EEG spike detection using time-frequency signal analysis

Hamid Hassanpour*, Mostefa Mesbah, Boualem Boashash

*Corresponding author for this work

Research output: Contribution to journalConference articlepeer-review

27 Citations (Scopus)


This paper presents a new method for detecting EEG spikes. The method is based on the time-frequency distribution of the signal. As spikes are short time broadband events, they are represented as ridges in the time-frequency domain. In this domain, the high instantaneous energy of spikes allows them to be distinguishable from the background. To detect spikes, the time-frequency distribution of the signal of interest is first enhanced to attenuate the noise. Two frequency slices of the enhanced time-frequency distribution are then extracted and subjected to the smoothed nonlinear energy operator (SNEO). Finally, the output of the SNEO is thresholded to localise the position of the spikes in the signal. The SNEO is employed to accentuate the spike signature in the extracted frequency slices. A spike is considered to exist in the time domain signal if a signature of the spike is detected at the same position in both frequency slices.

Original languageEnglish
Pages (from-to)V-421-V-424
JournalICASSP, IEEE International Conference on Acoustics, Speech and Signal Processing - Proceedings
Publication statusPublished - 2004
Externally publishedYes
EventProceedings - IEEE International Conference on Acoustics, Speech, and Signal Processing - Montreal, Que, Canada
Duration: May 17 2004May 21 2004

ASJC Scopus subject areas

  • Software
  • Signal Processing
  • Electrical and Electronic Engineering


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