Abstract
The nonstationary and multicomponent nature of newborn EEG seizures tend to increase the complexity of the seizure detection problem. In dealing with this type of problem, time-frequency based techniques were shown to outperform classical techniques. Neonatal EEG seizures have signatures in both low frequency (lower than 10 Hz) and high frequency (higher than 70 Hz) areas. Seizure detection techniques have been proposed that concentrate on either low frequency or high frequency signatures of seizures. They, however, tend to miss seizures that reveal themselves only in one of the frequency areas. To overcome this problem, we propose a detection method that uses time-frequency seizure features extracted from both low and high frequency areas. Results of applying the proposed method on five newborn EEGs are very encouraging.
| Original language | English |
|---|---|
| Pages (from-to) | 935-944 |
| Number of pages | 10 |
| Journal | Physiological Measurement |
| Volume | 25 |
| Issue number | 4 |
| DOIs | |
| Publication status | Published - Aug 2004 |
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Keywords
- EEG seizure detection
- Singular vector
- Spike detection
- Time-frequency
ASJC Scopus subject areas
- Biophysics
- Physiology
- Physiology (medical)
Cite this
Time-frequency based newborn EEG seizure detection using low and high frequency signatures. / Hassanpour, Hamid; Mesbah, Mostefa; Boashash, Boualem.
In: Physiological Measurement, Vol. 25, No. 4, 08.2004, p. 935-944.Research output: Contribution to journal › Article
}
TY - JOUR
T1 - Time-frequency based newborn EEG seizure detection using low and high frequency signatures
AU - Hassanpour, Hamid
AU - Mesbah, Mostefa
AU - Boashash, Boualem
PY - 2004/8
Y1 - 2004/8
N2 - The nonstationary and multicomponent nature of newborn EEG seizures tend to increase the complexity of the seizure detection problem. In dealing with this type of problem, time-frequency based techniques were shown to outperform classical techniques. Neonatal EEG seizures have signatures in both low frequency (lower than 10 Hz) and high frequency (higher than 70 Hz) areas. Seizure detection techniques have been proposed that concentrate on either low frequency or high frequency signatures of seizures. They, however, tend to miss seizures that reveal themselves only in one of the frequency areas. To overcome this problem, we propose a detection method that uses time-frequency seizure features extracted from both low and high frequency areas. Results of applying the proposed method on five newborn EEGs are very encouraging.
AB - The nonstationary and multicomponent nature of newborn EEG seizures tend to increase the complexity of the seizure detection problem. In dealing with this type of problem, time-frequency based techniques were shown to outperform classical techniques. Neonatal EEG seizures have signatures in both low frequency (lower than 10 Hz) and high frequency (higher than 70 Hz) areas. Seizure detection techniques have been proposed that concentrate on either low frequency or high frequency signatures of seizures. They, however, tend to miss seizures that reveal themselves only in one of the frequency areas. To overcome this problem, we propose a detection method that uses time-frequency seizure features extracted from both low and high frequency areas. Results of applying the proposed method on five newborn EEGs are very encouraging.
KW - EEG seizure detection
KW - Singular vector
KW - Spike detection
KW - Time-frequency
UR - http://www.scopus.com/inward/record.url?scp=4344636860&partnerID=8YFLogxK
UR - http://www.scopus.com/inward/citedby.url?scp=4344636860&partnerID=8YFLogxK
U2 - 10.1088/0967-3334/25/4/012
DO - 10.1088/0967-3334/25/4/012
M3 - Article
VL - 25
SP - 935
EP - 944
JO - Physiological Measurement
JF - Physiological Measurement
SN - 0967-3334
IS - 4
ER -