Characterization of EEG signal changes via Itakura distance

Xuan Kong, Nitish Thakor, Vaibhava Goel

Research output: Contribution to journalConference articlepeer-review

Abstract

Clinical assessment of neurological system would be greatly facilitated by interpretation of disease- or injury-related changes in electroencephalogram (EEG) signals. Under the assumption that EEG signal can be modeled as an autoregressive (AR) process, Itakura distance is used to measure the similarity of the EEG signals obtained during various phases of the experimental study. The effectiveness of the Itakura distance is demonstrated through its ability to distinguish hypoxia and asphyxia as well as to predict recovery following the injury.

Original languageEnglish (US)
Pages (from-to)873-874
Number of pages2
JournalAnnual International Conference of the IEEE Engineering in Medicine and Biology - Proceedings
Volume17
Issue number2
StatePublished - Dec 1 1995
Externally publishedYes
EventProceedings of the 1995 IEEE Engineering in Medicine and Biology 17th Annual Conference and 21st Canadian Medical and Biological Engineering Conference. Part 2 (of 2) - Montreal, Can
Duration: Sep 20 1995Sep 23 1995

ASJC Scopus subject areas

  • Signal Processing
  • Biomedical Engineering
  • Computer Vision and Pattern Recognition
  • Health Informatics

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