals; electroencephalography; robot control; intelligent robots.

DOI: 10.1504/IJCAT.2014.063905

International Journal of Computer Applications in Technology, 2014 Vol.50 No.1/2, pp.18 - 29

Received: 08 May 2021
Accepted: 12 May 2021

Published online: 25 Jul 2014 *

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