Single-Trial Evoked Potential Estimation Using Iterative Principal Component Analysis

Md Rakibul Mowla, Siew Cheok Ng, Muhammad S.A. Zilany, Raveendran Paramesran

Research output: Contribution to journalArticlepeer-review

7 Citations (Scopus)

Abstract

In this paper, we have presented an iterative principal component analysis (PCA) method to obtain single trial evoked potential. The performance of the iterative PCA has been compared with the performance of other iterative component analysis methods, such as independent component analysis, canonical correlation analysis (CCA), and the second-order blind identification, using simulated data at different signal-to-noise ratios as well as actual recordings of visual evoked potentials. In both the simulated and real cases, iterative PCA and CCA perform better than the other methods to estimate the amplitudes. In the estimated trials of the proposed method, the latency of the evoked potentials lies between ±4 ms range of true latency in about 90% of the case; but for other methods, this percentage is around 60%.

Original languageEnglish
Article number7513451
Pages (from-to)6955-6960
Number of pages6
JournalIEEE Sensors Journal
Volume16
Issue number18
DOIs
Publication statusPublished - 15 Sept 2016
Externally publishedYes

Keywords

  • blind source separation
  • Evoked potentials
  • principal component analysis
  • single trials

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