Please use this identifier to cite or link to this item: https://hdl.handle.net/10356/63594
Title: EEG based mind controlled
Authors: Wu, Qiu Long
Keywords: DRNTU::Engineering::Computer science and engineering
Issue Date: 2015
Abstract: Brain Computer Interfaces (BCIs) should be one of the most important technological in artificial intelligence. In this project will implement an Electroencephalography (EEG) base BCIs control system by using Filter Bank Common Spatial Pattern (FBCSP) algorithm as a feature extraction method and Extreme Learning Machine (ELM) as a feature classification method. Motor imagery is sensitive for think “left” and “right”. The Common Spatial Pattern (CSP) method is widely use for EEG signal feature extraction. Machine learning ELM method was used for both training and testing stage for classification. The results show 90% accuracy for two classes’ classification “think left” and “think right” and used this two classes’ classification permutation and combination to result output four directions.
URI: http://hdl.handle.net/10356/63594
Rights: Nanyang Technological University
Fulltext Permission: restricted
Fulltext Availability: With Fulltext
Appears in Collections:EEE Student Reports (FYP/IA/PA/PI)

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