Quantification of brain injury by EEG cepstral distance during transient global ischemia

Lei Hao, Rutwik Ghodadra, Nitish V. Thakor

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. Autoregressive (AR) models have previously been used to parameterize the EEG signals. Cepstral distance which is based on the AR model parameters, is used here to measure the similarity of the EEG signals obtained during various phases of the experimental study. The effectiveness of the cepstral distance is demonstrated through its ability to distinguish asphyxia and quantify the period of the brain asphyxia injury.

Original languageEnglish (US)
Pages (from-to)1205-1206
Number of pages2
JournalAnnual International Conference of the IEEE Engineering in Medicine and Biology - Proceedings
Volume3
StatePublished - Dec 1 1997
EventProceedings of the 1997 19th Annual International Conference of the IEEE Engineering in Medicine and Biology Society - Chicago, IL, USA
Duration: Oct 30 1997Nov 2 1997

ASJC Scopus subject areas

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

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