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The Utility of Voided Urine Samples as a Proxy for the Vaginal Microbiome and for the Prediction of Bacterial Vaginosis

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Infectious Microbes & Diseases 2022年第4期4卷 149-156页

作者： Bin Zhu Christopher Diachok Laahirie Edupuganti David J.Edwards Jeffrey R.Donowitz Katherine Tossas Andrey Matveyev Katherine M.Spaine Vladimir Lee Myrna G.Serrano Gregory A.Buck Department of Microbiology and Immunology School of MedicineVirginia Commonwealth UniversityRichmondVirginiaUSA Center for Microbiome Engineering and Data Analysis Virginia Commonwealth UniversityRichmondVirginiaUSA Department of Statistical Sciences and Operations Research College of Humanities and SciencesVirginia Commonwealth UniversityRichmondVirginiaUSA Department of Pediatric Infectious Diseases Children's Hospital of Richmond at Virginia Commonwealth UniversityRichmondVirginiaUSA Department of Infectious Diseases and International Health University of VirginiaCharlottesvilleVirginiaUSA Department of Health Behavior and Policy School of MedicineVirginia Commonwealth UniversityRichmondVirginiaUSA Department of Family Medicine and Population Health School of MedicineVirginia Commonwealth UniversityRichmondVirginiaUSA Computer Science Department College of EngineeringVirginia Commonwealth UniversityRichmondVirginiaUSA Genomics Core Virginia Commonwealth UniversityRichmondVirginiaUSA

Recent work has shown that the vaginal microbiome exerts a strong impact on women's gynecological ***,collection of vaginal specimens is invasive and requires previous clinical training or the involvement of a trained *** contrast,urine sample collection is routine and noninvasive and does not require involvement of a *** sought to compare the vaginal and urogenital microbiomes to assess the utility of voided urine samples as a proxy for the vaginal *** urogenital and vaginal samples were collected from pregnant women and characterized by 16S rRNA taxonomic *** examined diversities and compositions of paired urogenital and vaginal microbiomes using five discrete strategies to explore the similarity between the vaginal and urogenital microbiomes.A strategy comparing the paired urogenital and vaginal microbiomes in which taxa were assigned using the STIRRUPS database and urine-specific taxa were removed showed no significant difference in diversity and composition between the paired urogenital and vaginal ***,the relative abundances of common vaginal taxa were linearly correlated with those in the paired *** similarities suggest that voided urine samples could represent a noninvasive protocol for accurate profiling of the vaginalmicrobiome with likely clinical ***,a machine learning model was established in which the voided urine microbiome was compared favorably to the vaginal microbiome in predicting bacterial vaginosis.

关键词： 16S rRNA vaginal microbiome urine microbiome bacterial vaginosis reproductive and gynecologic health

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How to design the biofeedback training for the rehabilitation of PTSD patients?

How to design the biofeedback training for the rehabilitatio...

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Cognitive sciences, Genomics and Bioinformatics (CSGB)

作者： Olga Bazanova Alexander Zakharov Irina Larkova Tatiana Maryanovskaya Andrey Melnikov Sargylana Ermolaeva Ekaterina Nikolenko Igor Shirolapov Laboratory of Computer systems of Biofeedback The Research Institute of Molecular Biology and Biophysics Dolgoprudny Russia Educational and Scientific Center for Humanities and Social Science The Moscow Institute of Physics and Technology Novosibirsk Russia Research Institute of Neurosciences Samara State Medical University Samara Russia Laboratory of psychophysiological support Lugansk Republican Center for Emergency Medical Care and Disaster Medicine Lugansk Russia Mechanic-Mathematic Department Novosibirsk National Research State University Novosibirsk Russia Department of Physiology The Russian University of Sport «GTSOLIFK» Moscow Russia Master's Degree in Applied Data Analysis in the Medical Field The Moscow Institute of Physics and Technology Dolgoprudny Russia Department of Clinical Neuroscience Behavior and Neurotechnology Federal State Budgetary Scientific Institution “Scientific Research Institute of Neurosciences and Medicine” Novosibirsk Russia

Rationale for this review is the pressing medical and social problem of the posttraumatic stress disorder (PTSD) treatment. It is known that biofeedback technology is one of the most effective methods of treatment and rehabilitation for emotional profile disorders. In order to develop biofeedback aimed to PTSD rehabilitation, we conducted a literature search on this problem. However, it appears that at the moment there is not enough unambiguous data on this type of biofeedback design. The pathogenesis of PTSD is closely related to impaired efficiency of sensorimotor integration (SMI). The effectiveness of therapy for psychosomatic disorders in patients with PTSD can be increased by restoring normal sensorimotor integration. The review examines various autonomic, electrophysiological and postural markers of destroyed sensorimotor integration (SMI) in individuals with PTSD. We have found that the most informative indicators of SMI in norm include: an increase in EEG power in the individually determined high-frequency alpha subrange, a decrease in the speed of body sway and energy demands to maintain a vertical posture, and a decrease in EMG activity of muscles not involved in cognitive or psychomotor performance. We intend to use these indicators in diagnostic purposes and to develop neurofeedback technology for SMI recovery in patients with PTSD.

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A theoretical framework for polarization as the gradual fragmentation of a divided society

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Communications psychology 2024年第1期2卷 75页

作者： Ana-Maria Bliuc John M Betts Matteo Vergani Ayoub Bouguettaya Mioara Cristea Division of Psychology University of Dundee Dundee UK. abliuc001@dundee.ac.uk. Department of Data Science & AI Monash University Melbourne VIC Australia. School of Humanities & Social Science Deakin University Melbourne VIC Australia. Cedars-Sinai Medical Center Los Angeles US. Department of Psychology Heriot-Watt University Edinburgh UK.

We propose a framework integrating insights from computational social science, political, and social psychology to explain how extreme polarization can occur in deeply divided societies. Extreme polarization in a society emerges through a dynamic and complex process where societal, group, and individual factors interact. Dissent at different levels of analysis represents the driver of this process, where societal-level ideological dissent divides society into opposing camps, each with contrasting collective narratives. Within these opposing camps, further dissent leads to the formation of splinter factions and radical cells-sub-groups with increasingly extreme views. At the group level, collective narratives underpinning group identity become more extreme as society fragments. At the individual level, this process involves the internalization of an extreme group narrative and norms sanctioning radical behavior. The intense bonding within these groups and the convergence of personal and group identities through identity fusion increase the likelihood of radical group behavior.

关键词： Human behaviour Complex networks

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Citizen science’s transformative impact on science, citizen empowerment and socio-political processes

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Socio-Ecological Practice Research 2023年第1期5卷 11-33页

作者： von Gönner, Julia Herrmann, Thora M. Bruckermann, Till Eichinger, Michael Hecker, Susanne Klan, Friederike Lorke, Julia Richter, Anett Sturm, Ulrike Voigt-Heucke, Silke Brink, Wiebke Liedtke, Christin Premke-Kraus, Matthias Altmann, Carolin Bauhus, Wilhelm Bengtsson, Luiza Büermann, Andrea Dietrich, Peter Dörler, Daniel Eich-Brod, Regina Ferschinger, Laura Freyberg, Linda Grützner, Agnes Hammel, Gertrud Heigl, Florian Heyen, Nils B. Hölker, Franz Johannsen, Carolin Kluß, Thorsten Kluttig, Thekla Knobloch, Jörn Munke, Martin Mortega, Kim Pathe, Carsten Soßdorf, Anna Stämpfli, Tiina Thiel, Christian Tönsmann, Susanne Valentin, Anke Wagenknecht, Katherin Wegener, Robert Woll, Silvia Bonn, Aletta Department of Ecosystem Services Helmholtz Centre for Environmental Research - UFZ Permoserstr. 15 Leipzig 04318 Germany Institute of Biodiversity Friedrich Schiller University Jena Dornburgerstr. 159 Jena 07743 Germany German Centre for Integrative Biodiversity Research (iDiv) Halle-Jena-Leipzig Puschstr. 4 Leipzig 04103 Germany Institute of Education Leibniz University Hannover Schloßwenderstr. 1 Hannover 30159 Germany Center for Preventive Medicine and Digital Health Medical Faculty Mannheim Heidelberg University Ludolf-Krehl-Str. 7-11 Mannheim 68167 Germany Institute of Medical Biostatistics Epidemiology and Informatics University Medical Center of the Johannes Gutenberg University Mainz Obere Zahlbacher Str. 69 Mainz 55131 Germany Leibniz Institute for Evolution and Biodiversity Science Museum Für Naturkunde Berlin Invalidenstr. 43 Berlin 10115 Germany Institute of Data Science German Aerospace Center (DLR) Mälzerstr. 3-5 Jena 07745 Germany Leibniz Institute for Science and Mathematics Education Olshausenstr. 62 Kiel 24118 Germany Thünen-Institute of Biodiversity Bundesallee 65 Brunswick 38116 Germany Wissenschaft Im Dialog Charlottenstr. 80 Berlin 10117 Germany Helmholtz Association Berlin Head Office Anna-Louisa-Karsch-Str. 2 Berlin 10178 Germany Leibniz Association Berlin Head Office Chausseestr.111 Berlin 10115 Germany Research Transfer Office University of Münster Robert-Koch-Str.40 Münster 48149 Germany Max-Delbrück-Center for Molecular Medicine in the Helmholtz Association Robert-Rössle-Str.10 Berlin 13125 Germany Department of Monitoring and Exploration Technologies Helmholtz Centre for Environmental Research - UFZ Permoserstr. 15 Leipzig 04318 Germany Institute of Zoology University of Natural Resources and Life Sciences Vienna Gregor-Mendel-Str. 33 Vienna 1180 Austria Institute for Energy and Climate Research IEK8 Forschungszentrum Jülich GmbH Jülich 52425 Germany Heinrich Heine University Duesseldorf Universitä

Citizen science (CS) can foster transformative impact for science, citizen empowerment and socio-political processes. To unleash this impact, a clearer understanding of its current status and challenges for its development is needed. Using quantitative indicators developed in a collaborative stakeholder process, our study provides a comprehensive overview of the current status of CS in Germany, Austria and Switzerland. Our online survey with 340 responses focused on CS impact through (1) scientific practices, (2) participant learning and empowerment, and (3) socio-political processes. With regard to scientific impact, we found that data quality control is an established component of CS practice, while publication of CS data and results has not yet been achieved by all project coordinators (55%). Key benefits for citizen scientists were the experience of collective impact (“making a difference together with others”) as well as gaining new knowledge. For the citizen scientists’ learning outcomes, different forms of social learning, such as systematic feedback or personal mentoring, were essential. While the majority of respondents attributed an important value to CS for decision-making, only few were confident that CS data were indeed utilized as evidence by decision-makers. Based on these results, we recommend (1) that project coordinators and researchers strengthen scientific impact by fostering data management and publications, (2) that project coordinators and citizen scientists enhance participant impact by promoting social learning opportunities and (3) that project initiators and CS networks foster socio-political impact through early engagement with decision-makers and alignment with ongoing policy processes. In this way, CS can evolve its transformative impact. © 2023, The Author(s).

关键词： data quality Participatory research Political uptake Recognition Research data management Social learning

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Automated speech- and text-based classification of neuropsychiatric conditions in a multidiagnostic setting

arXiv

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arXiv 2023年

作者： Hansen, Lasse Rocca, Roberta Simonsen, Arndis Parola, Alberto Bliksted, Vibeke Ladegaard, Nicolai Bang, Dan Tylén, Kristian Weed, Ethan Østergaard, Søren Dinesen Fusaroli, Riccardo Department of Affective Disorders Aarhus University Hospital - Psychiatry Aarhus Denmark Department of Clinical Medicine Aarhus University Aarhus Denmark Center for Humanities Computing Aarhus University Aarhus Denmark Interacting Minds Centre Aarhus University Aarhus Denmark Psychosis Research Unit Aarhus University Hospital - Psychiatry Aarhus Denmark Department of Linguistics Cognitive Science and Semiotics Aarhus University Aarhus Denmark Wellcome Centre for Human Neuroimaging University College London LondonWC1N 3BG United Kingdom Department of Experimental Psychology University of Oxford OxfordOX2 6GG United Kingdom Center of Functionally Integrative Neuroscience Aarhus University Aarhus Denmark Linguistic Data Consortium University of Pennsylvania PhiladelphiaPA United States

Speech patterns have been identified as potential diagnostic markers for neuropsychiatric conditions. However, most studies only compare a single clinical group to healthy controls, whereas clinical practice often requires differentiating between multiple potential diagnoses (multiclass setting). To address this, we assembled a dataset of repeated recordings from 420 participants (67 with major depressive disorder (MDD), 106 with schizophrenia and 46 with autism spectrum disorder (ASD), as well as matched controls), and tested the performance of conventional machine learning models and advanced Transformer models on both binary and multiclass classification, based on voice and text features. While binary models performed comparably to previous research (F1 scores between 0.54-0.75 for ASD;0.67-0.92 for MDD;and 0.71-0.83 for schizophrenia);when differentiating between multiple diagnostic groups performance decreased markedly (F1 scores between 0.35-0.44 for ASD, 0.57-0.75 for MDD, 0.15-0.66 for schizophrenia, and 0.38-0.52 macro F1). Combining voice and text-based models increased performance, suggesting that they capture complementary diagnostic information. Our results indicate that models trained on binary classification might rely on markers of generic differences between clinical and non-clinical populations, or markers of clinical features that overlap across conditions, rather than identifying markers specific to individual conditions. We provide recommendations for future research in the field, suggesting increased focus on developing larger transdiagnostic datasets that include more fine-grained clinical features, and that can support the development of models that better capture the complexity of neuropsychiatric conditions and naturalistic diagnostic assessment. © 2023, CC BY-SA.

关键词： Classification (of information)

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Why Autonomous Vehicles Are Not Ready Yet: A Multi-Disciplinary Review of Problems, Attempted Solutions, and Future Directions

arXiv

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arXiv 2023年

作者： Dong, Xingshuai Cappuccio, Max Jassmi, Hamad Al Alnajjar, Fady Debie, Essam Ghasrikhouzani, Milad Lanteri, Alessandro Luqman, Ali McGregor, Tate Molloy, Oleksandra Plebe, Alice Regan, Michael Zhang, Dongmo School of Information and Communication Technology Griffith University Australia School of Engineering and Technology University of New South Wales Canberra Australia Emirates Centre for Mobility Research Center United Arab Emirates University United Arab Emirates College of Information Technology United Arab Emirates University United Arab Emirates University of Canberra Australia ESCP Business School France School of Humanities and Social Sciences University of New South Wales Sydney Australia School of Science University of New South Wales Canberra Australia University College London United Kingdom School of Civil and Environmental Engineering University of New South Wales Sydney Australia School of Computer Data and Mathematical Sciences Western Sydney University Australia

Personal autonomous vehicles are cars, trucks and bikes capable of sensing their surrounding environment, planning their route, and driving with little or no involvement of human drivers. Despite the impressive technological achievements made by the industry in recent times and the hopeful announcements made by leading entrepreneurs, to date no personal vehicle is approved for road circulation in a ‘fully’ or ‘semi’ autonomous mode (autonomy levels 4 and 5) and it is still unclear when such vehicles will eventually be mature enough to receive this kind of approval. The present review adopts an integrative and multidisciplinary approach to investigate the major challenges faced by the automative sector, with the aim to identify the problems that still trouble and delay the commercialization of autonomous vehicles. The review examines the limitations and risks associated with current technologies and the most promising solutions devised by the researchers. This negative assessment methodology is not motivated by pessimism, but by the aspiration to raise critical awareness about the technology’s state-of-the-art, the industry’s quality standards, and the society’s demands and expectations. While the survey primarily focuses on the applications of artificial intelligence for perception and navigation, it also aims to offer an enlarged picture that links the purely technological aspects with the relevant human-centric aspects, including, cultural attitudes, conceptual assumptions, and normative (ethico-legal) frameworks. Examining the broader context serves to highlight problems that have a cross-disciplinary scope and identify solutions that may benefit from a holistic consideration. Copyright © 2023, The Authors. All rights reserved.

关键词： Advanced driver assistance systems

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FOOTPRINT OF PUBLICATION SELECTION BIAS ON META-ANALYSES IN MEDICINE, ENVIRONMENTAL scienceS, PSYCHOLOGY, AND ECONOMICS

arXiv

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arXiv 2022年

作者： Bartoš, František Maier, Maximilian Wagenmakers, Eric-Jan Nippold, Franziska Doucouliagos, Hristos Ioannidis, John P.A. Otte, Willem M. Sladekova, Martina Deresssa, Teshome K. Bruns, Stephan B. Fanelli, Daniele Stanley, T.D. Department of Psychological Methods University of Amsterdam Netherlands Institute of Computer Science Czech Academy of Sciences Czech Republic Department of Experimental Psychology University College London United Kingdom Department of Economics Deakin University Australia United States Department of Epidemiology and Population Health Stanford University School of Medicine United States Stanford Prevention Research Center Department of Medicine Stanford University School of Medicine United States Department of Biomedical Data Science Stanford University School of Medicine United States Department of Statistics Stanford University School of Humanities and Sciences United States Department of Pediatric Neurology UMC Utrecht Brain Center University Medical Center Utrecht Utrecht University Netherlands School of Psychology University of Sussex United Kingdom Centre for Environmental Sciences Hasselt University Belgium Department of Economics University of Göttingen Germany Department of Methodology London School of Economics and Political Science United Kingdom School of Social Sciences Heriot-Watt University United Kingdom

Publication selection bias undermines the systematic accumulation of evidence. To assess the extent of this problem, we survey over 68,000 meta-analyses containing over 700,000 effect size estimates from medicine (67,386/597,699), environmental sciences (199/12,707), psychology (605/23,563), and economics (327/91,421). Our results indicate that meta-analyses in economics are the most severely contaminated by publication selection bias, closely followed by meta-analyses in environmental sciences and psychology, whereas meta-analyses in medicine are contaminated the least. After adjusting for publication selection bias, the median probability of the presence of an effect decreased from 99.9% to 29.7% in economics, from 98.9% to 55.7% in psychology, from 99.8% to 70.7% in environmental sciences, and from 38.0% to 29.7% in medicine. The median absolute effect sizes (in terms of standardized mean differences) decreased from d = 0.20 to d = 0.07 in economics, from d = 0.37 to d = 0.26 in psychology, from d = 0.62 to d = 0.43 in environmental sciences, and from d = 0.24 to d = 0.13 in medicine. © 2022, CC BY.

关键词： Economic analysis

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Environment Scan of Generative AI Infrastructure for Clinical and Translational science

arXiv

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arXiv 2024年

作者： Idnay, Betina Xu, Zihan Adams, William G. Adibuzzaman, Mohammad Anderson, Nicholas R. Bahroos, Neil Bell, Douglas S. Bumgardner, Cody Campion, Thomas Castro, Mario Cimino, James J. Cohen, I. Glenn Dorr, David Elkin, Peter L. Fan, Jungwei W. Ferris, Todd Foran, David J. Hanauer, David Hogarth, Mike Huang, Kun Kalpathy-Cramer, Jayashree Kandpal, Manoj Karnik, Niranjan S. Katoch, Avnish Lai, Albert M. Lambert, Christophe G. Li, Lang Lindsell, Christopher Liu, Jinze Lu, Zhiyong Luo, Yuan McGarvey, Peter Mendonca, Eneida A. Mirhaji, Parsa Murphy, Shawn Osborne, John D. Paschalidis, Ioannis C. Harris, Paul A. Prior, Fred Shaheen, Nicholas J. Shara, Nawar Sim, Ida Tachinardi, Umberto Waitman, Lemuel R. Wright, Rosalind J. Zai, Adrian H. Zheng, Kai Lee, Sandra Soo-Jin Malin, Bradley A. Natarajan, Karthik Price, W. Nicholson Zhang, Rui Zhang, Yiye Xu, Hua Bian, Jiang Weng, Chunhua Peng, Yifan Department of Biomedical Informatics Columbia University Irving Medical Center New YorkNY United States Department of Population Health Sciences Weill Cornell Medicine New YorkNY United States Department of Pediatrics Boston Medical Center BostonMA United States Chobanian & Avedisian School of Medicine Boston University BostonMA United States Oregon Clinical and Translational Research Institute Oregon Health and Science University PortlandOR United States Department of Public Health Sciences University of California Davis DavisCA United States Keck School of Medicine University of Southern California Los AngelesCA United States Department of Medicine David Geffen School of Medicine University of California Los Angeles Los AngelesCA United States Department of Pathology and Laboratory Medicine University of Kentucky College of Medicine LexingtonKY United States Division of Pulmonary Critical Care and Sleep Medicine University of Kansas School of Medicine Kansas CityKS United States Department of Biomedical Informatics and Data Science Heersink School of Medicine University of Alabama BirminghamAL United States Harvard Law School Petrie-Flom Center for Health Law Policy Biotechnology and Bioethics Harvard University CambridgeMA United States Department of Biomedical Informatics University at Buffalo BuffaloNY United States Center for Clinical and Translational Science Mayo Clinic RochesterMN United States Technology and Digital Solutions Stanford Medicine Stanford University StanfordCA United States Center for Biomedical Informatics Rutgers Cancer Institute New BrunswickNJ United States Department of Learning Health Sciences University of Michigan Medical School Ann ArborMI United States University of California San Diego La Jolla CA United States Department of Biostatistics and Health Data Science School of Medicine Indiana University IndianapolisIN United States Division of Artificial Medical Intelligence in Ophthalmology Univ

This study reports a comprehensive environmental scan of the generative AI (GenAI) infrastructure in the national network for clinical and translational science across 36 institutions supported by the Clinical and Translational science Award (CTSA) Program led by the National center for Advancing Translational sciences (NCATS) of the National Institutes of Health (NIH) at the United States. With the rapid advancement of GenAI technologies, including large language models (LLMs), healthcare institutions face unprecedented opportunities and challenges. This research explores the current status of GenAI integration, focusing on stakeholder roles, governance structures, and ethical considerations by administering a survey among leaders of health institutions (i.e., representing academic medical centers and health systems) to assess the institutional readiness and approach towards GenAI adoption. Key findings indicate a diverse range of institutional strategies, with most organizations in the experimental phase of GenAI deployment. The study highlights significant variations in governance models, with a strong preference for centralized decision-making but notable gaps in workforce training and ethical oversight. Moreover, the results underscore the need for a more coordinated approach to GenAI governance, emphasizing collaboration among senior leaders, clinicians, information technology staff, and researchers. Our analysis also reveals concerns regarding GenAI bias, data security, and stakeholder trust, which must be addressed to ensure the ethical and effective implementation of GenAI technologies. This study offers valuable insights into the challenges and opportunities of GenAI integration in healthcare, providing a roadmap for institutions aiming to leverage GenAI for improved quality of care and operational efficiency. © 2024, CC BY.

关键词： Electronic health record

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Tracking the consumption junction: Temporal dependencies between articles and advertisements in dutch newspapers

arXiv

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arXiv 2019年

作者： Wevers, Melvin Gao, Jianbo Nielbo, Kristoffer L. Digital Humanities Lab KNAW Humanities Cluster Netherlands Institute of Complexity Science and Big Data Technology Guangxi University China Center for Humanities Computing Aarhus Aarhus University Denmark

Historians have regularly debated whether advertisements can be used as a viable source to study the past. Their main concern centered on the question of agency. Were advertisements a reflection of historical events and societal debates, or were ad makers instrumental in shaping society and the ways people interacted with consumer goods? Using techniques from econometrics (Granger causality test) and complexity science (Adaptive Fractal Analysis), this paper analyzes to what extent advertisements shaped or reflected society. We found evidence that indicate a fundamental difference between the dynamic behavior of word use in articles and advertisements published in a century of Dutch newspapers. Articles exhibit persistent trends that are likely to be reflective of communicative memory. Contrary to this, advertisements have a more irregular behavior characterized by short bursts and fast decay, which, in part, mirrors the dynamic through which advertisers introduced terms into public discourse. On the issue of whether advertisements shaped or reflected society, we found particular product types that seemed to be collectively driven by a causality going from advertisements to articles. Generally, we found support for a complex interaction pattern dubbed the consumption junction. Finally, we discovered noteworthy patterns in terms of causality and long-range dependencies for specific product groups. All in, this study shows how methods from econometrics and complexity science can be applied to humanities data to improve our understanding of complex cultural-historical phenomena such as the role of advertising in society. Copyright © 2019, The Authors. All rights reserved.

关键词： Statistical tests

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Neural Networks Classification for Training of Five German Longsword Mastercuts - A Novel Application of Motion Capture: Analysis of Performance of Sword Fencing in the Historical European Martial Arts (HEMA) Domain

Neural Networks Classification for Training of Five German L...

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International Symposium on Computational Intelligence and Informatics

作者： Ryszard Klempous Konrad Kluwak Ito Atsushi Tomasz Górski Jan Nikodem Wojciech Bożejko Zenon Chaczko Grzegorz Borowik Jerzy Rozenblit Marek Kulbacki Wroclaw University of Science and Technology Wroclaw Poland Faculty of Economics Chuo University Tokyo Japan Polish Naval Academy Gdynia Poland School of Electrical and Data Engineering University of Technology Sydney Sydney Australia SWPS University of Social Sciences and Humanities Warsaw Poland University of Arizona Tucson USA R&D Center Polish-Japanese Academy of Information Technology Warsaw Poland DIVE IN AI Wroclaw Poland

ISBN: (纸本)9781665426855

This paper discusses an application of motion capture in longsword fencing, a discipline experiencing rising popularity since the 1990s. Historical European Martial Arts alliance focuses on re-enacting the Late Middle Ages and Renaissance fighting styles. To popularize this art, novel research to automatically distinguish selected sword cutting techniques has been conducted. The fencing knowledge required for conducting this research was based on publications and consultation with experts in the field, and recordings. For this research, different movements from Masterstrikes such as Zornhau (Strike of Wrath), Schielhau (Squinting Strike), Zwerchhau (Cross Strike), Krumphau (Crooked Strike), Scheitelhau (Crown Strike) were selected. Motions performed by an adept fencer (acting expert) were used as patterns of correct strikes and compared with the movements of fencing amateurs. The main goal of this research was to measure the precision of movement while performing five different fencing strokes. Each movement was recorded with 39 unique full-body plug-in gait configurations initially designed for medical applications. During the exercise, 16 EMG electrodes configuration was used for the measurement of muscle activity.

关键词： Training Electrodes Art Neural networks Europe Medical services Forestry

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