Time- Frequency based Renyi entropy of heart rate variability for newborn seizure detection

M. B. Malarvili, L. Rankine, M. Mesbah, B. Boashash

Research output: Chapter in Book/Report/Conference proceedingConference contribution

4 Citations (Scopus)

Abstract

The time-frequency (TF) version of Renyi entropy, which measures the information content and complexity of a signal, is used here as a feature in the classification of the newborn heart rate variability (HRV) as either corresponding to seizure or non-seizure. The newborn HRV is initially mapped to the TF domain using the modified B distribution (MBD). The time-frequency distribution (TFD) of HRV is post-processed before the Renyi entropy is computed. This post-processing method uses an image processing technique called component linking to identify the true HRV components and localize them in the TF plane. The results obtained so far show that the HRV corresponding to non-seizure can be discriminated from those corresponding to seizure using TF-based Renyi entropy with 78.57% sensitivity and 83.33 % specificity.

Original languageEnglish
Title of host publication2007 9th International Symposium on Signal Processing and its Applications, ISSPA 2007, Proceedings
DOIs
Publication statusPublished - 2007
Event2007 9th International Symposium on Signal Processing and its Applications, ISSPA 2007 - Sharjah, United Arab Emirates
Duration: Feb 12 2007Feb 15 2007

Other

Other2007 9th International Symposium on Signal Processing and its Applications, ISSPA 2007
CountryUnited Arab Emirates
CitySharjah
Period2/12/072/15/07

ASJC Scopus subject areas

  • Signal Processing

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    Malarvili, M. B., Rankine, L., Mesbah, M., & Boashash, B. (2007). Time- Frequency based Renyi entropy of heart rate variability for newborn seizure detection. In 2007 9th International Symposium on Signal Processing and its Applications, ISSPA 2007, Proceedings [4555371] https://doi.org/10.1109/ISSPA.2007.4555371