64 research outputs found
2023 SOARS Conference Program
Program for the 2023 Showcase of Osprey Advancements in Research and Scholarship (SOARS
Multivariate assessment of linear and non-linear causal coupling pathways within the central-autonomic-network in patients suffering from schizophrenia
Im Bereich der Zeitreihenanalyse richtet sich das Interesse zunehmend darauf, wie Einblicke in die Interaktions- und Regulationsprozesse von pathophysiologischen- und physiologischen Zuständen erlangt werden können. Neuste Fortschritte in der nichtlinearen Dynamik, der Informationstheorie und der Netzwerktheorie liefern dabei fundiertes Wissen über Kopplungswege innerhalb (patho)physiologischer (Sub)Systeme. Kopplungsanalysen zielen darauf ab, ein besseres Verständnis dafür zu erlangen, wie die verschiedenen integrierten regulatorischen (Sub)Systeme mit ihren komplexen Strukturen und Regulationsmechanismen das globale Verhalten und die unterschiedlichen physiologischen Funktionen auf der Ebene des Organismus beschreiben. Insbesondere die Erfassung und Quantifizierung der Kopplungsstärke und -richtung sind wesentliche Aspekte für ein detaillierteres Verständnis physiologischer Regulationsprozesse. Ziel dieser Arbeit war die Charakterisierung kurzfristiger unmittelbarer zentral-autonomer Kopplungspfade (top-to-bottom und bottom to top) durch die Kopplungsanalysen der Herzfrequenz, des systolischen Blutdrucks, der Atmung und zentraler Aktivität (EEG) bei schizophrenen Patienten und Gesunden. Dafür wurden in dieser Arbeit neue multivariate kausale und nicht-kausale, lineare und nicht-lineare Kopplungsanalyseverfahren (HRJSD, mHRJSD, NSTPDC) entwickelt, die in der Lage sind, die Kopplungsstärke und -richtung, sowie deterministische regulatorische Kopplungsmuster innerhalb des zentralen-autonomen Netzwerks zu quantifizieren und zu klassifizieren. Diese Kopplungsanalyseverfahren haben ihre eigenen Besonderheiten, die sie einzigartig machen, auch im Vergleich zu etablierten Kopplungsverfahren. Sie erweitern das Spektrum neuartiger Kopplungsansätze für die Biosignalanalyse und tragen auf ihre Weise zur Gewinnung detaillierter Informationen und damit zu einer verbesserten Diagnostik/Therapie bei. Die Hauptergebnisse dieser Arbeit zeigen signifikant schwächere nichtlineare zentral-kardiovaskuläre und zentral-kardiorespiratorische Kopplungswege und einen signifikant stärkeren linearen zentralen Informationsfluss in Richtung des Herzkreislaufsystems auf, sowie einen signifikant stärkeren linearen respiratorischen Informationsfluss in Richtung des zentralen Nervensystems in der Schizophrenie im Vergleich zu Gesunden. Die detaillierten Erkenntnisse darüber, wie die verschiedenen zentral-autonomen Netzwerke mit paranoider Schizophrenie assoziiert sind, können zu einem besseren Verständnis darüber führen, wie zentrale Aktivierung und autonome Reaktionen und/oder Aktivierung in physiologischen Netzwerken unter pathophysiologischen Bedingungen zusammenhängen.In the field of time series analysis, increasing interest focuses on insights gained how the coupling pathways of regulatory mechanisms work in healthy and ill states. Recent advances in non-linear dynamics, information theory and network theory lead to a new sophisticated body of knowledge about coupling pathways within (patho)physiological (sub)systems. Coupling analyses aim to provide a better understanding of how the different integrated physiological (sub)systems, with their complex structures and regulatory mechanisms, describe the global behaviour and distinct physiological functions at the organism level. In particular, the detection and quantification of the coupling strength and direction are important aspects for a more detailed understanding of physiological regulatory processes. This thesis aimed to characterize short-term instantaneous central-autonomic-network coupling pathways (top-to-bottom and bottom to top) by analysing the coupling of heart rate, systolic blood pressure, respiration and central activity (EEG) in schizophrenic patients and healthy participants. Therefore, new multivariate causal and non-causal linear and non-linear coupling approaches (HRJSD, mHRJSD, NSTPDC) that are able to determine the coupling strength and direction were developed. Whereby, the HRJSD and mHRJSD approaches allow the quantification and classification of deterministic regulatory coupling patterns within and between the cardiovascular- the cardiorespiratory system and the central-autonomic-network were developed. These coupling approaches have their own unique features, even as compared to well-established coupling approaches. They expand the spectrum of novel coupling approaches for biosignal analysis and thus contribute in their own way to detailed information obtained, and thereby contribute to improved diagnostics/therapy. The main findings of this thesis revealed significantly weaker non-linear central-cardiovascular and central-cardiorespiratory coupling pathways, and significantly stronger linear central information flow in the direction of the cardiac- and vascular system, and a significantly stronger linear respiratory information transfer towards the central nervous system in schizophrenia in comparison to healthy participants. This thesis provides an enhanced understanding of the interrelationship of central and autonomic regulatory mechanisms in schizophrenia. The detailed findings on how variously-pronounced, central-autonomic-network pathways are associated with paranoid schizophrenia may enable a better understanding on how central activation and autonomic responses and/or activation are connected in physiology networks under pathophysiological conditions
The Impact of the COVID-19 Emergency on the Quality of Life of the General Population
COVID-19 is a pandemic that has forced many states to declare restrictive measures in order to prevent its wider spread. These measures are necessary to protect the health of adults, children, and people with disabilities.
Long quarantine periods could cause an increase in anxiety crises, fear of contagion, and post-traumatic stress disorder (frustration, boredom, isolation, fear, insomnia, difficulty concentrating).
Post-traumatic stress disorder (PTSD) is a condition that can develop in subjects who have been or have witnessed a traumatic, catastrophic, or violent event, or who have become aware of a traumatic experience that happened to a loved one.
In fact, from current cases, it emerges that the prevalence of PTSD varies from 1% to 9% in the general population and can reach 50%–60% in subgroups of subjects exposed to traumas considered particularly serious. PTSD develops as a consequence of one or more physical or psychological traumatic events, such as exposure to natural disasters such as earthquakes, fires, floods, hurricanes, tsunamis; wars, torture, death threats; road accidents, robbery, air accidents; diseases with unfavorable prognoses; complicated or traumatic mourning; physical and sexual abuse and abuse during childhood; victimization and discrimination based on gender, sexual orientation, gender identity. It can also develop following changes in lifestyle habits caused by the COVID-19 epidemic
Machine Learning for Biomedical Application
Biomedicine is a multidisciplinary branch of medical science that consists of many scientific disciplines, e.g., biology, biotechnology, bioinformatics, and genetics; moreover, it covers various medical specialties. In recent years, this field of science has developed rapidly. This means that a large amount of data has been generated, due to (among other reasons) the processing, analysis, and recognition of a wide range of biomedical signals and images obtained through increasingly advanced medical imaging devices. The analysis of these data requires the use of advanced IT methods, which include those related to the use of artificial intelligence, and in particular machine learning. It is a summary of the Special Issue “Machine Learning for Biomedical Application”, briefly outlining selected applications of machine learning in the processing, analysis, and recognition of biomedical data, mostly regarding biosignals and medical images
Quantifying Quality of Life
Describes technological methods and tools for objective and quantitative assessment of QoL Appraises technology-enabled methods for incorporating QoL measurements in medicine Highlights the success factors for adoption and scaling of technology-enabled methods This open access book presents the rise of technology-enabled methods and tools for objective, quantitative assessment of Quality of Life (QoL), while following the WHOQOL model. It is an in-depth resource describing and examining state-of-the-art, minimally obtrusive, ubiquitous technologies. Highlighting the required factors for adoption and scaling of technology-enabled methods and tools for QoL assessment, it also describes how these technologies can be leveraged for behavior change, disease prevention, health management and long-term QoL enhancement in populations at large. Quantifying Quality of Life: Incorporating Daily Life into Medicine fills a gap in the field of QoL by providing assessment methods, techniques and tools. These assessments differ from the current methods that are now mostly infrequent, subjective, qualitative, memory-based, context-poor and sparse. Therefore, it is an ideal resource for physicians, physicians in training, software and hardware developers, computer scientists, data scientists, behavioural scientists, entrepreneurs, healthcare leaders and administrators who are seeking an up-to-date resource on this subject
The Impact of the COVID-19 Emergency on the Quality of Life of the General Population
COVID-19 is a pandemic that has forced many states to declare restrictive measures in order to prevent its wider spread. These measures are necessary to protect the health of adults, children, and people with disabilities.Long quarantine periods could cause an increase in anxiety crises, fear of contagion, and post-traumatic stress disorder (frustration, boredom, isolation, fear, insomnia, and difficulty concentrating).Post-traumatic stress disorder (PTSD) is a condition that can develop in subjects who have witnessed a traumatic, catastrophic, or violent event, or who have become aware of a traumatic experience that happened to a loved one.In fact, from current cases, it emerges that the prevalence of PTSD varies from 1% to 9% in the general population and can reach 50%–60% in subgroups of subjects exposed to traumas considered particularly serious. PTSD develops as a consequence of one or more physical or psychological traumatic events, such as exposure to natural disasters such as earthquakes, fires, floods, hurricanes, tsunamis; wars, torture, death threats; road accidents, robbery, air accidents; diseases with unfavorable prognoses; complicated or traumatic mourning; physical and sexual abuse and abuse during childhood; or victimization and discrimination based on gender, sexual orientation, or gender identity. It can also develop following changes in lifestyle habits caused by the COVID-19 epidemic.Thank you for reading the manuscripts in this Special Issue, "The Impact of the COVID-19 Emergency on the Quality of Life of the General Population"
Proceedings of the 11th International Conference on Kinanthropology
The 11th International Conference on Kinantropology was held on the Nov 29 – Dec 1, 2017 in Brno and was organized by the Faculty of Sports Studies, Masaryk University and the Faculty of Kinesiology, University of Zagreb. This year was divided into several themes: sports medicine, sport and social science, sport training, healthy lifestyle and healthy ageing, sports management, analysis of human movement. Part of the conference was also a symposium Atletika and Ortoreha that gathered specialists in physiotherapy
Diagnostic Challenges in Sports Cardiology
The foundations of sports cardiology include promoting physical activity and providing a safe environment for training and competition for all athletes at all levels, from professional to recreational. To combine these two aims, reliable tools to perform preparticipation screenings are needed. Moreover, those at high risk of potentially life-threatening events should be advised to limit their training load, while others should be reassured that there is no exercise-related cardiovascular risk. We are currently witnessing the advent of new portable devices for remote and mobile heart monitoring and several new and promising biochemical markers, which can support athletes’ diagnostic processes. In this Special Issue of the Diagnostics journal entitled “Diagnostic Challenges in Sports Cardiology”, we present a series of 13 manuscripts, including eight original works, three reviews, and two case reports, which give a glimpse into the current research topics in the area of sports cardiology
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