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Quaternion Common Spatial Patterns

Enshaeifar, Shirin, Cheong Took, Clive, Cheolsoo, P and Mandic, D (2016) Quaternion Common Spatial Patterns IEEE Transactions on Neural Systems and Rehabilitation Engineering, 25 (8). pp. 1278-1286.

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A novel quaternion-valued common spatial patterns (QCSP) algorithm is introduced to model co-channel coupling of multi-dimensional processes. To cater for the generality of quaternion-valued non-circular data, we propose a generalised QCSP (G-QCSP) which incorporates the information on power difference between the real and imaginary parts of data channels. As an application, we demonstrate how G-QCSP can be used to provide high classification rates, even at a signal-to-noise ratio (SNR) as low as -10 dB. To illustrate the usefulness of our method in EEG analysis, we employ G-QCSP to extract features for discriminating between imagery left and right hand movements. The classification accuracy using these features is 70%. Furthermore, the proposed method is used to distinguish between Parkinson’s disease (PD) patients and healthy control subjects, providing an accuracy of 87%.

Item Type: Article
Subjects : Computing Science
Divisions : Faculty of Engineering and Physical Sciences > Computing Science
Authors :
Cheong Took,
Cheolsoo, P
Mandic, D
Date : 3 November 2016
DOI : 10.1109/TNSRE.2016.2625039
Copyright Disclaimer : © 2016 IEEE. Personal use of this material is permitted. Permission from IEEE must be obtained for all other uses, in any current or future media, including reprinting/republishing this material for advertising or promotional purposes, creating new collective works, for resale or redistribution to servers or lists, or reuse of any copyrighted component of this work in other works.
Uncontrolled Keywords : Common spatial pattern, Quaternion domain, Augmented statistics.
Related URLs :
Depositing User : Symplectic Elements
Date Deposited : 20 Dec 2016 11:39
Last Modified : 16 Jan 2019 17:10

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