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Löfhede, Johan
Alternative names
Publications (10 of 17) Show all publications
Sandsjö, L., Löfhede, J., Eriksson, S., Guo, L. & Thordstein, M. (2012). EEG Measurements using Textile Electrodes. Paper presented at ISEK 2012 - XIX Congress of the International Society of Electrophysiology and Kinesiology, Brisbane, Australia, 19-21st July, 2012. Paper presented at ISEK 2012 - XIX Congress of the International Society of Electrophysiology and Kinesiology, Brisbane, Australia, 19-21st July, 2012. CCRE SPINE, The University of Queensland, Brisbane, Australia
Open this publication in new window or tab >>EEG Measurements using Textile Electrodes
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2012 (English)Conference paper, Published paper (Refereed)
Place, publisher, year, edition, pages
CCRE SPINE, The University of Queensland, Brisbane, Australia, 2012
Keywords
Medicinsk teknik, Smarta textilier
National Category
Medical Laboratory and Measurements Technologies
Research subject
Textiles and Fashion (General)
Identifiers
urn:nbn:se:hb:diva-6817 (URN)2320/11307 (Local ID)978-0-646-58228-3 (ISBN)2320/11307 (Archive number)2320/11307 (OAI)
Conference
ISEK 2012 - XIX Congress of the International Society of Electrophysiology and Kinesiology, Brisbane, Australia, 19-21st July, 2012
Available from: 2015-12-22 Created: 2015-12-22
Flisberg, A., Kjellmer, I., Löfhede, J., Lindecrantz, K. & Thordstein, M. (2011). Prognostic capacity of automated quantification of suppression time in the EEG of post-asphyctic full-term neonates. Acta Paediatrica, 100(10), 1338-1343
Open this publication in new window or tab >>Prognostic capacity of automated quantification of suppression time in the EEG of post-asphyctic full-term neonates
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2011 (English)In: Acta Paediatrica, ISSN 0803-5253, E-ISSN 1651-2227, Vol. 100, no 10, p. 1338-1343Article in journal (Refereed) Published
Abstract [en]

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 group of asphyxiated newborn infants. Methods: Twenty-one full-term newborn infants who had been resuscitated for severe birth asphyxia were studied. Eight channel continuous EEG was recorded for prolonged time periods during the first days of life. Artefact detection or rejection was not applied to the signals. The signals were fed through a pretrained classifier and then segmented into burst and suppression periods. Total suppression length per hour was calculated. All surviving patients were followed with structured neurodevelopmental assessments to at least 18 months of age. Results: The patients who developed neurodevelopmental disability or died had significant suppression periods in their EEG during the first days of life while the patients who had a normal follow-up had no or negligible amount of suppression. Conclusions: This new method for automatic quantification of suppression periods in the raw, neonatal EEG discriminates infants with good from those with poor outcome.

Keywords
asphyxia neonatorum, electroencephalogram monitoring, full-term newborn infant, quantification, Medicinteknik
National Category
Engineering and Technology
Identifiers
urn:nbn:se:hb:diva-3204 (URN)10.1111/j.1651-2227.2011.02323.x (DOI)2320/9668 (Local ID)2320/9668 (Archive number)2320/9668 (OAI)
Available from: 2015-11-13 Created: 2015-11-13 Last updated: 2017-11-11Bibliographically approved
Löfhede, J., Thordstein, M., Löfgren, N., Flisberg, A., Rosa-Zurera, M., Kjellmer, I. & Lindecrantz, K. (2010). Automatic classification of background EEG activity in healthy and sick neonates. Journal of Neural Engineering, 7(1)
Open this publication in new window or tab >>Automatic classification of background EEG activity in healthy and sick neonates
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2010 (English)In: Journal of Neural Engineering, ISSN 1741-2560, E-ISSN 1741-2552, Vol. 7, no 1Article in journal (Refereed) Published
Abstract [en]

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%.

Place, publisher, year, edition, pages
Institute of Physics Publishing Ltd., 2010
Keywords
neonatal, EEG, signal processing, classification, medicin, fysiologi, farmakologi, neonatal care, Medicinteknik
National Category
Medical and Health Sciences Physiology Physiology Physiology Biomedical Laboratory Science/Technology
Identifiers
urn:nbn:se:hb:diva-2779 (URN)10.1088/1741-2560/7/1/016007 (DOI)2320/6145 (Local ID)2320/6145 (Archive number)2320/6145 (OAI)
Note

Sponsorship:

Stiftelsen Margarethahemmet

ALF

BIOPATTERN EU Network of Excellence, EU contract 508803

Available from: 2015-11-13 Created: 2015-11-13 Last updated: 2018-01-10Bibliographically approved
Flisberg, A., Kjellmer, I., Löfhede, J., Löfgren, N., Rosa-Zurera, M., Lindecrantz, K. & Thordstein, M. (2010). Does indomethacin for closure of patent ductus arteriosus affect cerebral function?. Acta Paediatrica, 99(10), 1493-1497
Open this publication in new window or tab >>Does indomethacin for closure of patent ductus arteriosus affect cerebral function?
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2010 (English)In: Acta Paediatrica, ISSN 0803-5253, E-ISSN 1651-2227, Vol. 99, no 10, p. 1493-1497Article in journal (Refereed) Published
Abstract [en]

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.

Place, publisher, year, edition, pages
Wiley-Blackwell Publishing Ltd., 2010
Keywords
Medicinteknik
National Category
Biomedical Laboratory Science/Technology
Identifiers
urn:nbn:se:hb:diva-2846 (URN)10.1111/j.1651-2227.2010.01857.x (DOI)2320/6892 (Local ID)2320/6892 (Archive number)2320/6892 (OAI)
Available from: 2015-11-13 Created: 2015-11-13 Last updated: 2017-11-13Bibliographically approved
Löfhede, J., Seoane Martínez, F. & Thorstein, M. (2010). Soft Textile Electrodes for EEG Monitoring. In: : . Paper presented at 10th IEEE International Conference on Information Technology and Applications, Corfu, Greece. Nov 2010.
Open this publication in new window or tab >>Soft Textile Electrodes for EEG Monitoring
2010 (English)Conference paper, Published paper (Refereed)
Keywords
Medicinteknik
National Category
Engineering and Technology
Identifiers
urn:nbn:se:hb:diva-6489 (URN)2320/7363 (Local ID)2320/7363 (Archive number)2320/7363 (OAI)
Conference
10th IEEE International Conference on Information Technology and Applications, Corfu, Greece. Nov 2010
Available from: 2015-12-22 Created: 2015-12-22 Last updated: 2016-12-01Bibliographically approved
Löfhede, J. (2009). The EEG of the neonatal brain: classification of background activity. (Doctoral dissertation). Göteborg : Chalmers University of Technology
Open this publication in new window or tab >>The EEG of the neonatal brain: classification of background activity
2009 (English)Doctoral thesis, monograph (Other academic)
Abstract [en]

The brain requires a continuous supply of oxygen and nutrients, and even a short period of reduced oxygen supply can cause severe and lifelong consequences for the affected individual. The unborn baby is fairly robust, but there are of course limits also for these individuals. The most sensitive and most important organ is the brain. When the brain is deprived of oxygen, a process can start that ultimately may lead to the death of brain cells and irreparable brain damage. This process has two phases; one more or less immediate and one delayed. There is a window of time of up to 24 hours where action can be taken to prevent the delayed secondary damage. One recently clinically available technique is to reduce the metabolism and thereby stop the secondary damage in the brain by cooling the baby. It is important to be able to quickly diagnose hypoxic injuries and to follow the development of the processes in the brain. For this, the electroencephalogram (EEG) is an important tool. The EEG is a voltage signal that originates within the brain and that can be recorded easily and non-invasively at bedside. The signals are, however, highly complex and require special competence to interpret, a competence that typically is not available at the intensive care unit, and particularly not continuously day and night. This thesis addresses the problem of automatic classification of neonatal EEG and proposes methods that would be possible to use in bedside monitoring equipment for neonatal intensive care units. The thesis is a compilation of six papers. The first four deal with the segmentation of pathological signals (burst suppression) from post-asphyctic full term newborn babies. These studies investigate the use of various classification techniques, using both supervised and unsupervised learning. In paper V the scope is widened to include both classification of pathological activity versus activity found in healthy babies as well as application of the segmentation methods on the parts of the EEG signal that are found to be of the pathological type. The use of genetic algorithms for feature selection is also investigated. In paper VI the segmentation methods are applied on signals from pre-term babies to investigate the impact of a certain medication on the brain. The results of this thesis demonstrate ways to improve the monitoring of the brain during intensive care of newborn babies. Hopefully it will someday be implemented in monitoring equipment and help to prevent permanent brain damage in post asphyctic babies.

Place, publisher, year, edition, pages
Göteborg : Chalmers University of Technology, 2009
Series
Skrifter från Högskolan i Borås, ISSN 0280-381X ; 19
Series
Doktorsavhandlingar vid Chalmers tekniska högskola. Ny serie, ISSN 0346-718X ; 3020
Keywords
asphyxia, hypoxia, cerebral, segmentation, Medicinteknik
National Category
Physiology Signal Processing Biomedical Laboratory Science/Technology
Identifiers
urn:nbn:se:hb:diva-3533 (URN)2320/5740 (Local ID)978-91-7385-339-2 (ISBN)2320/5740 (Archive number)2320/5740 (OAI)
Available from: 2015-12-04 Created: 2015-12-04 Last updated: 2018-01-10
Löfhede, J., Löfgren, N., Thordstein, M., Flisberg, A., Kjellmer, I. & Lindecrantz, K. (2008). Classification of burst and suppression in the neonatal electroencephalogram. Journal of Neural Engineering, 5(4), 402-410
Open this publication in new window or tab >>Classification of burst and suppression in the neonatal electroencephalogram
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2008 (English)In: Journal of Neural Engineering, ISSN 1741-2560, E-ISSN 1741-2552, Vol. 5, no 4, p. 402-410Article in journal (Refereed) Published
Abstract [en]

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.

Place, publisher, year, edition, pages
Institute of Physics Publishing Ltd., 2008
Keywords
EEG, classification, burst, suppression, neonatal, neonatal care, Medicinteknik
National Category
Physiology Biomedical Laboratory Science/Technology Signal Processing
Identifiers
urn:nbn:se:hb:diva-2455 (URN)10.1088/1741-2560/5/4/005 (DOI)2320/4176 (Local ID)2320/4176 (Archive number)2320/4176 (OAI)
Available from: 2015-11-13 Created: 2015-11-13 Last updated: 2018-01-10Bibliographically approved
Löfhede, J., Löfgren, N., Thordstein, M., Flisberg, A., Kjellmer, I. & Lindecrantz, K. (2008). Classification of Burst Suppression and Tracé Alternant in Neonatal EEG. In: Proceedings of Medicinteknikdagarna 2008. Annual conference of Svensk Förening för Medicinsk Teknik och Fysik, Göteborg, Oct., 2008: . Paper presented at Medicinteknikdagarna 2008. Annual conference of Svensk Förening för Medicinsk Teknik och Fysik, Göteborg, Oct., 2008.
Open this publication in new window or tab >>Classification of Burst Suppression and Tracé Alternant in Neonatal EEG
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2008 (English)In: Proceedings of Medicinteknikdagarna 2008. Annual conference of Svensk Förening för Medicinsk Teknik och Fysik, Göteborg, Oct., 2008, 2008Conference paper, Published paper (Refereed)
Keywords
EEG, classification, burst, suppression, tracé alternant, neonatal, neonatal care, Medicinteknik
National Category
Physiology Signal Processing Biomedical Laboratory Science/Technology
Identifiers
urn:nbn:se:hb:diva-6076 (URN)2320/4510 (Local ID)2320/4510 (Archive number)2320/4510 (OAI)
Conference
Medicinteknikdagarna 2008. Annual conference of Svensk Förening för Medicinsk Teknik och Fysik, Göteborg, Oct., 2008
Available from: 2015-12-22 Created: 2015-12-22 Last updated: 2018-01-10Bibliographically approved
Löfhede, J., Degerman, J., Löfgren, N., Thordstein, M., Flisberg, A., Kjellmer, I. & Lindecrantz, K. (2008). Comparing a Supervised and an Unsupervised Classification Method for Burst Detection in Neonatal EEG. In: Proceedings of Engineering in Medicine and Biology Society, EMBS 2008. 30th Annual International Conference of the IEEE, 20-24 August, 2008: . Paper presented at Engineering in Medicine and Biology Society, EMBS 2008. 30th Annual International Conference of the IEEE, 20-24 August, 2008 (pp. 3836-3839). IEEE
Open this publication in new window or tab >>Comparing a Supervised and an Unsupervised Classification Method for Burst Detection in Neonatal EEG
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2008 (English)In: Proceedings of Engineering in Medicine and Biology Society, EMBS 2008. 30th Annual International Conference of the IEEE, 20-24 August, 2008, IEEE , 2008, p. 3836-3839Conference paper, Published paper (Refereed)
Abstract [en]

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.

Place, publisher, year, edition, pages
IEEE, 2008
Keywords
EEG, classification, burst, suppression, neonatal, neonatal care, Medicinteknik
National Category
Physiology Signal Processing Biomedical Laboratory Science/Technology
Identifiers
urn:nbn:se:hb:diva-5990 (URN)2320/4180 (Local ID)978-1-4244-1814-5 (ISBN)2320/4180 (Archive number)2320/4180 (OAI)
Conference
Engineering in Medicine and Biology Society, EMBS 2008. 30th Annual International Conference of the IEEE, 20-24 August, 2008
Available from: 2015-12-22 Created: 2015-12-22 Last updated: 2018-01-10Bibliographically approved
Thordstein, M., Kjellmer, I., Löfgren, N., Löfhede, J., Lindecrantz, K., Dean, J. & Mallard, C. (2008). Effects of inflammation on cerebral electric activity in fetal sheep. In: : . Paper presented at 4´th EURAIBI International meeting, Siena 3-5 april, 2008 and 2nd Congress of the European Academy of Paediatrics, Nice, 23-28 oktober, 2008..
Open this publication in new window or tab >>Effects of inflammation on cerebral electric activity in fetal sheep
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2008 (English)Conference paper, Poster (with or without abstract) (Other academic)
Abstract [en]

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.

Keywords
Medicinteknik
National Category
Physiology Signal Processing Biomedical Laboratory Science/Technology
Identifiers
urn:nbn:se:hb:diva-5992 (URN)2320/4178 (Local ID)2320/4178 (Archive number)2320/4178 (OAI)
Conference
4´th EURAIBI International meeting, Siena 3-5 april, 2008 and 2nd Congress of the European Academy of Paediatrics, Nice, 23-28 oktober, 2008.
Available from: 2015-12-22 Created: 2015-12-22 Last updated: 2018-01-10Bibliographically approved
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