TY  - CONF
  - R. Ahmed, A. Temko, W. Marnane, G. Boylan, G. Lightbody
  - 34th Annual International IEEE EMBS Conference
  - Dynamic Time Warping Based Neonatal Seizure Detection System
  - 2012
  - August
  - Published
  - 1
  - Scopus: 3 ()
  - 4919
  - 4922
  - San Diego, CA, USA
  - 28-AUG-12
  - 01-SEP-12
  - Neonatal seizures patterns evolve with changing frequency, morphology and propagation. This study is an initial attempt to incorporate the characteristics of temporal evolution of neonatal seizures into our developed neonatal seizure detector. The previously designed SVM-based neonatal seizure detector is modified by substituting the Gaussian kernel with the Gaussian dynamic time warping kernel, to enable the SVM to classify variable length sequences of feature vectors of neonatal seizures. The preliminary results obtained compare favourably with the conventional SVM. The fusion of the two approaches is expected to improve the current state of the art neonatal seizure detection system
  - 10.1109/EMBC.2012.6347097
  - Science Foundation Ireland
  - 10/IN.1/B3036
DA  - 2012/08
ER  - 

@inproceedings{V154234491,
   = {R. Ahmed,  A. Temko and  W. Marnane,  G. Boylan and  G. Lightbody },
   = {34th Annual International IEEE EMBS Conference},
   = {{Dynamic Time Warping Based Neonatal Seizure Detection System}},
   = {2012},
   = {August},
   = {Published},
   = {1},
   = {Scopus: 3 ()},
  pages = {4919--4922},
   = {San Diego, CA, USA},
  month = {Aug},
   = {01-SEP-12},
   = {{Neonatal seizures patterns evolve with changing frequency, morphology and propagation. This study is an initial attempt to incorporate the characteristics of temporal evolution of neonatal seizures into our developed neonatal seizure detector. The previously designed SVM-based neonatal seizure detector is modified by substituting the Gaussian kernel with the Gaussian dynamic time warping kernel, to enable the SVM to classify variable length sequences of feature vectors of neonatal seizures. The preliminary results obtained compare favourably with the conventional SVM. The fusion of the two approaches is expected to improve the current state of the art neonatal seizure detection system}},
   = {10.1109/EMBC.2012.6347097},
   = {Science Foundation Ireland},
   = {10/IN.1/B3036},
  source = {IRIS}
}