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Engagement assessment using eeg signals
| Content Provider | NASA Technical Reports Server (NTRS) |
|---|---|
| Author | Heitkamp, Dean Xu, Roger Wang, Wei Pepe, Aaron Li, Jiang Li, Feng McKenzie, Frederic Zhang, Guangfan Schnell Sr., Thomas Anderson, Nick |
| Copyright Year | 2012 |
| Description | In this paper, we present methods to analyze and improve an EEG-based engagement assessment approach, consisting of data preprocessing, feature extraction and engagement state classification. During data preprocessing, spikes, baseline drift and saturation caused by recording devices in EEG signals are identified and eliminated, and a wavelet based method is utilized to remove ocular and muscular artifacts in the EEG recordings. In feature extraction, power spectrum densities with 1 Hz bin are calculated as features, and these features are analyzed using the Fisher score and the one way ANOVA method. In the classification step, a committee classifier is trained based on the extracted features to assess engagement status. Finally, experiment results showed that there exist significant differences in the extracted features among different subjects, and we have implemented a feature normalization procedure to mitigate the differences and significantly improved the engagement assessment performance. |
| File Size | 3965252 |
| Page Count | 8 |
| File Format | |
| Alternate Webpage(s) | http://archive.org/details/NASA_NTRS_Archive_20130008671 |
| Archival Resource Key | ark:/13960/t5n927s23 |
| Language | English |
| Publisher Date | 2012-03-01 |
| Access Restriction | Open |
| Subject Keyword | Behavioral Sciences Alertness Situational Awareness Electroencephalography Preprocessing Analysis of Variance Operator Performance Ntrs Nasa Technical Reports Server (ntrs) Nasa Technical Reports Server Aerodynamics Aircraft Aerospace Engineering Aerospace Aeronautic Space Science |
| Content Type | Text |
| Resource Type | Article |
