EEG Artefact Identification and Extraction in Autonomic Network
For Future Control of Semi-Autonomous Systems
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The main contribution of the book was the identification, extraction and classification of electroencephalographic (EEG) artefacts in controlling a robotic hand. The specific contribution made in the research included the development of augmented EEG signal and EEG artefact extraction process using mathematical models. A BCI system was augmented in autonomic wireless neural network activated by various EEG artefacts. Robotic control command codes were developed and they were modular in their application strategy. This was consolidated with adequate software and hardware architecture which were...
The main contribution of the book was the identification, extraction and classification of electroencephalographic (EEG) artefacts in controlling a robotic hand. The specific contribution made in the research included the development of augmented EEG signal and EEG artefact extraction process using mathematical models. A BCI system was augmented in autonomic wireless neural network activated by various EEG artefacts. Robotic control command codes were developed and they were modular in their application strategy. This was consolidated with adequate software and hardware architecture which were reconfigurable and leveraged using neuro-symbolic behaviour language in controlling the robotic system
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