Sensor space time-varying information flow analysis of multiclass motor imagery through Kalman Smoother and em algorithm

Mahyar Hamedi, Sh Hussain Salleh, Chee Ming Ting, S. Balqis Samdin, Alias Mohd Noor

Research output: Chapter in Book/Report/Conference proceedingConference PaperResearchpeer-review

4 Citations (Scopus)

Abstract

Inter-channel time-varying (TV) relationships of scalp neural recordings offer deep understanding of the brain sensory and cognitive functions. This paper develops a state space-based TV multivariate autoregressive (MVAR) model for estimating TV-information flow (IF) recruited by different motor imagery (MI) movements. TV model coefficients are computed through Kalman filter (KF) by incorporating Kalman smoothing approach and expectation-maximization algorithm for model parameter estimation, KS-EM. Volume conduction (VC) problem is also addressed by considering full noise covariate in observation equation. An automated model initialization is also implemented to deliver optimal estimates. TV-partial directed coherence derived from the proposed model is applied for IF analysis. The performance of KS-EM is assessed and compared with dual extended KF and overlapping sliding window-based MVAR models using simulated data. Finally, TV-IF during four different MI movements is studied. Results show the superiority of KS-EM for tracking the rapid signal parameter changes and eliminating the VC effect in the sensor space EEG. Differences in contralateral/ipsilateral TV-IF around alpha and lower beta bands during each MI task reveal the high potential of this feature for BCI applications.

Original languageEnglish
Title of host publication2015 International Conference on BioSignal Analysis, Processing and Systems, ICBAPS 2015
PublisherIEEE, Institute of Electrical and Electronics Engineers
Pages118-122
Number of pages5
ISBN (Electronic)9781479968794
DOIs
Publication statusPublished - 5 Oct 2015
Externally publishedYes
EventInternational Conference on BioSignal Analysis, Processing and Systems 2015 - Kuala Lumpur, Malaysia
Duration: 26 May 201528 May 2015
Conference number: 1st
https://ieeexplore.ieee.org/xpl/conhome/7277373/proceeding (Proceedings)

Conference

ConferenceInternational Conference on BioSignal Analysis, Processing and Systems 2015
Abbreviated titleICBAPS 2015
CountryMalaysia
CityKuala Lumpur
Period26/05/1528/05/15
Internet address

Keywords

  • brain connectivity analysis
  • electroencephalogram
  • motor imagery movement
  • sensor space connectivity
  • state space model

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