원문정보
보안공학연구지원센터(IJMUE)
International Journal of Multimedia and Ubiquitous Engineering
Vol.9 No.6
2014.06
pp.81-92
피인용수 : 0건 (자료제공 : 네이버학술정보)
초록
영어
Ordinal Pattern analysis has been used recently for extracting qualitative information from non-linear time series and it has been applied to usefully track brain dynamics. In this paper, we proposed a novel P300-based BCI system which depends on ordinal time series analysis as a feature extraction method. We have shown that this method can efficiently revel P300 feature, and therefore good classification accuracies and bitrates have been achieved for healthy and disabled subjects.
목차
Abstract
1. Introduction
2. P300 Brain Computer Interfacing
3. Nonlinear time Series Analysis
3.1. Nonlinearity of the Medium
3.2. Reconstruction of Dynamics from Observation
4. Ordinal Pattern Analysis
5. Materials and Methods
5.1. Datasets
5.2. Offline Analysis
5.3. Preprocessing Operations
5.4. Ordinal pattern calculations
5.5. Machine Learning and Classification
6. Results
7. Conclusion and Discussion
Acknowledgements
References
1. Introduction
2. P300 Brain Computer Interfacing
3. Nonlinear time Series Analysis
3.1. Nonlinearity of the Medium
3.2. Reconstruction of Dynamics from Observation
4. Ordinal Pattern Analysis
5. Materials and Methods
5.1. Datasets
5.2. Offline Analysis
5.3. Preprocessing Operations
5.4. Ordinal pattern calculations
5.5. Machine Learning and Classification
6. Results
7. Conclusion and Discussion
Acknowledgements
References
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