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

Access to Document

10.1109/ISSPA.2007.4555371

Fingerprint Dive into the research topics of 'Time- Frequency based Renyi entropy of heart rate variability for newborn seizure detection'. Together they form a unique fingerprint.

Cite this

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

@inproceedings{7fa52ca8a27044b8bd84b26524e33c66,

title = "Time- Frequency based Renyi entropy of heart rate variability for newborn seizure detection",

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.",

author = "Malarvili, {M. B.} and L. Rankine and M. Mesbah and B. Boashash",

year = "2007",

doi = "10.1109/ISSPA.2007.4555371",

language = "English",

isbn = "1424407796",

booktitle = "2007 9th International Symposium on Signal Processing and its Applications, ISSPA 2007, Proceedings",

note = "2007 9th International Symposium on Signal Processing and its Applications, ISSPA 2007 ; Conference date: 12-02-2007 Through 15-02-2007",

}

TY - GEN

T1 - Time- Frequency based Renyi entropy of heart rate variability for newborn seizure detection

AU - Malarvili, M. B.

AU - Rankine, L.

AU - Mesbah, M.

AU - Boashash, B.

PY - 2007

Y1 - 2007

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.

UR - http://www.scopus.com/inward/record.url?scp=51549104169&partnerID=8YFLogxK

UR - http://www.scopus.com/inward/citedby.url?scp=51549104169&partnerID=8YFLogxK

U2 - 10.1109/ISSPA.2007.4555371

DO - 10.1109/ISSPA.2007.4555371

M3 - Conference contribution

AN - SCOPUS:51549104169

SN - 1424407796

SN - 9781424407798

BT - 2007 9th International Symposium on Signal Processing and its Applications, ISSPA 2007, Proceedings

T2 - 2007 9th International Symposium on Signal Processing and its Applications, ISSPA 2007

Y2 - 12 February 2007 through 15 February 2007

ER -