| 1. |
- Campagnoli, Monica, et al.
(författare)
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A novel splicing mutation causes an undescribed type of analbuminemia.
- 2002
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Ingår i: Biochimica et biophysica acta. - 0006-3002. ; 1586:1, s. 43-9
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Tidskriftsartikel (refereegranskat)abstract
- Analbuminemia is a rare autosomal recessive disorder manifested by the absence or severe reduction of circulating serum albumin in homozygous subjects. In this report we describe a new molecular defect that caused the analbuminemic trait in a newborn of Iraqi origin. When the parents' DNA was analyzed, both subjects were found to be heterozygous for the same mutation found in the infant. All the 14 exon and flanking intron sequences of the albumin gene were amplified via PCR and screened for mutations by SSCP and heteroduplex analysis. A mutation in the DNA region encoding exon 1 and its flanking intron was revealed by the presence of a heteroduplex. The fragment, which was directly DNA sequenced, contains a previously unreported single nucleotide change, consisting in a G to A substitution at nucleotide 118 in the structural gene of the human protein. This mutation, involving the first base of intron 1, destroys the GT dinucleotide consensus sequence found at the 5' end of most intervening sequences and causes the defective pre-mRNA splicing responsible for the analbuminemic trait.
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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. |
- Flisberg, Anders, 1958, et al.
(författare)
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EEG and spectral edge frequency : analysis in posthypoxic newborn piglets
- 2010
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Ingår i: Neuro - endocrinology letters. - : Brain Research Promotion. - 0172-780X. ; 31:2, s. 181-186
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Tidskriftsartikel (refereegranskat)abstract
- OBJECTIVE: To evaluate the frequency content of the electroencephalogram (EEG) during recovery after a severe hypoxic insult in newborn piglets. METHODS: EEG was continuously monitored in nine newborn piglets exposed to a severe hypoxic period. Power spectra in five frequency bands were calculated using Fourier transformation. Spectral edge frequency 90 (SEF90) was defined as the frequency below which 90% of the power in the EEG was located. The piglets were divided into two groups; Group 1 represented piglets with some EEG recovery and Group 2 represented piglets without any EEG recovery. RESULTS: The recovery of the EEG in Group 1 had the same time course in all frequency bands. SEF90 indicates recovery earlier than the value of total power. But SEF90 also signals activity in the EEGs that were almost completely suppressed. When SEF90 was calculated during periods of periodic EEG activity during the very early phase of recovery, the values fell within the same range as during the control period. CONCLUSION: Spectral analysis of continuous EEG in newborn piglets exposed to very severe hypoxia showed that no specific frequency band of the EEG preceded the other ones during recovery. The results of the SEF90 measure, demonstrates the need for critical analysis of the raw EEG before any reliable estimation of cerebral function can be made.
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| 4. |
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| 5. |
- Gu, Irene Yu-Hua, 1953, et al.
(författare)
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3D Limb Movement Tracking and Analysis for Neurological Dysfunctions of Neonates Using Multi-Camera Videos
- 2016
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Ingår i: Proceedings of the Annual International Conference of the IEEE Engineering in Medicine and Biology Society, EMBS. - 1557-170X. - 9781457702204 ; 2016-October, s. 2395-2398
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Konferensbidrag (refereegranskat)abstract
- Central nervous system dysfunction in infants may be manifested through inconsistent, rigid and abnormal limb movements. Detection of limb movement anomalies associated with such neurological dysfunctions in infants is the first step towards early treatment for improving infant development. This paper addresses the issue of detecting and quantifying limb movement anomalies in infants through non-invasive 3D image analysis methods using videos from multiple camera views. We propose a novel scheme for tracking 3D time trajectories of markers on infant’s limbs by video analysis techniques. The proposed scheme employ videos captured from three camera views. This enables us to detect a set of enhanced 3D markers through cross-view matching and to effectively handle marker self-occlusions by other body parts. We track a set of 3D trajectories of limb movements by a set of particle filters in parallel, enabling more robust 3D tracking of markers, and use the 3D model errors for quantifying abrupt limb movements. The proposed work makes a significant advancement to the previous work in [1] through employing tracking in 3D space, and hence overcome several main barriers that hinder real applications by using single camera-based techniques. To the best of our knowledge, applying such a multi-view video analysis approach for assessing neurological dysfunctions of infants through 3D time trajectories of markers on limbs is novel, and could lead to computer-aided tools for diagnosis of dysfunctions where early treatment may improve infant development. Experiments were conducted on multi-view neonate videos recorded in a clinical setting and results have provided further support to the proposed method.
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| 6. |
- Löfgren, N., et al.
(författare)
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On evaluation of spectrum estimators for EEG
- 2004
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Ingår i: Proceedings Of The 26th Annual International Conference Of The IEEE Engineering In Medicine And Biology Society. - : IEEE. - 0780384393 ; 1, s. 305-9
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Konferensbidrag (refereegranskat)abstract
- In the search for how neonatal EEG is affected by asphyxia it is of importance to find reliable estimates of EEG power spectra. Several spectral estimation methods do exist, but since the true spectra are unknown it is hard to tell how well the estimators perform. Therefore a model to generate simulated EEG with known spectrum is proposed and the model is used to evaluate performance of several parametric and Fourier based spectral estimators.
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| 7. |
- Löfgren, Nils, 1969, et al.
(författare)
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Spectral distance for ARMA models applied to electroencephalogram for early detection of hypoxia
- 2006
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Ingår i: Journal of Neural Engineering. - : IOP Publishing. - 1741-2560 .- 1741-2552. ; 3:3, s. 227-34
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Tidskriftsartikel (refereegranskat)abstract
- A novel measure of spectral distance is presented, which is inspired by the prediction residual parameter presented by Itakura in 1975, but derived from frequency domain data and extended to include autoregressive moving average (ARMA) models. This new algorithm is applied to electroencephalogram (EEG) data from newborn piglets exposed to hypoxia for the purpose of early detection of hypoxia. The performance is evaluated using parameters relevant for potential clinical use, and is found to outperform the Itakura distance, which has proved to be useful for this application. Additionally, we compare the performance with various algorithms previously used for the detection of hypoxia from EEG. Our results based on EEG from newborn piglets show that some detector statistics divert significantly from a reference period less than 2 min after the start of general hypoxia. Among these successful detectors, the proposed spectral distance is the only spectral-based parameter. It therefore appears that spectral changes due to hypoxia are best described by use of an ARMA- model-based spectral estimate, but the drawback of the presented method is high computational effort.
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| 8. |
- 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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| 9. |
- 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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| 10. |
- 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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