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

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

doi:10.1109/ISSPA.2007.4555371

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

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

Electrical and Computer Engineering

Research output: Chapter in Book/Report/Conference proceeding › Conference 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 language	English
Title of host publication	2007 9th International Symposium on Signal Processing and its Applications, ISSPA 2007, Proceedings
DOIs	https://doi.org/10.1109/ISSPA.2007.4555371
Publication status	Published - 2007
Event	2007 9th International Symposium on Signal Processing and its Applications, ISSPA 2007 - Sharjah, United Arab Emirates Duration: Feb 12 2007 → Feb 15 2007

Other

Other	2007 9th International Symposium on Signal Processing and its Applications, ISSPA 2007
Country	United Arab Emirates
City	Sharjah
Period	2/12/07 → 2/15/07

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

Malarvili, MB, 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, 2007 9th International Symposium on Signal Processing and its Applications, ISSPA 2007, Sharjah, United Arab Emirates, 2/12/07. https://doi.org/10.1109/ISSPA.2007.4555371

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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.",

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AU - Rankine, L.

AU - Mesbah, M.

AU - Boashash, B.

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N2 - 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.

AB - 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.

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