TY - GEN
T1 - A method for the blind separation of sources for use as the first stage of a neonatal seizure detection system
AU - Faul, S.
AU - Marnane, L.
AU - Lightbody, G.
AU - Boylan, G.
AU - Connolly, S.
PY - 2005
Y1 - 2005
N2 - A method is proposed for automatically choosing independent components (ICs) of interest from neonatal EEG data, with the aim of using them in further analysis to detect seizures. This procedure greatly reduces the amount of information which needs to be processed in the seizure detection system, and reduces the effect of noise and artefacts on its performance. The Fast ICA algorithm is used to generate the ICs, and the complexity of each IC is examined to determine those of interest. The Singular Value Fraction (SVF) measure is used to reduce the number of sources containing artefacts chosen. In the best case, the 12 channel EEG used in these tests is reduced to 2 or 3 sources of interest, In every case, at least 3 sources were removed that consisted of noise.
AB - A method is proposed for automatically choosing independent components (ICs) of interest from neonatal EEG data, with the aim of using them in further analysis to detect seizures. This procedure greatly reduces the amount of information which needs to be processed in the seizure detection system, and reduces the effect of noise and artefacts on its performance. The Fast ICA algorithm is used to generate the ICs, and the complexity of each IC is examined to determine those of interest. The Singular Value Fraction (SVF) measure is used to reduce the number of sources containing artefacts chosen. In the best case, the 12 channel EEG used in these tests is reduced to 2 or 3 sources of interest, In every case, at least 3 sources were removed that consisted of noise.
UR - https://www.scopus.com/pages/publications/32844459840
U2 - 10.1109/ICASSP.2005.1416327
DO - 10.1109/ICASSP.2005.1416327
M3 - Conference proceeding
AN - SCOPUS:32844459840
SN - 0780388747
SN - 9780780388741
T3 - ICASSP, IEEE International Conference on Acoustics, Speech and Signal Processing - Proceedings
SP - V409-V412
BT - 2005 IEEE ICASSP '05 - Proc. - Design and Implementation of Signal Proces.Syst.,Indust. Technol. Track,Machine Learning for Signal Proces. Education, Spec. Sessions
PB - Institute of Electrical and Electronics Engineers Inc.
T2 - 2005 IEEE International Conference on Acoustics, Speech, and Signal Processing, ICASSP '05
Y2 - 18 March 2005 through 23 March 2005
ER -