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| 2. |
- Flisberg, Anders, 1958, et al.
(författare)
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Does indomethacin for closure of patent ductus arteriosus affect cerebral function?
- 2010
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Ingår i: Acta Paediatrica. - : Wiley. - 0803-5253 .- 1651-2227. ; 99:10, s. 1493-1497
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Tidskriftsartikel (refereegranskat)abstract
- Objective: To study whether indomethacin used in conventional dose for closure of patent ductus arteriosus affects cerebral function measured by Electroencephalograms (EEG) evaluated by quantitative measures. Study design: Seven premature neonates with haemodynamically significant persistent ductus arteriosus were recruited. EEG were recorded before, during and after an intravenous infusion of 0.2 mg/kg indomethacin over 10 min. The EEG was analysed by two methods with different degrees of complexity for the amount of low-activity periods (LAP, "suppressions") as an indicator of affection of cerebral function. Results: Neither of the two methods identified any change in the amount of LAPs in the EEG as compared to before the indomethacin infusion. Conclusion: Indomethacin in conventional dose for closure of patent ductus arteriosus does not affect cerebral function as evaluated by quantitative EEG.
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| 3. |
- Löfhede, Johan, 1978, et al.
(författare)
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Automatic classification of background EEG activity in healthy and sick neonates
- 2010
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Ingår i: Journal of Neural Engineering. - : IOP Publishing. - 1741-2560 .- 1741-2552. ; 7:1
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Tidskriftsartikel (refereegranskat)abstract
- 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 different types of background activity needs to be considered. In this work, we have developed a scheme for automatic classification of background EEG activity in newborn babies. EEG from six full-term babies who were displaying a burst suppression pattern while suffering from the after-effects of asphyxia during birth was included along with EEG from 20 full-term healthy newborn babies. The signals from the healthy babies were divided into four behavioural states: active awake, quiet awake, active sleep and quiet sleep. By using a number of features extracted from the EEG together with Fisher’s linear discriminant classifier we have managed to achieve 100% correct classification when separating burst suppression EEG from all four healthy EEG types and 93% true positive classification when separating quiet sleep from the other types. The other three sleep stages could not be classified. When the pathological burst suppression pattern was detected, the analysis was taken one step further and the signal was segmented into burst and suppression, allowing clinically relevant parameters such as suppression length and burst suppression ratio to be calculated. The segmentation of the burst suppression EEG works well, with a probability of error around 4%.
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| 4. |
- Löfhede, Johan, et al.
(författare)
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Classification of burst and suppression in the neonatal electroencephalogram
- 2008
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Ingår i: Journal of Neural Engineering. - : Institute of Physics Publishing Ltd.. - 1741-2560 .- 1741-2552. ; 5:4, s. 402-410
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Tidskriftsartikel (refereegranskat)abstract
- Fisher's linear discriminant (FLD), a feed-forward artificial neural network (ANN) and a support vector machine (SVM) were compared with respect to their ability to distinguish bursts from suppressions in electroencephalograms (EEG) displaying a burst-suppression pattern. Five features extracted from the EEG were used as inputs. The study was based on EEG signals from six full-term infants who had suffered from perinatal asphyxia, and the methods have been trained with reference data classified by an experienced electroencephalographer. The results are summarized as the area under the curve (AUC), derived from receiver operating characteristic (ROC) curves for the three methods. Based on this, the SVM performs slightly better than the others. Testing the three methods with combinations of increasing numbers of the five features shows that the SVM handles the increasing amount of information better than the other methods.
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| 7. |
- Löfhede, Johan, et al.
(författare)
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Comparing a Supervised and an Unsupervised Classification Method for Burst Detection in Neonatal EEG
- 2008
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Ingår i: Proceedings of Engineering in Medicine and Biology Society, EMBS 2008. 30th Annual International Conference of the IEEE, 20-24 August, 2008. - : IEEE. - 1557-170X. - 9781424418145 ; , s. 3836-3839
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Konferensbidrag (refereegranskat)abstract
- Hidden Markov Models (HMM) and Support Vector Machines (SVM) using unsupervised and supervised training, respectively, were compared with respect to their ability to correctly classify burst and suppression in neonatal EEG. Each classifier was fed five feature signals extracted from EEG signals from six full term infants who had suffered from perinatal asphyxia. Visual inspection of the EEG by an experienced electroencephalographer was used as the gold standard when training the SVM, and for evaluating the performance of both methods. The results are presented as receiver operating characteristic (ROC) curves and quantified by the area under the curve (AUC). Our study show that the SVM and the HMM exhibit similar performance, despite their fundamental differences.
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| 8. |
- Löfhede, Johan, 1978, et al.
(författare)
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Detection of bursts in the EEG of post asphyctic newborns
- 2006
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Ingår i: 2006 28th Annual International Conference of the IEEE Engineering in Medicine and Biology Society. - 1557-170X. - 9781424400324 ; , s. 2179-2182, s. 5-6
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Konferensbidrag (refereegranskat)abstract
- Eight features inherent in the electroencephalogram (EEG) have been extracted and evaluated with respect to their ability to distinguish bursts from suppression in burst-suppression EEG. The study is based on EEG from six full term infants who had suffered from lack of oxygen during birth. The features were used as input in a neural network, which was trained on reference data segmented by an experienced electroencephalographer. The performance was then evaluated on validation data for each feature separately and in combinations. The results show that there are significant variations in the type of activity found in burst-suppression EEG from different subjects, and that while one or a few features seem to be sufficient for most patients in this group, some cases require specific combinations of features for good detection to be possible.
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| 9. |
- Löfhede, Johan, 1978, et al.
(författare)
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Soft Textile Electrodes for EEG Monitoring
- 2010
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Ingår i: [12]10th IEEE International Conference on Information Technology and Applications.
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Konferensbidrag (refereegranskat)
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| 10. |
- Thordstein, Magnus, et al.
(författare)
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Effects of inflammation on cerebral electric activity in fetal sheep
- 2008
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Ingår i: 2nd Congress of the European Academy of Paediatrics, Nice 23-28 okt 2008.
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Konferensbidrag (övrigt vetenskapligt/konstnärligt)abstract
- OBJECTIVE Intrauterine infections can by themselves induce fetal brain damage but also potentiate the effects of other harmful influences such as asphyxia and seizures. Using an EEG technique that permits the recording of extremely low frequencies, often called DC EEG, changes in the level, i.e. DC shifts can be detected. The DC level has been suggested to depend mainly on the potential over the blood brain barrier (BBB), in turn decided primarily by the arterial level of pCO2. Fetuses affected by infection/inflammation that produce detrimental effects on the brain, may have elevated levels of pCO2 and disturbance of the BBB. We aimed at investigating the possibility that the DC EEG could be used to detect the effects of inflammation on the fetal brain. METHODS Fetal sheep were instrumented at 97 days of gestation with catheters, four active EEG electrodes placed on the dura mater as well as extracranial reference and ground electrodes. After three days of recovery, the bacterial endotoxin lipopolysaccharide (LPS) was given to the fetus (200 ng i.v.). RESULTS Exposure to LPS induced a positive DC shift in parallel to the assumed affection of cerebral function and to the pCO2 elevation. This change was not always obvious in standard EEG. CONCLUSIONS These recordings of fetal DC EEG appear to be the first to be done. They indicate that the effects of inflammation on cerebral function can be monitored by DC EEG. Such monitoring might be feasible also during late stages of labour and in neonates.
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