Detection of seizure signals in newborns
This paper considers a system design for processing a multidimensional biomedical signal formed by EEG, ECG, EOG and motion recorded from a newborn, for the purpose of detection of epileptic seizures in newborns as an extension of the method reported in Boashash et al. (1997) and Roessgen et al. (1998). We describe the proposed design, and discuss how the signals will be analysed and fused to detect the occurrence of seizure. We also discuss the role of modelling in refining the signal processing unit.
- Engineering Innovation Research [41 items ]
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|Effectiveness of combined time-frequency imageand signal-based features for improving the detection and classification of epileptic seizure activities in EEG signals ||Boubchir, Larbi; Al-Maadeed, Somaya; Bouridane, Ahmed||2014||IEEE||Conference Paper|
|A methodology for time-frequency image processing applied to the classification of nonstationary multichannel signals using instantaneous frequency descriptors with application to newborn EEG signals ||Azemi, Ghasem; Boubchir, Larbi; Boashash, B.||2003||Springer||Article|
|Time-frequency signal and image processing of non-stationary signals with application to the classification of newborn EEG abnormalities ||Boashash, Boualem; Boubchir, Larbi; Azemi, Ghasem||2011||IEEE||Conference Paper|