Search Results - "Lofhede, J"

Textile electrodes for EEG recording--a pilot study by Löfhede, Johan, Seoane, Fernando, Thordstein, Magnus

“…The overall aim of our research is to develop a monitoring system for neonatal intensive care units. Long-term EEG monitoring in newborns require that the…”
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Prognostic capacity of automated quantification of suppression time in the EEG of post-asphyctic full-term neonates by Flisberg, A, Kjellmer, I, Löfhede, J, Lindecrantz, K, Thordstein, M

“…Aim:  To evaluate the prognostic capacity of a new method for automatic quantification of the length of suppression time in the electroencephalogram (EEG) of a…”
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Classification of burst and suppression in the neonatal electroencephalogram by Löfhede, J, Löfgren, N, Thordstein, M, Flisberg, A, Kjellmer, I, Lindecrantz, K

“…Fisher's linear discriminant (FLD), a feed-forward artificial neural network (ANN) and a support vector machine (SVM) were compared with respect to their…”
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P10-18 Automated classification of human neonatal EEG by Thordstein, M, Lofhede, J, Flisberg, A, Lofgren, N, Lindecrantz, K, Kjellmer, I

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Does indomethacin for closure of patent ductus arteriosus affect cerebral function? by Flisberg, A, Kjellmer, I, Löfhede, J, Löfgren, N, Rosa-Zurera, M, Lindecrantz, K, Thordstein, M

“…Objective:  To study whether indomethacin used in conventional dose for closure of patent ductus arteriosus affects cerebral function measured by…”
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Comparing a supervised and an unsupervised classification method for burst detection in neonatal EEG by Lofhede, J., Degerman, J., Lofgren, N., Thordstein, M., Flisberg, A., Kjellmer, I., Lindecrantz, K.

“…Hidden Markov Models (HMM) and Support Vector Machines (SVM) using unsupervised and supervised training, respectively, were compared with respect to their…”
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Automatic classification of background EEG activity in healthy and sick neonates by Löfhede, Johan, Thordstein, Magnus, Löfgren, Nils, Flisberg, Anders, Rosa-Zurera, Manuel, Kjellmer, Ingemar, Lindecrantz, Kaj

“…The overall aim of our research is to develop methods for a monitoring system to be used at neonatal intensive care units. When monitoring a baby, a range of…”
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Detection of Bursts in the EEG of Post Asphyctic Newborns by Lofhede, J., Lofgren, N., Thordstein, M., Flisberg, A., Kjellmer, I., Lindecrantz, K.

“…Eight features inherent in the electroencephalogram (EEG) have been extracted and evaluated with respect to their ability to distinguish bursts from…”
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Comparison of Three Methods for Classifying Burst and Suppression in the EEG of Post Asphyctic Newborns by Lofhede, J., Lofgren, N., Lindecrantz, K., Flisberg, A., Kjellmer, I., Thordstein, M.

“…Fisher's linear discriminant, a feed-forward neural network (NN) and a support vector machine (SVM) are compared with respect to their ability to distinguish…”
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Classifying Burst and Suppression in the EEG of Post Asphyctic Newborns using a Support Vector Machine by Lofhede, J., Lofgren, N., Thordstein, M., Flisberg, A., Kjellmer, I., Lindecrantz, K.

“…A support vector machine (SVM) was trained to distinguish bursts from suppression in burst-suppression EEG, using five features inherent in the…”
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