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Träfflista för sökning "AMNE:(MEDICAL AND HEALTH SCIENCES Basic Medicine Physiology) ;lar1:(hb)"

Sökning: AMNE:(MEDICAL AND HEALTH SCIENCES Basic Medicine Physiology) > Högskolan i Borås

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1.
  • Karlsson, Kåre, et al. (författare)
  • Heart rate as a marker of stress in ambulance personnel : A pilot study of the body's response to the ambulance alarm
  • 2011
  • Ingår i: Prehospital and Disaster Medicine. - : Cambridge University Press. - 1049-023X .- 1945-1938. ; 26:1, s. 21-26
  • Tidskriftsartikel (refereegranskat)abstract
    • Introduction: Studies have demonstrated the presence of stress and post-traumatic stress among ambulance personnel, but no previous research has focused on the body's reaction in the form of the change in heart rate of ambulance staff in association with specific occupational stress.Hypothesis: The purpose of this study is to investigate whether work as an ambulance professional generates prolonged physiological arousal that can be measured by heart rate in different situations.Methods: Twenty participants carried a pulse-meter in the form of a wristwatch, which continuously measured and stored their heart rate 24 hours per day for a period of seven days. All ambulance alarms that occurred during the test period were recorded in journals, and the participants completed diaries and a questionnaire describing their experiences. The alarms were divided into different phases. Correlations between heart rate in the different phases were computed.Results: Analysis of study data indicated a significant rise of heart rate unrelated to physical effort during an emergency alarm and response. This increased heart rate was noticed throughout the mission and it was not related to the length of experience the staff had in the ambulance profession. In addition, a non-significant trend suggested that alarms involving acutely ill children lead to an even higher increase in heart rate. In addition, this research showed that constant tension existed during sleep, while available for an emergency, indicated by a noticeable increase in heart rate during sleep at work compared to sleeping at home.Conclusions: A rise in heart rate was experienced during all acute emergency missions, regardless of a subject's experience, education, and gender. Missions by themselves generated a rate increase that did not seem to correlate with physical effort required during an emergency response. This study shows that working on an ambulance that responds to medical emergencies is associated with a prolonged physiological arousal.
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2.
  • Löfhede, Johan, et al. (författare)
  • Classification of burst and suppression in the neonatal electroencephalogram
  • 2008
  • Ingår i: Journal of Neural Engineering. - : Institute of Physics Publishing Ltd.. - 1741-2560 .- 1741-2552. ; 5:4, s. 402-410
  • 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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3.
  • Löfhede, Johan, et al. (författare)
  • Comparing a Supervised and an Unsupervised Classification Method for Burst Detection in Neonatal EEG
  • 2008
  • 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
  • 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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4.
  • Flisberg, Anders, 1958, et al. (författare)
  • EEG and spectral edge frequency : analysis in posthypoxic newborn piglets
  • 2010
  • Ingår i: Neuro - endocrinology letters. - : Brain Research Promotion. - 0172-780X. ; 31:2, s. 181-186
  • 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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5.
  • Seoane, Fernando, 1976-, et al. (författare)
  • Brain electrical impedance at various frequencies : the effect of hypoxia
  • 2004
  • Ingår i: Proceedings of the 26th Annual International Conference of the IEEE EMBS, San Francisco, CA, USA • September 1-5, 2004. - : IEEE Engineering in Medicine and Biology Society. - 0780384393 ; 3, s. 2322-5
  • Konferensbidrag (refereegranskat)abstract
    • Non-invasive multi-frequency measurements of transcephalic impedance, both reactance and resistance, can efficiently detect cell swelling of brain tissue and can be used for early detection of threatening brain damage. We have performed experiments on piglets to monitor transcephalic impedance during hypoxia. The obtained results have confirmed the hypothesis that changes in the size of cells modify the tissue impedance. During tissue inflammation after induced hypoxia, cerebral tissue exhibits changes in both reactance and resistance. Those changes are remarkably high, up to 71% over the baseline, and easy to measure especially at certain frequencies. A better understanding of the electrical behaviour of cerebral tissue during cell swelling would lead us to develop effective non-invasive clinical tools and methods for early diagnosis of cerebral edema and brain damage prevention.
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6.
  • Löfhede, Johan, 1978 (författare)
  • Classification of Burst and Suppression in the Neonatal EEG
  • 2007
  • Licentiatavhandling (övrigt vetenskapligt/konstnärligt)abstract
    • The brain requires a continuous supply of oxygen and even a short period of reduced oxygen supply risks severe and lifelong consequences for the affected individual. The delivery is a vulnerable period for a baby who may experience for example hypoxia (lack of oxygen) that can damage the brain. Babies who experience problems are placed in an intensive care unit where their vital signs are monitored, but there is no reliable way to monitor the brain directly. Monitoring the brain would provide valuable information about the processes going on in it and could influence the treatment and help to improve the quality of neonatal care. The scope of this project is to develop methods that eventually can be put together to form a monitoring system for the brain that can function as decision-support for the physician in charge of treating the patient.The specific technical problem that is the topic of this thesis is detection of burst and suppression in the electroencephalogram (EEG) signal. The thesis starts with a brief description of the brain, with a focus on where the EEG originates, what types of activity can be found in this signal and what they mean. The data that have been available for the project are described, followed by the signal processing methods that have been used for pre-processing, and the feature functions that can be used for extracting certain types of characteristics from the data are defined. The next section describes classification methodology and how it can be used for making decisions based on combinations of several features extracted from a signal. The classification methods Fisher’s Linear Discriminant, Neural Networks and Support Vector Machines are described and are finally compared with respect to their ability to discriminate between burst and suppression. An experiment with different combinations of features in the classification has also been carried out. The results show similar results for the three methods but it can be seen that the SVM is the best method with respect to handling multiple features.
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9.
  • Löfhede, Johan, 1978 (författare)
  • The EEG of the Neonatal Brain – Classification of Background Activity
  • 2009
  • Doktorsavhandling (övrigt vetenskapligt/konstnärligt)abstract
    • 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 easily and non-invasively can be recorded 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. This thesis addresses the problem of automatic classification of neonatal EEG and proposes methods that would be possible to use in bed-side 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.
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