Genetic feature selection in EEG-based motion sickness estimation

Chun-Shu Wei, Li-Wei Ko*, Shang Wen Chuang, Tzyy Ping Jung, Chin-Teng Lin

*此作品的通信作者

研究成果: Conference contribution同行評審

6 引文 斯高帕斯(Scopus)

摘要

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.

原文English
主出版物標題2011 International Joint Conference on Neural Networks, IJCNN 2011 - Final Program
頁面365-369
頁數5
DOIs
出版狀態Published - 2 八月 2011
事件2011 International Joint Conference on Neural Network, IJCNN 2011 - San Jose, CA, United States
持續時間: 31 七月 20115 八月 2011

出版系列

名字Proceedings of the International Joint Conference on Neural Networks

Conference

Conference2011 International Joint Conference on Neural Network, IJCNN 2011
國家/地區United States
城市San Jose, CA
期間31/07/115/08/11

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