Earticle

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

키워드

저자

• Mohammed J. Alhaddad [ Computer Science, Faculty of Computing and Information Technology, King Abdulaziz University, Jeddah, Saudi Arabia ]
• Mahmoud I Kamel [ Computer Science, Faculty of Computing and Information Technology, King Abdulaziz University, Jeddah, Saudi Arabia ]
• Dalal M. Bakheet [ Computer Science, Faculty of Computing and Information Technology, King Abdulaziz University, Jeddah, Saudi Arabia ]

참고문헌

발행기관

간행물

표지보기 관심저널 등록

• 간행물명

  International Journal of Multimedia and Ubiquitous Engineering

• 간기

  월간

• pISSN

  1975-0080

• 수록기간

  2008~2016

• 등재여부

  SCOPUS

• 십진분류

  KDC 505 DDC 605