EEG based mind controlled car
This project describes the process to design and implementation of real time application for Extreme Learning Machine on Brain-Computer interface area. The ELM was proposed by Dr. Huang GB in NTU, which is Single-hidden layer feed forward network can be applied as a reliable and efficiency classifie...
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sg-ntu-dr.10356-638822023-07-07T16:27:08Z EEG based mind controlled car Li, Yue Lin Zhiping Huang Guangbin School of Electrical and Electronic Engineering BMW DRNTU::Engineering::Electrical and electronic engineering This project describes the process to design and implementation of real time application for Extreme Learning Machine on Brain-Computer interface area. The ELM was proposed by Dr. Huang GB in NTU, which is Single-hidden layer feed forward network can be applied as a reliable and efficiency classifier in many different area. The project worked closely with the research team in NTU to conduct the FBCSP feature extraction for Motor Image which aim to differentiate different types of brain signal when subject “thinking” left or right. And also apply this extracted feature to ELM in order to classify it in real time. This project can match the feature in real time with accuracy around 90%. Furthermore, in order to demo the result, we built a remote control car which controlled by the classification result from ELM classifier. Bachelor of Engineering 2015-05-19T09:23:46Z 2015-05-19T09:23:46Z 2015 2015 Final Year Project (FYP) http://hdl.handle.net/10356/63882 en Nanyang Technological University 53 p. application/pdf |
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DRNTU::Engineering::Electrical and electronic engineering Li, Yue EEG based mind controlled car |
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This project describes the process to design and implementation of real time application for Extreme Learning Machine on Brain-Computer interface area. The ELM was proposed by Dr. Huang GB in NTU, which is Single-hidden layer feed forward network can be applied as a reliable and efficiency classifier in many different area. The project worked closely with the research team in NTU to conduct the FBCSP feature extraction for Motor Image which aim to differentiate different types of brain signal when subject “thinking” left or right. And also apply this extracted feature to ELM in order to classify it in real time. This project can match the feature in real time with accuracy around 90%. Furthermore, in order to demo the result, we built a remote control car which controlled by the classification result from ELM classifier. |
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Lin Zhiping |
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Lin Zhiping Li, Yue |
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Final Year Project |
author |
Li, Yue |
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Li, Yue |
title |
EEG based mind controlled car |
title_short |
EEG based mind controlled car |
title_full |
EEG based mind controlled car |
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EEG based mind controlled car |
title_full_unstemmed |
EEG based mind controlled car |
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eeg based mind controlled car |
publishDate |
2015 |
url |
http://hdl.handle.net/10356/63882 |
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1772828775244890112 |