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  • Public defence: 2020-03-06 10:15 Ada Lovelace, Building B, Linköping
    Voronov, Sergii
    Linköping University, Department of Electrical Engineering, Vehicular Systems. Linköping University, Faculty of Science & Engineering.
    Machine Learning Models for Predictive Maintenance2020Doctoral thesis, comprehensive summary (Other academic)
    Abstract [en]

    The amount of goods produced and transported around the world each year increases and heavy-duty trucks are an important link in the logistic chain. To guarantee reliable delivery a high degree of availability is required, i.e., avoid standing by the road unable to continue the transport mission. Unplanned stops by the road do not only cost due to the delay in delivery, but can also lead to damaged cargo. Vehicle downtime can be reduced by replacing components based on statistics of previous failures. However, such an approach is both expensive due to the required frequent visits to a workshop and inefficient as many components from the vehicles in the fleet are still operational. A prognostic method, allowing for vehicle individualized maintenance plans, therefore poses a significant potential in the automotive field. The prognostic method estimates component degradation and remaining useful life based on recorded data and how the vehicle has been operated.

    Lead-acid batteries is a part of the electrical power system in a heavy-duty truck, primarily responsible for powering the starter motor but also powering auxiliary units, e.g., cabin heating and kitchen equipment, which makes the battery a vital component for vehicle availability. Developing physical models of battery degradation is a difficult process which requires access to battery health sensing that is not available in the given study as well a detailed knowledge of battery chemistry.

    An alternative approach, considered in this work, is data-driven methods based on large amounts of logged data describing vehicle operation conditions. In the use-case studied, recorded data is not closely related to battery health which makes battery prognostic challenging. Data is collected during infrequent and non-equidistant visits to a workshop and there are complex dependencies between variables in the data. The main aim of this work has been to develop a framework and methods for estimating lifetime of lead-acid batteries using data-driven methods for condition-based maintenance. The methodology is general and can be applicable for prognostics of other components.

    A main contribution of the thesis is development of machine learning models for predictive maintenance, estimating conditional reliability functions, using Random Survival Forests (RSF) and recurrent neural networks (RNN). An important property of the data is that for a specific vehicle there may be multiple data readouts, but also one single data readout which makes predictive modeling challenging and dealing with this situation is discussed for both RSF and neural networks models. Data quality is important when building data-driven models, and here the data is imbalanced since there are few battery failures relative to the number of vehicles. Further, the data includes many uninformative variables and among those that are informative, there are complex dependencies and correlation. Methods for selecting which data features to use in the model in this situation is also a key contribution. When a point estimation of the conditional reliability functions is available, it is of interest to know how uncertain the estimate is as it allows to take quality of the prediction into account when deciding on maintenance actions. A theory for estimating the variance of the RSF predictor is another contribution in the thesis. To conclude, the results show that Long Short-Term Memory networks, which is a type of RNN, is the most suitable for the vehicle operational data and give the best performance among methods evaluated in the thesis.

    List of papers
    1. Heavy-duty truck battery failure prognostics using random survival forests
    Open this publication in new window or tab >>Heavy-duty truck battery failure prognostics using random survival forests
    2016 (English)In: IFAC PAPERSONLINE, ELSEVIER SCIENCE BV , 2016, Vol. 49, no 11, p. 562-569Conference paper, Published paper (Refereed)
    Abstract [en]

    Predicting lead-acid battery failure is important for heavy-duty trucks to avoid unplanned stops by the road. There are large amount of data from trucks in operation, however, data is not closely related to battery health which makes battery prognostic challenging. A new method for identifying important variables for battery failure prognosis using random survival forests is proposed. Important variables are identified and the results of the proposed method are compared to existing variable selection methods. This approach is applied to generate a prognosis model for lead-acid battery failure in trucks and the results are analyzed. (C) 2016, IFAC (International Federation of Automatic Control) Hosting by Elsevier Ltd. All rights reserved.

    Place, publisher, year, edition, pages
    ELSEVIER SCIENCE BV, 2016
    Keywords
    Battery failure prognosis; Random survival forests; Variable selection
    National Category
    Transport Systems and Logistics
    Identifiers
    urn:nbn:se:liu:diva-132240 (URN)10.1016/j.ifacol.2016.08.082 (DOI)000383464400082 ()
    Conference
    8th IFAC Symposium on Advances in Automotive Control (AAC)
    Available from: 2016-10-24 Created: 2016-10-21 Last updated: 2020-01-24
    2. Variable selection for heavy-duty vehicle battery failure prognostics using random survival forests
    Open this publication in new window or tab >>Variable selection for heavy-duty vehicle battery failure prognostics using random survival forests
    2016 (English)In: PHME 2016 Proceedings of the Third European Conference of the Prognostics and Health Management Society 2016, Bilbao, Spain July 5–8, 2016 / [ed] Ioana Eballard and Anibal Bregon, 2016, p. 649-659Conference paper, Published paper (Refereed)
    Abstract [en]

    Prognostics and health management is a useful tool for more flexible maintenance planning and increased system reliability. The application in this study is lead-acid battery failure prognosis for heavy-duty trucks which is important to avoid unplanned stops by the road. There are large amounts of data available, logged from trucks in operation. However, datais not closely related to battery health which makes battery prognostic challenging. When developing a data-driven prognostics model and the number of available variables is large,variable selection is an important task, since including non-informative variables in the model have a negative impact on prognosis performance. Two features of the dataset has been identified, 1) few informative variables, and 2) highly correlated variables in the dataset. The main contribution is a novel method for identifying important variables, taking these two properties into account, using Random Survival Forests to estimate prognostics models. The result of the proposed method is compared to existing variable selection methods,and applied to a real-world automotive dataset. Prognostic models with all and reduced set of variables are generated and differences between the model predictions are discussed, and favorable properties of the proposed approach are highlighted.

    Keywords
    variable selection, random survival forest, battery failure prognostics
    National Category
    Other Electrical Engineering, Electronic Engineering, Information Engineering
    Identifiers
    urn:nbn:se:liu:diva-131788 (URN)978-1-936263-21-9 (ISBN)
    Conference
    Third European Conference of the Prognostics and Health Management Society 2016, Bilbao, July 5-8, 2016
    Available from: 2016-10-06 Created: 2016-10-06 Last updated: 2020-01-24Bibliographically approved
    3. Data-Driven Battery Lifetime Prediction and Confidence Estimation for Heavy-Duty Trucks
    Open this publication in new window or tab >>Data-Driven Battery Lifetime Prediction and Confidence Estimation for Heavy-Duty Trucks
    2018 (English)In: IEEE Transactions on Reliability, ISSN 0018-9529, E-ISSN 1558-1721, Vol. 67, no 2, p. 623-639Article in journal (Refereed) Published
    Abstract [en]

    Maintenance planning is important in the automotive industry as it allows fleet owners or regular customers to avoid unexpected failures of the components. One cause of unplanned stops of heavy-duty trucks is failure in the lead-acid starter battery. High availability of the vehicles can be achieved by changing the battery frequently, but such an approach is expensive both due to the frequent visits to a workshop and also due to the component cost. Here, a data-driven method based on random survival forest (RSF) is proposed for predicting the reliability of the batteries. The dataset available for the study, covering more than 50 000 trucks, has two important properties. First, it does not contain measurements related directly to the battery health; second, there are no time series of measurements for every vehicle. In this paper, the RSF method is used to predict the reliability function for a particular vehicle using data from the fleet of vehicles given that only one set of measurements per vehicle is available. A theory for confidence bands for the RSF method is developed, which is an extension of an existing technique for variance estimation in the random forest method. Adding confidence bands to the RSF method gives an opportunity for an engineer to evaluate the confidence of the model prediction. Some aspects of the confidence bands are considered: their asymptotic behavior and usefulness in model selection. A problem of including time-related variables is addressed in this paper with the argument that why it is a good choice not to add them into the model. Metrics for performance evaluation are suggested, which show that the model can be used to schedule and optimize the cost of the battery replacement. The approach is illustrated extensively using the real-life truck data case study.

    Place, publisher, year, edition, pages
    IEEE-INST ELECTRICAL ELECTRONICS ENGINEERS INC, 2018
    Keywords
    Battery lifetime prognostics; data-driven prediction; flexible maintenance; infinitesimal jackknife (IJ) confidence bands; reliability
    National Category
    Other Computer and Information Science
    Identifiers
    urn:nbn:se:liu:diva-149358 (URN)10.1109/TR.2018.2803798 (DOI)000433911000015 ()
    Note

    Funding Agencies|Scania CV; FFI (Vehicle Strategic Research and Innovation)

    Available from: 2018-07-02 Created: 2018-07-02 Last updated: 2020-01-24
    4. Lead-acid battery maintenance using multilayer perceptron models
    Open this publication in new window or tab >>Lead-acid battery maintenance using multilayer perceptron models
    2018 (English)In: 2018 IEEE International Conference on Prognostics and Health Management (ICPHM), 2018, p. 1-8Conference paper, Published paper (Refereed)
    Abstract [en]

    Predictive maintenance of components has the potential to significantly reduce costs for maintenance and to reduce unexpected failures. Failure prognostics for heavy-duty truck lead-acid batteries is considered with a multilayer perceptron (MLP) predictive model. Data used in the study contains information about how approximately 46,000 vehicles have been operated starting from the delivery date until the date when they come to the workshop. The model estimates a reliability and lifetime probability function for a vehicle entering a workshop. First, this work demonstrates how heterogeneous data is handled, then the architectures of the MLP models are discussed. Main contributions are a battery maintenance planning method and predictive performance evaluation based on reliability and lifetime functions, a new model for reliability function when its true shape is unknown, the improved objective function for training MLP models, and handling of imbalanced data and comparison of performance of different neural network architectures. Evaluation shows significant improvements of the model compared to more simple, time-based maintenance plans.

    Keywords
    lead acid batteries, neural nets, preventive maintenance, reliability, lead-acid battery maintenance, MLP models, neural network architectures, reliability function, lifetime functions, predictive performance evaluation, battery maintenance planning method, heterogeneous data, lifetime probability function, multilayer perceptron predictive model, heavy-duty truck lead-acid batteries, failure prognostics, predictive maintenance, simple time-based maintenance plans, improved objective function, Batteries, Histograms, Maintenance engineering, Data models, Neural networks, Conferences
    National Category
    Transport Systems and Logistics
    Identifiers
    urn:nbn:se:liu:diva-163289 (URN)10.1109/ICPHM.2018.8448472 (DOI)
    Conference
    2018 IEEE International Conference on Prognostics and Health Management (ICPHM)
    Available from: 2020-01-24 Created: 2020-01-24 Last updated: 2020-01-24Bibliographically approved
  • Public defence: 2020-03-06 10:15 K3, Kåkenhus, Norrköping
    Seitanidou, Maria S
    Linköping University, Department of Science and Technology, Laboratory of Organic Electronics. Linköping University, Faculty of Science & Engineering.
    Overcoming Limitations of Iontronic Delivery Devices2020Doctoral thesis, comprehensive summary (Other academic)
    Abstract [en]

    Organic electronic devices are considered as one of the best candidates to replace conventional inorganic electronic devices due to their electronic conductive functionality, low-cost production techniques, the ability to tune their optical and electronic properties using organic chemistry, and their mechanical flexibility. Moreover, these systems are ideal for bioelectronic applications due to their softness, biocompatibility, and most importantly, their electronic and ionic transport. Indeed, these materials are compatible with biological tissues and cells improving the signal transduction between electronic devices and electrically excitable cells. As ions serve as one of the primary signal carriers of cells, they can selectively tune a cell’s activity; therefore, an improved interface between electronics and biological systems can offer several advantages in healthcare, e.g. the development of efficient drug delivery devices.  

    The main focus of this thesis is the development of electronic delivery devices. Electrophoretic delivery devices called organic electronic ion pumps (OEIPs) are used to electronically control the delivery of small ions, neurotransmitters, and drugs with high spatiotemporal resolution. This work elucidates the ion transport processes and phenomena that happen in the ion exchange membranes during ion delivery and clarifies which parameters are crucial for the ion transport efficiency of the OEIPs. This thesis shows a systematic investigation of these parameters and indicates new methods and OEIP designs to overcome these challenges. Two novel OEIP designs are developed and introduced in this thesis to improve the local ion transport while limiting side effects. OEIPs based on palladium proton trap contacts can improve the membrane permselectivity and optimize the delivery of γ-aminobutyric acid (GABA) neurotransmitters at low pH while preventing any undesired pH changes from proton transport in the biological systems. And OEIPs based on glass capillary fibers are developed to overcome the limitations of devices on planar substrates, related to more complex and larger biologically relevant ion delivery with low mobility for implantable applications. This design can optimize the transport of ions and drugs such as salicylic acid (SA) at low concentrations and at relatively much higher rates, thereby addressing a wider range of biomedically relevant applications and needs.   

    List of papers
    1. pH Dependence of γ-Aminobutyric Acid Iontronic Transport
    Open this publication in new window or tab >>pH Dependence of γ-Aminobutyric Acid Iontronic Transport
    Show others...
    2017 (English)In: Journal of Physical Chemistry B, ISSN 1520-6106, E-ISSN 1520-5207, Vol. 121, no 30, p. 7284-7289Article in journal (Refereed) Published
    Abstract [en]

    The organic electronic ion pump (OEIP) has been developed as an “iontronic” tool for delivery of biological signaling compounds. OEIPs rely on electrophoretically “pumping” charged compounds, either at neutral or shifted pH, through an ion-selective channel. Significant shifts in pH lead to an abundance of H+ or OH–, which are delivered along with the intended substance. While this method has been used to transport various neurotransmitters, the role of pH has not been explored. Here we present an investigation of the role of pH on OEIP transport efficiency using the neurotransmitter γ-aminobutyric acid (GABA) as the model cationic delivery substance. GABA transport is evaluated at various pHs using electrical and chemical characterization and compared to molecular dynamics simulations, all of which agree that pH 3 is ideal for GABA transport. These results demonstrate a useful method for optimizing transport of other substances and thus broadening OEIP applications.

    Place, publisher, year, edition, pages
    American Chemical Society (ACS), 2017
    National Category
    Electrical Engineering, Electronic Engineering, Information Engineering Chemical Sciences
    Identifiers
    urn:nbn:se:liu:diva-139731 (URN)10.1021/acs.jpcb.7b05218 (DOI)000407189200007 ()28741949 (PubMedID)2-s2.0-85026913272 (Scopus ID)
    Note

    Funding agencies: EU Seventh Framework Programme [607896]; Knut and Alice Wallenberg Foundation [2012.0302]; Onnesjo Foundation

    Available from: 2017-08-14 Created: 2017-08-14 Last updated: 2020-02-17Bibliographically approved
    2. Overcoming transport limitations in miniaturized electrophoretic delivery devices
    Open this publication in new window or tab >>Overcoming transport limitations in miniaturized electrophoretic delivery devices
    2019 (English)In: Lab on a Chip, ISSN 1473-0197, E-ISSN 1473-0189, Vol. 19, no 8, p. 1427-1435Article in journal (Refereed) Published
    Abstract [en]

    Organic electronic ion pumps (OEIPs) have been used for delivery of biological signaling compounds, at high spatiotemporal resolution, to a variety of biological targets. The miniaturization of this technology provides several advantages, ranging from better spatiotemporal control of delivery to reduced invasiveness for implanted OEIPs. One route to miniaturization is to develop OEIPs based on glass capillary fibers that are filled with a polyelectrolyte (cation exchange membrane, CEM). These devices can be easily inserted and brought into close proximity to targeted cells and tissues and could be considered as a starting point for other fiber-based OEIP and iontronic technologies enabling favorable implantable device geometries. While characterizing capillary OEIPs we observed deviations from the typical linear current-voltage behavior. Here we report a systematic investigation of these irregularities by performing experimental characterizations in combination with computational modelling. The cause of the observed irregularities is due to concentration polarization established at the OEIP inlet, which in turn causes electric field-enhanced water dissociation at the inlet. Water dissociation generates protons and is typically problematic for many applications. By adding an ion-selective cap that separates the inlet from the source reservoir this effect is then, to a large extent, suppressed. By increasing the surface area of the inlet with the addition of the cap, the concentration polarization is reduced which thereby allows for significantly higher delivery rates. These results demonstrate a useful approach to optimize transport and delivery of therapeutic substances at low concentrations via miniaturized electrophoretic delivery devices, thus considerably broadening the opportunities for implantable OEIP applications.

    Place, publisher, year, edition, pages
    Royal Society of Chemistry, 2019
    National Category
    Analytical Chemistry
    Identifiers
    urn:nbn:se:liu:diva-157204 (URN)10.1039/c9lc00038k (DOI)000465283700008 ()30875418 (PubMedID)2-s2.0-85064156567 (Scopus ID)
    Note

    Funding Agencies|Swedish Foundation for Strategic Research; Advanced Functional Materials SFO-center at Linkoping University; Onnesjo Foundation; Knut and Alice Wallenberg Foundation

    Available from: 2019-06-14 Created: 2019-06-14 Last updated: 2020-02-17Bibliographically approved
    3. Modulating Inflammation in Monocytes Using Capillary Fiber Organic Electronic Ion Pumps
    Open this publication in new window or tab >>Modulating Inflammation in Monocytes Using Capillary Fiber Organic Electronic Ion Pumps
    Show others...
    2019 (English)In: Advanced Healthcare Materials, ISSN 2192-2640, E-ISSN 2192-2659, Vol. 8, no 19, article id 1900813Article in journal (Refereed) Published
    Abstract [en]

    An organic electronic ion pump (OEIP) delivers ions and drugs from a source, through a charge selective membrane, to a target upon an electric bias. Miniaturization of this technology is crucial and will provide several advantages, ranging from better spatiotemporal control of delivery to reduced invasiveness for implanted OEIPs. To miniaturize OEIPs, new configurations have been developed based on glass capillary fibers filled with an anion exchange membrane (AEM). Fiber capillary OEIPs can be easily implanted in proximity to targeted cells and tissues. Herein, the efficacy of such a fiber capillary OEIP for modulation of inflammation in human monocytes is demonstrated. The devices are located on inflammatory monocytes and local delivery of salicylic acid (SA) is initiated. Highly localized SA delivery results in a significant decrease in cytokine (tumor necrosis factor alpha and interleukin 6) levels after lipopolysaccharide stimulation. The findings-the first use of such capillary OEIPs in mammalian cells or systems-demonstrate the utility of the technology for optimizing transport and delivery of different therapeutic substances at low concentrations, with the benefit of local and controlled administration that limits the adverse effect of oral/systemic drug delivery.

    Place, publisher, year, edition, pages
    WILEY, 2019
    Keywords
    bioelectronics; capillary fibers; cytokines; drug delivery; electrophoresis; inflammation; ion exchange membranes; iontronics; organic electronics
    National Category
    Biophysics
    Identifiers
    urn:nbn:se:liu:diva-161161 (URN)10.1002/adhm.201900813 (DOI)000486128400001 ()31502760 (PubMedID)
    Note

    Funding Agencies|Swedish Foundation for Strategic ResearchSwedish Foundation for Strategic Research [RIT15-0119]; Advanced Functional Materials SFO-Center at Linkoping University; International Interdisciplinary Laboratory for Advanced Functional Materials, Linkopings Universitet; Onnesjo Foundation; Knut and Alice Wallenberg FoundationKnut & Alice Wallenberg Foundation

    Available from: 2019-10-25 Created: 2019-10-25 Last updated: 2020-02-17
  • Public defence: 2020-03-13 09:00 Hasselquistsalen, Building 511, Linköping
    Israelsson, Johan
    Linköping University, Faculty of Medicine and Health Sciences. Linköping University, Department of Health, Medicine and Caring Sciences, Division of Nursing Sciences and Reproductive Health.
    Health-related quality of life after cardiac arrest2020Doctoral thesis, comprehensive summary (Other academic)
    Abstract [en]

    Background: Cardiac arrest is a major health problem worldwide. For many of the afflicted, cardiac arrest is the natural end of life. For others, it is an unexpected event suddenly striking in the middle of life. During the last decades, major efforts in treatment have contributed to more people surviving their cardiac arrest. However, previous research has mainly focused on survival, while the knowledge about health-related quality of life in survivors is sparse. Hence, there is a need for more research in order to extend the knowledge about the living situations among survivors and their spouses. For example, factors associated with health-related quality of life are not sufficiently investigated. Knowledge about such factors is important in order to develop interventions and to be able to improve post cardiac arrest care. In addition, existing research shows incongruent results concerning differences in characteristics and survival between men and women. In order to provide equitable care between sexes, further studies are warranted.

    Aim: The overall aim of this thesis was to increase the knowledge of survival and health-related quality of life among people suffering cardiac arrest with focus on sex and other related factors. The specific aims were: to describe in-hospital cardiac arrest events with regard to sex and investigate if sex is associated with survival after controlling for known predictors and interaction effects (study I), to describe health status and psychological distress among in-hospital cardiac arrest survivors in relation to sex (study II), to investigate factors associated with health-related quality of life among cardiac arrest survivors treated with an implantable cardioverter defibrillator in relation to sex, and to compare their health-related quality of life with a general population, (study III) and to investigate if type D personality and perceived control among cardiac arrest survivors and their spouses were associated with their own and their partners’ health-related quality of life (study IV).

    Methods: The general design in all studies (I-IV) was quantitative, cross-sectional and correlational. This thesis is based on four different data collections. Data was systematically collected using national quality registries (I and II) or by sending questionnaires to survivors (III and IV) and their spouses (IV), treated at several different hospitals in Sweden. The sample size varied between 126 and 990 across the studies. The outcomes and explanatory study variables were chosen with respect to Wilson and Cleary’s conceptual model of health-related quality of life. The main outcome variables were survival after resuscitation, survival at hospital discharge, survival at 30 days post cardiac arrest (I), and health-related quality of life measured by the Hospital Anxiety and Depression Scale (II and III) and the EuroQol-5 dimensions (II-IV). In this thesis descriptive and inferential statistics were applied. The main statistics consisted of logistic and linear regression analyses, and structural equation modelling.

    Results: Male sex was associated with a better chance of survival to hospital discharge, but no associations between sex and survival after resuscitation or at 30 days were identified. More men than women received resuscitation attempts when suffering an in-hospital cardiac arrest (study I). Health-related quality of life among most cardiac arrest survivors was good (II-IV), even when compared to a general population (III). However, a significant proportion reported low health status and symptoms of anxiety and depression (II and III). Women reported worse health-related quality of life compared to men, and female sex was associated with poorer health-related quality of life in the multiple regression models (II and III). Several additional factors were identified to be associated with poorer health-related quality of life: being unemployed, having a type D personality, perceiving less control, suffering from more comorbidities and suffering from more ICD-related concerns (III). In addition, older age was associated with poorer (EQ VAS) or better (HADS Anxiety) health-related quality of life, depending of outcome measure (II). Moreover, perceived control and type D personality among the survivors were associated with health-related quality of life among their spouses, but not vice versa.

    Conclusions: Although, sex does not appear to be an important predictor for survival, the difference between men and women regarding the proportion of resuscitation attempts should be further investigated. The majority of survivors and their spouses report good health-related quality of life similar to general populations. However, a substantial proportion suffer from health problems. Since women in general report worse health-related quality of life compared to men a higher proportion of women may be in need of support. Several factors associated with worse health-related quality of life were identified and might be used during follow-up and rehabilitation. For example, identifying type D personality might be important when screening patients at risk for health problems. Perceiving more control could be targeted by health-supportive interventions, for example person-centered care. Healthcare professionals should make efforts to identify survivors at risk of poor health-related quality of life and offer individualized support when needed. Characteristics among survivors were associated with health-related quality of life in their spouses. Including spouses in follow-up care is therefore important. Wilson and Cleary’s conceptual model for health-related quality of life appears to be applicable for choosing outcomes in cardiac arrest research and might be helpful when designing interventions to improve post cardiac arrest care.

    List of papers
    1. Is there a difference in survival between men and women suffering in-hospital cardiac arrest?
    Open this publication in new window or tab >>Is there a difference in survival between men and women suffering in-hospital cardiac arrest?
    2014 (English)In: Heart & Lung, ISSN 0147-9563, E-ISSN 1527-3288, Vol. 43, no 6, p. 510-515Article in journal (Refereed) Published
    Abstract [en]

    Objectives: To describe in-hospital cardiac arrest (CA) events with regard to sex and to investigate if sex is associated with survival. Background: Previous studies exploring differences between sexes are incongruent with regard to clinical outcomes. In order to provide equality and improve care, further investigations into these aspects are warranted. Methods: This registry study included 286 CAs. To investigate if sex was associated with survival, logistic regression analyses were performed. Results: The proportion of CA with a resuscitation attempt compared to CA without resuscitation was higher among men. There were no associations between sex and survival when controlling for previously known predictors and interaction effects. Conclusions: Sex does not appear to be a predictor for survival among patients suffering CA where resuscitation is attempted. The difference regarding proportion of resuscitation attempts requires more attention. It is important to consider possible interaction effects when studying the sex perspective.

    Place, publisher, year, edition, pages
    Elsevier, 2014
    Keywords
    Heart arrest; Hospital; Sex; Survival; Predictor
    National Category
    Clinical Medicine
    Identifiers
    urn:nbn:se:liu:diva-112817 (URN)10.1016/j.hrtlng.2014.05.012 (DOI)000344837600007 ()25005828 (PubMedID)
    Note

    Funding Agencies|county council of Kalmar

    Available from: 2015-01-08 Created: 2014-12-17 Last updated: 2020-02-17Bibliographically approved
    2. Health status and psychological distress among in-hospital cardiac arrest survivors in relation to gender
    Open this publication in new window or tab >>Health status and psychological distress among in-hospital cardiac arrest survivors in relation to gender
    Show others...
    2017 (English)In: Resuscitation, ISSN 0300-9572, E-ISSN 1873-1570, Vol. 114, p. 27-33Article in journal (Refereed) Published
    Abstract [en]

    Aim: To describe health status and psychological distress among in -hospital cardiac arrest (IHCA) survivors in relation to gender. Methods: This national register study consists of data from follow-up registration of IHCA survivors 3-6 months post cardiac arrest (CA) in Sweden. A questionnaire was sent to the survivors, including measurements of health status (EQ-5D-5L) and psychological distress (HADS). Results: Between 2013 and 2015, 594 IHCA survivors were included in the study. The median values for EQ-5D-5L index and EQVAS among survivors were 0.78 (ql-q3 = 0.67-0.86) and 70 (ql -q3 = 50-80) respectively. The values were significantly lower (p amp;lt; 0.001) in women compared to men. In addition, women reported more problems than men in all dimensions of EQ-5D-5L, except self -care. A majority of the respondents reported no problems with anxiety (85.4%) and/or symptoms of depression (87.0%). Women reported significantly more problems with anxiety (p amp;lt; 0.001) and symptoms of depression (p amp;lt; 0.001) compared to men. Gender was significantly associated with poorer health status and more psychological distress. No interaction effects for gender and age were found. Conclusions: Although the majority of survivors reported acceptable health status and no psychological distress, a substantial proportion reported severe problems. Women reported worse health status and more psychological distress compared to men. Therefore, a higher proportion of women may be in need of support. Health care professionals should make efforts to identify health problems among survivors and offer individualised support when needed. (C) 2017 Elsevier B.V. All rights reserved.

    Place, publisher, year, edition, pages
    ELSEVIER IRELAND LTD, 2017
    Keywords
    Anxiety; Depression; Health status; Heart arrest; Hospitals; Gender
    National Category
    Public Health, Global Health, Social Medicine and Epidemiology
    Identifiers
    urn:nbn:se:liu:diva-138921 (URN)10.1016/j.resuscitation.2017.02.006 (DOI)000402487800021 ()28216089 (PubMedID)
    Note

    Funding Agencies|Swedish Heart and Lung Association; Medical Research Council of Southeast Sweden

    Available from: 2017-06-27 Created: 2017-06-27 Last updated: 2020-02-17
    3. Factors associated with health-related quality of life among cardiac arrest survivors treated with an implantable cardioverter-defibrillator
    Open this publication in new window or tab >>Factors associated with health-related quality of life among cardiac arrest survivors treated with an implantable cardioverter-defibrillator
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    2018 (English)In: Resuscitation, ISSN 0300-9572, E-ISSN 1873-1570, Vol. 132, p. 78-84Article in journal (Refereed) Published
    Abstract [en]

    Aim: To explore factors associated with health-related quality of life (HRQoL) among cardiac arrest (CA) survivors treated with an implantable cardioverter-defibrillator (ICD) in relation to gender, and to compare their HRQoL with a general population. Methods: This cross-sectional study included 990 adults treated with an ICD after suffering CA. All participants received a questionnaire including demographics, comorbidities and instruments to measure HRQoL (EQ-5D-3L and HADS), ICD-related concerns (ICDC), perceived control (CAS), and type D personally (DS-14). HRQoL (EQ-5D-3L) was compared to a general Swedish population, matched for age and gender. Linear regression analyses were used to explore factors associated with HRQoL. Results: The CA survivors reported better HRQoL in EQ index and less pain/discomfort compared to the general population (p amp;lt; 0.001). In contrast, they reported more problems in mobility and usual activities (p amp;lt; 0.01). Problems with anxiety and depression were reported by 15.5% and 7.4% respectively. The following factors were independently associated with all aspects of worse HRQoL: being unemployed, suffering more comorbidity, perceiving less control, and having a type D personally. Further, being female and suffering ICD-related concerns were independently associated with worse HRQoL in three of the four final regression models. Conclusions: This extensive population-based study showed that most CA survivors living with an ICD rate their HRQoL as acceptable. In addition, their HRQoL is similar to a general population. Women reported worse HRQoL compared to men. Several factors associated with HRQoL were identified, and might be used when screening patients for health problems and when developing health promoting interventions.

    Place, publisher, year, edition, pages
    ELSEVIER IRELAND LTD, 2018
    Keywords
    Health-related quality of life; Health status; Psychological distress; Cardiac arrest; Implantable cardioverter-defibrillator; Gender
    National Category
    Public Health, Global Health, Social Medicine and Epidemiology
    Identifiers
    urn:nbn:se:liu:diva-152373 (URN)10.1016/j.resuscitation.2018.09.002 (DOI)000446854900019 ()30201535 (PubMedID)
    Note

    Funding Agencies|Medical Research Council of Southeast Sweden; Swedish Heart and Lung Association

    Available from: 2018-11-05 Created: 2018-11-05 Last updated: 2020-02-17
    4. Dyadic effects of type D personality and perceived control on health-related quality of life in cardiac arrest survivors and their spouses using the actor-partner interdependence model
    Open this publication in new window or tab >>Dyadic effects of type D personality and perceived control on health-related quality of life in cardiac arrest survivors and their spouses using the actor-partner interdependence model
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    2019 (English)In: European Journal of Cardiovascular Nursing, ISSN 1474-5151, E-ISSN 1873-1953, article id UNSP 1474515119890466Article in journal (Refereed) Epub ahead of print
    Abstract [en]

    Background: There is a lack of knowledge about factors associated with health-related quality of life in cardiac arrest survivors and their spouses. In addition, survivors and spouses are likely to affect each others health-related quality of life. Aims: The aim was to investigate if a distressed personality and perceived control among cardiac arrest survivors and their spouses were associated with their own and their partners health-related quality of life. Methods: This dyadic cross-sectional study used the actor-partner interdependence model to analyse associations between a distressed personality (type D personality), perceived control (control attitudes scale), and health-related quality of life (EQ index and EQ visual analogue scale). Results: In total, 126 dyads were included in the study. Type D personality and perceived control in cardiac arrest survivors were associated with their own health-related quality of life. In their spouses, a significant association was found for type D personality but not for perceived control. In addition, type D personality and perceived control in survivors were associated with health-related quality of life in their spouses. Conclusions: Type D personality and perceived control are factors that might be considered during post cardiac arrest, because of the associations with health-related quality of life in survivors and spouses. More research is needed to test psychosocial interventions in the cardiac arrest population in order to improve health-related quality of life.

    Place, publisher, year, edition, pages
    SAGE PUBLICATIONS LTD, 2019
    Keywords
    Heart arrest; survivor; partner; health; quality of life; dyads
    National Category
    Public Health, Global Health, Social Medicine and Epidemiology
    Identifiers
    urn:nbn:se:liu:diva-162500 (URN)10.1177/1474515119890466 (DOI)000498130000001 ()31752502 (PubMedID)
    Note

    Funding Agencies|Swedish Heart and Lung AssociationSwedish Heart-Lung Foundation; Medical Research Council of Southeast Sweden

    Available from: 2019-12-16 Created: 2019-12-16 Last updated: 2020-02-17
  • Public defence: 2020-03-20 10:15 Ada Lovelace, House B, Linköping
    Radnosrati, Kamiar
    Linköping University, Department of Electrical Engineering, Automatic Control. Linköping University, Faculty of Science & Engineering.
    Time of Flight Estimation for Radio Network Positioning2020Doctoral thesis, comprehensive summary (Other academic)
    Abstract [en]

    Trilateration is the mathematical theory of computing the intersection of circles. These circles may be obtained by time of flight (ToF) measurements in radio systems, as well as laser, radar and sonar systems. A first purpose of this thesis is to survey recent efforts in the area and their potential for localization. The rest of the thesis then concerns selected problems in new cellular radio standards as well as fundamental challenges caused by propagation delays in the ToF measurements, which cannot travel faster than the speed of light. We denote the measurement uncertainty stemming from propagation delays for positive noise, and develop a general theory with optimal estimators for selected distributions, which can be applied to trilateration but also a much wider class of estimation problems.

    The first contribution concerns a narrow-band mode in the long-term evolution (LTE) standard intended for internet of things (IoT) devices. This LTE standard includes a special position reference signal sent synchronized by all base stations (BS) to all IoT devices. Each device can then compute several pair-wise time differences that correspond to hyperbolic functions. The simulation-based performance evaluation indicates that decent position accuracy can be achieved despite the narrow bandwidth of the channel.

    The second contribution is a study of how timing measurements in LTE can be combined. Round trip time (RTT) to the serving BS and time difference of arrival (TDOA) to the neighboring BS are used as measurements. We propose a filtering framework to deal with the existing uncertainty in the solution and evaluate with both simulated and experimental test data. The results indicate that the position accuracy is better than 40 meters 95% of the time.

    The third contribution is a comprehensive theory of how to estimate the signal observed in positive noise, that is, random variables with positive support. It is well known from the literature that order statistics give one order of magnitude lower estimation variance compared to the best linear unbiased estimator (BLUE). We provide a systematic survey of some common distributions with positive support, and provide derivations and summaries of estimators based on order statistics, including the BLUE one for comparison. An iterative global navigation satellite system (GNSS) localization algorithm, based on the derived estimators, is introduced to jointly estimate the receiver’s position and clock bias.

    The fourth contribution is an extension of the third contribution to a particular approach to utilize positive noise in nonlinear models. That is, order statistics have been employed to derive estimators for a generic nonlinear model with positive noise. The proposed method further enables the estimation of the hyperparameters of the underlying noise distribution. The performance of the proposed estimator is then compared with the maximum likelihood estimator when the underlying noise follows either a uniform or exponential distribution.

    List of papers
    1. Performance of OTDOA Positioning in Narrowband IoT Systems
    Open this publication in new window or tab >>Performance of OTDOA Positioning in Narrowband IoT Systems
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    2017 (English)In: 28th Annual IEEE International Symposium on Personal, Indoor and Mobile Radio Communications (PIMRC): Proceedings, IEEE, 2017Conference paper, Published paper (Refereed)
    Abstract [en]

    Narrowband Internet of Things (NB-IoT) is an emerging cellular technology designed to target low-cost devices, high coverage, long device battery life (more than ten years), and massive capacity. We investigate opportunities for device tracking in NB-IoT systems using Observed Time Difference of Arrival (OTDOA) measurements. Reference Signal Time Difference (RSTD) reports are simulated to be sent to the mobile location center periodically or on an ondemand basis. We investigate the possibility of optimizing the number of reports per minute budget on horizontal positioning accuracy using an on-demand reporting method based on the Signal to Noise Ratio (SNR) of the measured cells received by the User Equipment (UE). Wireless channels are modeled considering multipath fading propagation conditions. Extended Pedestrian A (EPA) and Extended Typical Urban (ETU) delay profiles corresponding to low and high delay spread environments, respectively, are simulated for this purpose. To increase the robustness of the filtering method, measurement noise outliers are detected using confidence bounds estimated from filter innovations.

    Place, publisher, year, edition, pages
    IEEE, 2017
    National Category
    Communication Systems Control Engineering Signal Processing
    Identifiers
    urn:nbn:se:liu:diva-142819 (URN)10.1109/PIMRC.2017.8292365 (DOI)000426970901053 ()978-1-5386-3531-5 (ISBN)978-1-5386-3529-2 (ISBN)
    Conference
    28th Annual IEEE International Symposium on Personal, Indoor and Mobile Radio Communications (PIMRC), Montreal, QC, Canada, 08-13 October, 2017
    Projects
    Tracking in complex sensor systems, TRAX
    Available from: 2017-11-06 Created: 2017-11-06 Last updated: 2020-02-16
    2. Fusion of TOF and TDOA for 3GPP Positioning
    Open this publication in new window or tab >>Fusion of TOF and TDOA for 3GPP Positioning
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    2016 (English)In: Fusion 2016, 19th International Conference on Information Fusion: Proceedings, Institute of Electrical and Electronics Engineers (IEEE), 2016, p. 1454-1460Conference paper, Published paper (Refereed)
    Abstract [en]

    Positioning in cellular networks is often based on mobile-assisted measurements of serving and neighboring base stations. Traditionally, positioning is considered to be enabled when the mobile provides measurements of three different base stations. In this paper, we additionally investigate positioning based on time series of Time Of Flight (TOF) and Time Difference of Arrival (TDOA) measurements gathered from two base stations with known positions, where the specific base stations involved depend on the trajectory of the mobile station.. The set of two base stations is different along the trajectory. Each report contains TOF for the serving base station, and one TDOA measurement for the most favorable neighboring base station relative the serving base station. We derive explicit analytical solution related to the intersection of the absolute distance circle (from TOF) and relative distance hyperbola (from TDOA). We consider both geometric noise-free problem and the more realistic problem with additive noise as delivered in the 3rd Generation Partnership Project (3GPP) Long-Term Evolution (LTE). Positioning performance is evaluated using the Cramer-Rao lower bound.

    Place, publisher, year, edition, pages
    Institute of Electrical and Electronics Engineers (IEEE), 2016
    National Category
    Control Engineering
    Identifiers
    urn:nbn:se:liu:diva-130209 (URN)000391273400193 ()978-0-9964527-4-8 (ISBN)
    Conference
    19th International Conference on Information Fusion, Heidelberg, Germany, July 5-8, 2016
    Projects
    TRAX
    Funder
    EU, FP7, Seventh Framework Programme, 607400
    Available from: 2016-07-15 Created: 2016-07-15 Last updated: 2020-02-16Bibliographically approved
  • Public defence: 2020-03-27 12:35 TemCAS, T-building, Linköping
    Mutter, Amelia
    Linköping University, Department of Thematic Studies, Technology and Social Change. Linköping University, Faculty of Arts and Sciences.
    Multiple Imaginaries of the Fossil Fuel Free Future: Biogas and Electricity in Swedish Urban Transport2020Doctoral thesis, comprehensive summary (Other academic)
    Abstract [en]

    In the wake of the climate crisis, it has become increasingly evident that the fossil fuel-based transport system must undergo a global transformation. Numerous renewable fuel alternatives have been suggested, accompanied by imaginaries of how these technologies will contribute to a better future. These imaginaries have a wide-ranging impact because the implementation of each alternative technology will require the build-up of multifarious socio-technical ensembles that support their use. As a result, replacing fossil fuels with these renewable alternatives is likely to be a complex process. This dissertation considers the emergence of two such visions of renewable fuels studying imaginaries of biogas and electricity in the Swedish context. Biogas has a long history of use as a transport fuel in Sweden, where although it makes up a small percentage of total fuel use it also forms the basis of numerous municipal public transport systems. Meanwhile, electric vehicles have become increasingly attractive as more actors subscribe to an imaginary that sees the future of vehicles as shared, autonomous, and electric. This interaction is exemplified in urban public transportation as many municipalities begin to implement electric buses in an attempt to increase energy efficiency and reduce pollution. This thesis follows three case studies where the imaginaries of biogas and electric vehicles interact: urban public transport in the municipalities of Linköping and Malmö, and analysis of a comprehensive national policy document Fossil fuel freedom on the road. It contributes to a wider understanding of how visions can influence obduracy and change of transport alternatives within the wider transformation to a fossil fuel free future.  

    List of papers
    1. Mobilizing sociotechnical imaginaries of fossil-free futures - Electricity and biogas in public transport in Linkoping, Sweden
    Open this publication in new window or tab >>Mobilizing sociotechnical imaginaries of fossil-free futures - Electricity and biogas in public transport in Linkoping, Sweden
    2019 (English)In: Energy Research & Social Science, ISSN 2214-6296, E-ISSN 2214-6326, Vol. 49Article in journal (Refereed) Published
    Abstract [en]

    In response to concerns about climate change and fossil fuel reliance, Swedish national policy has set the ambitious goal of a fossil fuel independent transport fleet by 2030, opening up a widespread debate on renewable fuel choice. Across sectors and regions, this debate inspires competing visions for how this transition can be achieved. Using sociotechnical imaginaries for a theoretical background, this paper will examine two competing visions in the case of urban public transport in Linkoping, Sweden. While the biogas sociotechnical imaginary is based on the socio-material reality of the existing local infrastructure system, the electricity imaginary is gaining widespread support including from national and international interests. Using interviews with fourteen key actors and document analysis, this paper seeks to understand how local actors understand biogas and electric buses as competing technologies and how they mobilize these antagonistic imaginaries in their own visions of the future. Most often, actors mobilize both the biogas and the electric imaginary alongside each other, suggestion an attempt at reconciling them at the local level. This reconciliation sheds light on the challenge of applying national imaginaries to local cases and indicates that the complexity of multi-level systems must be considered in large scale sustainability transitions.

    Place, publisher, year, edition, pages
    ELSEVIER SCIENCE BV, 2019
    Keywords
    Sociotechnical imaginaries; Biogas; Electric vehicles; Local contexts
    National Category
    Social Sciences Interdisciplinary
    Identifiers
    urn:nbn:se:liu:diva-155537 (URN)10.1016/j.erss.2018.10.025 (DOI)000460444100001 ()
    Note

    Funding Agencies|Biogas Research Center; Linkoping University; Swedish Energy Agency

    Available from: 2019-03-27 Created: 2019-03-27 Last updated: 2020-02-03
    2. Obduracy and Change in Urban Transport: Understanding Competition Between Sustainable Fuels in Swedish Municipalities
    Open this publication in new window or tab >>Obduracy and Change in Urban Transport: Understanding Competition Between Sustainable Fuels in Swedish Municipalities
    2019 (English)In: Sustainability, ISSN 2071-1050, E-ISSN 2071-1050, SUSTAINABILITY, Vol. 11, no 21, article id 6092Article in journal (Refereed) Published
    Abstract [en]

    Within the renewable transport transition, a number of alternative technologies have emerged creating competing visions of how to reduce fossil fuel dependence. This paper examines the dynamics of competing fuels in two Swedish municipalities where electric buses have emerged, threatening incumbent biogas-based bus systems. While in Linkoping, actors are resistant to the promise of electrification, in Malmo the shift to electrify urban buses has already begun. Here, the theoretical perspectives of obduracy and sociotechnical imaginaries are used to analyze obduracy and change in Linkoping and Malmo, showing how the local contexts of these two municipalities influence obduracy or willingness to change. In Linkoping, perceived connections between the biogas-based bus system and local infrastructures of renewable waste management and organic food production cause actors to place biogas buses at the center of a sustainable future region, while in Malmo linkages to the gas network (which also distributes natural gas) cause actors to question the sustainability of the fuel in use and opens up the city to welcome new electric vehicle tests. These examples show how fuel alternatives interact with each other in the wider renewable energy transition.

    Place, publisher, year, edition, pages
    MDPI, 2019
    Keywords
    obduracy; sociotechnical imaginaries; urban public transport; electric vehicles; biogas
    National Category
    Energy Systems
    Identifiers
    urn:nbn:se:liu:diva-162889 (URN)10.3390/su11216092 (DOI)000501205200219 ()2-s2.0-85074853894 (Scopus ID)
    Note

    Funding Agencies|Swedish Energy Agency, Linkoping University

    Available from: 2020-01-02 Created: 2020-01-02 Last updated: 2020-02-03Bibliographically approved