Abstract
The identification of newborn seizures requires the processing of a number of physiological signals routinely recorded from patients, including the EEG and ECG, as well as EOG and respiration signals. Most existing studies have focused on using the EEG as the sole information source in automatic seizure detection. Some of these studies concluded that the information obtained from the EEG should be supplemented by other information obtained from other recorded physiological signals. This chapter documents an approach that uses the ECG as the basis for seizure detection and explores how such approach could be combined with the EEG based methodologies to achieve a robust automatic seizure detector.
| Original language | English |
|---|---|
| Title of host publication | Advanced Biosignal Processing |
| Publisher | Springer Berlin Heidelberg |
| Pages | 95-121 |
| Number of pages | 27 |
| ISBN (Print) | 9783540895053 |
| DOIs | |
| Publication status | Published - 2009 |
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ASJC Scopus subject areas
- Engineering(all)
Cite this
Heart rate variability time-frequency analysis for newborn seizure detection. / Mesbah, Mostefa; Boashash, Boualem; Balakrishnan, Malarvili; Coldiz, Paul B.
Advanced Biosignal Processing. Springer Berlin Heidelberg, 2009. p. 95-121.Research output: Chapter in Book/Report/Conference proceeding › Chapter
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TY - CHAP
T1 - Heart rate variability time-frequency analysis for newborn seizure detection
AU - Mesbah, Mostefa
AU - Boashash, Boualem
AU - Balakrishnan, Malarvili
AU - Coldiz, Paul B.
PY - 2009
Y1 - 2009
N2 - The identification of newborn seizures requires the processing of a number of physiological signals routinely recorded from patients, including the EEG and ECG, as well as EOG and respiration signals. Most existing studies have focused on using the EEG as the sole information source in automatic seizure detection. Some of these studies concluded that the information obtained from the EEG should be supplemented by other information obtained from other recorded physiological signals. This chapter documents an approach that uses the ECG as the basis for seizure detection and explores how such approach could be combined with the EEG based methodologies to achieve a robust automatic seizure detector.
AB - The identification of newborn seizures requires the processing of a number of physiological signals routinely recorded from patients, including the EEG and ECG, as well as EOG and respiration signals. Most existing studies have focused on using the EEG as the sole information source in automatic seizure detection. Some of these studies concluded that the information obtained from the EEG should be supplemented by other information obtained from other recorded physiological signals. This chapter documents an approach that uses the ECG as the basis for seizure detection and explores how such approach could be combined with the EEG based methodologies to achieve a robust automatic seizure detector.
UR - http://www.scopus.com/inward/record.url?scp=78650299911&partnerID=8YFLogxK
UR - http://www.scopus.com/inward/citedby.url?scp=78650299911&partnerID=8YFLogxK
U2 - 10.1007/978-3-540-89506-0_5
DO - 10.1007/978-3-540-89506-0_5
M3 - Chapter
AN - SCOPUS:78650299911
SN - 9783540895053
SP - 95
EP - 121
BT - Advanced Biosignal Processing
PB - Springer Berlin Heidelberg
ER -