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| Content Provider | IEEE Xplore Digital Library |
|---|---|
| Author | Chun-Shu Wei Li-Wei Ko Shang-Wen Chuang Tzyy-Ping Jung Chin-Teng Lin |
| Copyright Year | 2011 |
| Description | Author affiliation: Brain Research Center and the Department of Electrical Engineering, National Chiao-Tung University, Hsinchu, Taiwan, R.O.C. (Chun-Shu Wei; Shang-Wen Chuang; Chin-Teng Lin) || Swartz Center for Computational Neuroscience, Institute for Neural Computation, University of California San Diego, 92037, USA (Tzyy-Ping Jung) || Brain Research Center and the Department of Biological Science and Technology, National Chiao-Tung University, Hsinchu, Taiwan, R.O.C. (Li-Wei Ko) |
| Abstract | Motion sickness is a common symptom that occurs when the brain receives conflicting information about the sensation of movement. Many motion sickness biomarkers have been identified, and electroencephalogram (EEG)-based motion sickness level estimation was found feasible in our previous study. This study employs genetic feature selection to find a subset of EEG features that can further improve estimation performance over the correlation-based method reported in the previous studies. The features selected by genetic feature selection were very different from those obtained by correlation analysis. Results of this study demonstrate that genetic feature selection is a very effective method to optimize the estimation of motion-sickness level. This demonstration could lead to a practical system for noninvasive monitoring of the motion sickness of individuals in real-world environments. |
| Starting Page | 365 |
| Ending Page | 369 |
| File Size | 520553 |
| Page Count | 5 |
| File Format | |
| ISBN | 9781424496358 |
| ISSN | 21614407 |
| e-ISBN | 9781424496372 |
| DOI | 10.1109/IJCNN.2011.6033244 |
| Language | English |
| Publisher | Institute of Electrical and Electronics Engineers, Inc. (IEEE) |
| Publisher Date | 2011-07-31 |
| Publisher Place | USA |
| Access Restriction | Subscribed |
| Rights Holder | Institute of Electrical and Electronics Engineers, Inc. (IEEE) |
| Subject Keyword | Electroencephalography Estimation Genetic algorithms Genetics Correlation Feature extraction Educational institutions |
| Content Type | Text |
| Resource Type | Article |
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