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Information Journal Paper

Title

A STUDY OF VARIOUS FEATURE EXTRACTION METHODS ON A MOTOR IMAGERY BASED BRAIN COMPUTER INTERFACE SYSTEM

Pages

  13-19

Keywords

BRAIN-COMPUTER INTERFACE (BCI) 

Abstract

 Introduction: Brain Computer Interface (BCI) systems based on Movement Imagination (MI) are widely used in recent decades. Separate feature extraction methods are employed in the MI data sets and classified in Virtual Reality (VR) environments for real-time applications.Methods: This study applied wide variety of features on the recorded data using Linear Discriminant Analysis (LDA) classifier to select the best feature sets in the offline mode.The data set was recorded in 3-class tasks of the left hand, the right hand, and the foot motor imagery.Results: The experimental results showed that Auto-Regressive (AR), Mean Absolute Value (MAV), and Band Power (BP) features have higher accuracy values, 75% more than those for the other features.Discussion: These features were selected for the designed real-time navigation. The corresponding results revealed the subject-specific nature of the MI-based BCI system; however, the Power Spectral Density (PSD) based α-BP feature had the highest averaged accuracy.

Cites

References

Cite

APA: Copy

RESALAT, SEYED NAVID, & SABA, VALIALLAH. (2016). A STUDY OF VARIOUS FEATURE EXTRACTION METHODS ON A MOTOR IMAGERY BASED BRAIN COMPUTER INTERFACE SYSTEM. BASIC AND CLINICAL NEUROSCIENCE, 7(1), 13-19. SID. https://sid.ir/paper/327750/en

Vancouver: Copy

RESALAT SEYED NAVID, SABA VALIALLAH. A STUDY OF VARIOUS FEATURE EXTRACTION METHODS ON A MOTOR IMAGERY BASED BRAIN COMPUTER INTERFACE SYSTEM. BASIC AND CLINICAL NEUROSCIENCE[Internet]. 2016;7(1):13-19. Available from: https://sid.ir/paper/327750/en

IEEE: Copy

SEYED NAVID RESALAT, and VALIALLAH SABA, “A STUDY OF VARIOUS FEATURE EXTRACTION METHODS ON A MOTOR IMAGERY BASED BRAIN COMPUTER INTERFACE SYSTEM,” BASIC AND CLINICAL NEUROSCIENCE, vol. 7, no. 1, pp. 13–19, 2016, [Online]. Available: https://sid.ir/paper/327750/en

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