Describing the nonstationarity level of neurological signals based on quantifications of time-frequency representation

Shanbao Tong, Zhengjun Li, Yisheng Zhu, Nitish V Thakor

Research output: Contribution to journalArticle

Abstract

Most neurological signals including electroencephalogram (EEG), evoked potential (EP) and local field potential (LFP) have been known to be time varying and nonstationary, especially in some pathological conditions. Currently, the most widely used quantitative tool for such nonstationary signals is time-frequency representation (TFR) which demonstrates the temporal evolution of different frequency components. However, TFR does not directly provide a quantitative measure of nonstationarity level, e.g., how far the process deviates from stationarity. In this study, we introduced three different quantifications of TFR (qTFR) to characterize the nonstationarity level of the involving signals: 1) degree of stationarity (DS); 2) Shannon entropy (SE) of the marginal spectrum; and 3) Kullback-Leibler distance (KLD) between a TFR and a uniform distribution. These descriptors provide quantitative analysis of stationarity of a signal such that the stationarity of different signals could be compared. In this study, we obtained the TFRs of the EEG signals before and after the hypoxic-ischemic (HI) brain injury and examined the stationarity of the EEG. DS, SE, and KLD can indicate the nonstationarity change of EEG at each frequency following the HI injury, especially in the upper δ-and lower θ-band (e.g., [2 Hz, 8 Hz]) as well as in the β2 band (e.g., [22 Hz-26 Hz]). Moreover, it is shown that the stationarity of the EEG changes differently in different frequencies following the HI injury.

Original languageEnglish (US)
Pages (from-to)1780-1785
Number of pages6
JournalIEEE Transactions on Biomedical Engineering
Volume54
Issue number10
DOIs
StatePublished - Oct 2007

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Electroencephalography
Bioelectric potentials
Entropy
Brain
Chemical analysis

Keywords

  • Electroencephalogram (EEG)
  • Kullback-Leibler distance
  • Shannon entropy
  • Stationarity
  • Time-frequency representation (TFR)

ASJC Scopus subject areas

  • Biomedical Engineering

Cite this

Describing the nonstationarity level of neurological signals based on quantifications of time-frequency representation. / Tong, Shanbao; Li, Zhengjun; Zhu, Yisheng; Thakor, Nitish V.

In: IEEE Transactions on Biomedical Engineering, Vol. 54, No. 10, 10.2007, p. 1780-1785.

Research output: Contribution to journalArticle

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