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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| Format: | Final Year Project |
| Language: | English |
| Published: |
2015
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| Online Access: | http://hdl.handle.net/10356/63882 |
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| Institution: | Nanyang Technological University |
| Language: | English |
| Summary: | 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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