EEG based assisted driving system
The EEG technologies have further developments in recent years. The use of EEG is not limited to traditional clinic uses. EEG-based applications become popular topics for the researchers and developers. This project develops an EEG-based assisted driving system to achieve using brainwave to control...
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| Other Authors: | |
| Format: | Final Year Project (FYP) |
| Language: | English |
| Published: |
2014
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| Online Access: | http://hdl.handle.net/10356/61135 |
| _version_ | 1811688997291819008 |
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| author | Liu, Yanling |
| author2 | Huang Guangbin |
| author_facet | Huang Guangbin Liu, Yanling |
| author_sort | Liu, Yanling |
| collection | NTU |
| description | The EEG technologies have further developments in recent years. The use of EEG is not limited to traditional clinic uses. EEG-based applications become popular topics for the researchers and developers. This project develops an EEG-based assisted driving system to achieve using brainwave to control a car. It is an innovation for modern cars. The system translates subject’s brainwave to control commands of turning left, turning right, moving forward and moving reverse. It uses smooth to preprocess the signal, four methods including Sample Entropy, Power Spectrum Density, Spectrogram, and Continuous Wavelet Transform to extract EEG features, and Extreme Learning Machine to classify these features. The system achieves an accuracy of 0.9691 with an online dataset and its success is verified with EEG signals collected by the author via Emotiv. |
| first_indexed | 2024-10-01T05:41:06Z |
| format | Final Year Project (FYP) |
| id | ntu-10356/61135 |
| institution | Nanyang Technological University |
| language | English |
| last_indexed | 2024-10-01T05:41:06Z |
| publishDate | 2014 |
| record_format | dspace |
| spelling | ntu-10356/611352023-07-07T16:32:52Z EEG based assisted driving system Liu, Yanling Huang Guangbin School of Electrical and Electronic Engineering DRNTU::Engineering The EEG technologies have further developments in recent years. The use of EEG is not limited to traditional clinic uses. EEG-based applications become popular topics for the researchers and developers. This project develops an EEG-based assisted driving system to achieve using brainwave to control a car. It is an innovation for modern cars. The system translates subject’s brainwave to control commands of turning left, turning right, moving forward and moving reverse. It uses smooth to preprocess the signal, four methods including Sample Entropy, Power Spectrum Density, Spectrogram, and Continuous Wavelet Transform to extract EEG features, and Extreme Learning Machine to classify these features. The system achieves an accuracy of 0.9691 with an online dataset and its success is verified with EEG signals collected by the author via Emotiv. Bachelor of Engineering 2014-06-05T06:36:46Z 2014-06-05T06:36:46Z 2014 2014 Final Year Project (FYP) http://hdl.handle.net/10356/61135 en Nanyang Technological University 63 p. application/pdf |
| spellingShingle | DRNTU::Engineering Liu, Yanling EEG based assisted driving system |
| title | EEG based assisted driving system |
| title_full | EEG based assisted driving system |
| title_fullStr | EEG based assisted driving system |
| title_full_unstemmed | EEG based assisted driving system |
| title_short | EEG based assisted driving system |
| title_sort | eeg based assisted driving system |
| topic | DRNTU::Engineering |
| url | http://hdl.handle.net/10356/61135 |
| work_keys_str_mv | AT liuyanling eegbasedassisteddrivingsystem |