The symposium supports students who seek to learn and gain skills and knowledge in the area of biomechanics of sport and ageing with a special reference to artificial intelligence. Therefore, the Hungarian University of Sports Science through the Department of Kinesiology offers students the opportunity to receive two continuing education credits for participating in the 2nd Scientific Symposium of Biomechanics in Sport and Ageing: Artificial Intelligence.
By registering for the course linked to the symposium HERE, students can earn continuing education credits through the NEPTUN educational system. To obtain the two credits, students must attend the symposium in person or online on 15-16 October 2024 and take notes during each presentation. After the symposium, students must submit these notes to a designated member of the organizing committee by 17.00, 23 October 2024. Late submissions will not be considered. It will be at the designated teacher's discretion to award the maximum of two credits or just partial credit of one credit or zero credit for incomplete submissions.
Alan Godfrey
Dr Godfrey major research is in algorithms for data science and analytics in healthcare. This includes areas of artificial intelligence, machine learning, data mining and multidimensional signal processing. He has published over 100 papers on those topics in various engineering and medical journals from a portfolio of translational-based research. He serves as Deputy Editor for npj/Nature Digital Medicine, Editor for Maturitas and Associate Editor for Journal of NeuroEngineering & Rehabilitation. He is an International Advisory board member for Physiological Measurement. Dr Godfrey is a Member of the Institution Engineering Technology (MIET) and Senior Member of the Institution of Electrical and Electronic Engineering (SMIEEE).
András Horváth
Dr. Horvath holds a Medical Doctor degree and a PhD in Clinical Neurosciences. Currently her serves as the Head and Director of Research Studies at the Nyírő Gyula National Institute of Psychiatry and Addicology in Hungary, where he leads the Neurocognitive Research Centre.
He specializes in the neurophysiology and neuroimaging of cognitive decline, as well as fine movement analysis in neurological disorders.
Outside of their primary lab activities, Dr. Horvath serves as the leader of several key initiatives, including the Euro-Fingers Consortium, Hungarian Chapter, the Hungarian Dementia Prevention Platform, and the “Momentum” Neurocognitive Research Group of the Hungarian Academy of Sciences. Dr.Horvath has a rich history of research engagement, having been a visiting scientist at the University of Zurich and ETH Zurich (Translational Neuromodeling Unit) in 2013, at Université Libre de Bruxelles (Department of Psychiatry) in 2014, and a visiting postdoc fellow at New York University (Langone Medical Research Center Buzsaki Lab) in 2018. In 2022, he was recognized as a visiting professor at the University of Lisbon (Instituto de Medicina Molecular). He has received prestigious recognition for their scientific contributions, including the Junior Prima Award in Hungarian Sciences, the Merit Research Excellence Award from Semmelweis University, and the Grey Walter Investigator Award in 2022.
An accomplished researcher, he has authored over 50 peer-reviewed publications, with a cumulative impact factor of >140 and independent citations exceeding 800, reflecting a significant contribution to the field of clinical neurosciences.
Attila Biró
He is an accomplished and performance-driven professional, CTO of ITware - with extensive experience and a proven track record in international business-, software development, and scientific research in the fields of mHealth, eHealth, ICT, and complex M2M/IoT solutions. Since 2017, he has led sport-related research, development, and innovation projects connected to Sunbears Cloud Campus (SBCC) Ecosystem in Japan with Japanese companies, universities, performance sports teams, and the Tokyo Institute of Technology (TIT). His main research interests include applied AI and advanced technologies in sports strategy, safety, early identification, and prevention or control of diseases and injuries. He is a strong advocate of innovation management. Attila is a 2xPhD candidate in Health Sciences at the University of Malaga (Spain) and Computer Science at the George Emil Palade University of Medicine, Pharmacy, Science, and Technology of Targu Mures (Romania). His research combines sensors and advanced technologies (such as behavior change techniques - BCTs, gamification) with machine vision, NLP, LLM, and emotion analysis, pushing the boundaries of technologies, sensors (such as body sensors, IMUs, medical radars), and AI in health and informatics. Currently, he is associate researcher at several universities. More…
Chris Richter
Dr. Chris Richter is a distinguished expert in academia, science, and industry, with a career spanning healthcare, professional sports, life sciences, and the digitalization of the German government. With over 70 peer-reviewed papers, reviewing activities for more than 15 scientific journals, and 15+ keynotes on movement and AI, Dr. Richter is a leading voice in his field.
Dr. Richter has served as the Head of Data Analytics and Innovation at the Sports Surgery Clinic in Dublin, pioneering advancements in healthcare. He has also consulted for professional sports, including roles with the English Premier League and the NBA as a Biomechanical Consultant at TotalPerformance. In the life sciences sector, he excelled as a Senior Applied Researcher at Kaia Health and currently leads the Data and Technology Team at Byte.
Driven by a passion for bridging the gap between advanced movement capture technologies and the delivery of automated, meaningful insights, Dr. Richter is dedicated to solving complex problems, enhancing processes, and exploring uncharted territories. His fascination with machine learning has made him an innovative force in sports and medical science, continually pushing the boundaries of what is possible.
Join Dr. Richter as he shares his insights on AI and injury prediction, and discover how his work is shaping the future of these fields.
Claudine Lamoth
Claudine Lamoth is a Professor of Movement Analysis and Smart Technology for Healthy Ageing at the University Medical Center Groningen / University of Groningen, Netherlands. Her research focuses on understanding gait and postural control mechanisms in age- and lifestyle-related disorders.
Lamoth's interdisciplinary approach combines dynamical systems theory, biomechanics, behavioral sciences, and data sciences. She collaborates with medical departments, biomedical technology experts, data scientists, artists, and industry partners on projects aimed at prevention, personalized interventions, and early risk detection. Her work is characterized by the innovative use of sensor technology and AI/data science methods. Part of this research involves developing, testing, and validating sensing and monitoring technology that can assess, remotely monitor, and provide personalized services to individuals in their natural (home) environment
Throughout her career, Lamoth has secured approximately €10 million in research grants and has mentored 15 PhD students and over 100 undergraduates. She currently leads a research group of 7 researchers and 12 PhD students.
Dzmitry Kaliukhovich
Dzmitry Kaliukhovich serves as a Senior Principal Data 
Scientist in the R&D Data Science & Digital Health division at Johnson & Johnson Innovative Medicine. He specializes in identification and evaluation of digital health technologies and tools for drug development in the pharmaceutical industry. In his role, Dzmitry supports activities related to patient enrichment, phenotyping, and monitoring of patient’s well-being in clinical trials as well as the development and validation of novel biomarkers and endpoints for treatment efficacy. His primary areas of interest cover several disease areas, including neuropsychiatric, neurodegenerative, and pulmonary diseases.
Dzmitry has a proven track of record in analyzing actigraphy, speech, active and passive sensing behavior data generated by wearable devices as well as electrophysiological and eye movement signals in primates and rodents. Dzmitry holds a master’s degree in Computer Science from Brest State Technical University, Belarus, and a Ph.D. in Cognitive Neuroscience from KU Leuven, Belgium. He is based in Antwerpen, Belgium.
Gergő Bolla
I’m a passionate Researcher with a robust background in biomedical engineering and clinical neuroscience. Currently pursuing a PhD in Clinical Neuroscience at Semmelweis University, I’m driven by the application of data science and machine learning in healthcare.
At the Neurocognitive Research Center, I have developed machine learning algorithms for early dementia detection using MRI data, contributing significantly to ongoing research efforts. This work involved collaborating closely with medical experts, ensuring that the models' outputs were both accurate and clinically relevant. Additionally, I played a key role in automating MRI data analysis and developing databases and KPI-s that improved the efficiency of anomaly detection.
Previously, I have contributed to the development and monitoring of machine learning models for pricing and revenue forecasting at Egis Pharmaceuticals. These models were integral to strategic decisions with substantial financial implications. I also designed interactive dashboards, enabling real-time insights into market trends.
Adept in Python, MATLAB, and a range of AI/ML libraries, proficient in data manipulation, visualization, and database management. Outside of work, I enjoy hiking, cycling, reading, and engaging in continuous learning.
Dedicated to leveraging data analytics/data science to drive innovation in both research and industry, aspiring to make impactful contributions to both healthcare and other industrial applications.
Gusztáv Fekete
Dr. Gusztáv Fekete is currently a Principle Research Fellow at the Széchenyi István University and a Guest Professor at the Ningbo University. He has a worked at several universities such the Hungarian University of Agriculture and Life Sciences
(2007-2010), Ghent University (2010-2013), University of West-Hungary (2014-2017), Eötvös Loránd University (2017-2024) and the Slovak Academy of Sciences (2024).
He has formed a Research Group in Applied Biomechanics in 2024, where at present he supervises the work of four PhD students. So far nine students obtained PhD under his supervision. He carries out active work at several Doctoral School in Hungary, for example he is a full external member of the University of Pannonia, Habilitation Committee and Doctoral Council. In addition, he is the regional vice-president of Hungarian Mechanical Engineering Scientific Association.
Dr. Fekete has published 115 peer-reviewed journal and conference papers
(Scopus Citations 1849, h-index 25). He is Editor of Physical Activity and Health journal (Ubiquity Press, UK, 2017-). Dr. Fekete has received several honors and awards including “Promising Researcher of the Eötvös Loránd University” (2022), “Dr. Csaba Gyenge Memorial Prize in recognition of outstanding research” (2022), “János Bolyai Scholarship” (2021). In 2023, he was listed among the Top 2% Researchers Based on Stanford University Database.
Luis Sigcha
Ph.D. in Mechanical Engineering by the Universidad Politécnica de Madrid (UPM), Master in Big Data Analytics from the European University of Madrid, and Master in Acoustic Engineering (UPM). Luis did his doctoral thesis at the Instrumentation and Applied Acoustics Research Group (I2A2-UPM) in collaboration with the Ergonomics & Human Factors Group (EHF) at the Universidade do Minho (Guimares-Portugal). His research involves the automatic detection of human movement using wearable sensors (wearables) and artificial intelligence with application in physical activity monitoring, Parkinson's disease assessment, and occupational risk prevention.
Luis is passionate in the application of cutting-edge technologies to solve real problems. He has participated in 8 research projects funded by competitive grants, authored 9 indexed scientific articles, 4 book chapters, and 9 presentations at international congresses. Additionally, his served as the director of 8 final degree projects (Bachelor and Master) and 1 Ph.D. student.
Currently he is working as a postdoctoral researcher in the cross-European Project: WEALTH (Wearable sensors for the assessment of physical and eating behaviours) and the Spain project: Biomarcadores digitales para la evaluación del estado motor de pacientes con Enfermedad de Párkinson para su aplicación Clínica y Terapéutica (BIOCLITE). Also, he is part of the Data-Driven Computer Engineering Research Group (D2ICE), in the Department of Electronic and Computer Engineering, and the Health Research Institute (HRI) at the University of Limerick.
Melissa Boswell
Melissa Boswell, VP of Science and Research at the Joe Gibbs Human Performance Institute, is at the forefront of bioengineering innovation, driving research and advancements in the field. Melissa heads JGHPI’s human performance research vision by bridging the cross-disciplinary work of the biomechanics and machine learning groups and leading collaborative research projects between JGHPI and outside organizations and universities. She is also passionate about quantifying movement as a biomarker, motivating physical activity, and increasing access to health care.
Before joining the Human Performance Institute, Melissa was a postdoctoral scholar in the Neuromuscular Biomechanics Laboratory at Stanford University, where she received her PhD in Bioengineering. Her doctoral work was focused on digital tools for increasing access to biomechanical assessments. During her postdoctoral work, she designed and led a digital clinical trial to test the efficacy of a mobile psychological intervention for knee osteoarthritis using at-home biomechanical assessments as a novel functional outcome measure.
While at Stanford, Melissa founded and hosted the podcast Biomechanics On Our Minds and organized Stanford’s National Biomechanics Day. She is a member of the International Society of Biomechanics and a Women in Sports Data Fellow, promoting diversity and equity in sports analytics. Melissa has experience as a consultant and strategic advisor for multiple fitness and digital therapeutic companies, fostering collaboration between engineers, clinicians, and designers to create user-centric solutions that have positively impacted the lives of athletes and individuals with chronic pain.
Melissa remains steadfast in her commitment to a creative, human-centered, holistic approach to engineering and health as a dedicated leader in bioengineering.
Neil Cronin
I am a Professor of Exercise Biology at the University of Jyväskylä. My research spans human locomotion, imaging techniques, and more recently, applications of artificial intelligence in the sport and health domains. In particular, in recent years I have explored the use of markerless pose estimation, generative AI techniques for audio and video synthesis, and various medical imaging analysis techniques. At the Budapest Symposium, I will give an overview of recent developments in AI, specifically related to biomechanics and medical image analysis.
Peter van Ooijen
Prof. Dr. Ir. P.M.A. (Peter) van Ooijen is a distinguished professor in at the University Medical Center Groningen, specializing in Medical Informatics, Computer Science, and Artificial Intelligence. With over 25 years of experience in medical imaging informatics, he has made significant contributions to the field, particularly in the application of machine learning and deep learning into medical imaging.
Prof. van Ooijen's research at the department of Radiotherapy focuses on the detection, segmentation, diagnosis, treatment, and prediction of cancer. His work is highly regarded in the scientific community, and he continues to push the boundaries of AI in healthcare.
In addition to his research, Prof. van Ooijen holds several key positions. He is the theme coordinator for "Digital Healthcare" at Jantina Tammes School, coordinator of the Machine Learning Lab at the Data Science Center in Health (DASH), and the president of the European Society of Medical Imaging Informatics (EuSoMII). He also serves on the editorial board of several prestigious journals.
Prof. van Ooijen's prolific academic output is evident in his publication record. He has co-authored more than 200 PubMed enlisted papers and contributed to numerous book as editor and author, contributing significantly to the body of knowledge in his field.
Aim
Three poster presentations will be awarded at the 2nd Biomechanics in Sport and Ageing Symposium — Artificial intelligence. The aim of the award is to acknowledge outstanding scientific contributions of under/graduate/postgraduate students in the field of artificial intelligence in sports and ageing.
How to apply?
All accepted abstracts will be considered for the award. The award panel will shortlist presentations based on the scientific merit of the abstracts.
Prize (shared prize is possible)
- 1st place: 300 €
- 2nd place: 200 €
- 3rd place: 100 €
Application criteria
Undergraduate, graduate, or postgraduate students can apply. Applicant student must be the registered first author of the submitted abstract and will need to present the poster in person at the poster session of the symposium. Each pitch lasts for 3 minutes while standing by the poster followed by an answer-question period of 2 minutes. Poster presentations to be awarded are of high quality in terms of scientific merit, presentation skills, and the ability to answer questions.
Abstract format
Title, authors, affiliations, first author’s email address, 350 words of text structured as follows: Background, Methods, Results, Conclusions, Acknowledgements. The header and funding acknowledgements are excluded from the 350 words.
Poster format
Participants are encouraged to use minimal amount of text and use instead graphics, illustration as the main vehicle to present information. Title banner followed by Background, Methods, Results, and Conclusions organized in a columnar format. The size of the poster should be A0 (height 120 cm, width 90 cm), which can be recorded on flipchart boards.
Decision and announcement
A panel decides on the awards and their decisions are final. Awards are announced at the closing dinner of the symposium.
Submission deadline: The upload deadline has ended.
Invited speakers to submit an abstract in word.docx format, comprising up to 350 words. Format the abstract as follows:
- Title
- Name
- Affiliation
- Email address
- Abstract text (up to 350)
- Acknowledgements
- All abstracts will be complied into a pdf online booklet.
Submission deadline: 27 September 2024
tf.hu/bsa |
Program | Abstract booklet | Registration | Speakers | Student poster award | Continuing education credits | Conference venue | Budapest | Accommodation | Social programs | Committees | Contact
Welcome to the 2nd Biomechanics in Sport and Ageing Symposium: Artificial Intelligence, organized by the Hungarian University of Sports Science and the Department of Kinesiology, Budapest, Hungary, 15-16 October 2024!
The aim of the symposium is to provide a scientific platform for a state-of-the-art update on the progress of artificial intelligence, AI, in sport biomechanics and ageing. Artificial intelligence relies on computers to execute commands that historically required human intelligence. Now, we have apps that offer talking digital assistant services, respond to voice and text requests, it can answer questions, write poetry, generate images, draft emails, analyze personal photos, set a timer or place a phone call. Indeed, as we can surmise it from Turing’s seminal paper, AI builds computational units that mimic human intelligence and abilities: language, communication, comprehension of concepts, automated thinking, (machine) learning, computer vision, and movements via robotics (1). Supervised or unsupervised machine learning, i.e., the science of coding computers to learn and behave as humans do, as a subset of AI, allows us to discern patterns and structure in data. Deep learning optimizes supervised learning and trains models to learn how to map an input to an expected output (2). All this occurring at a neck breaking pace so that “global governance is needed, otherwise the risk is social collapse” opines Paolo Benanti, a Vatican and Italian government advisor on AI ethics.
The tools of AI are also becoming ubiquitous in sport biomechanics and ageing research. Sport and ageing might appear unrelated. Yet we consider sport and ageing as complementary: assessment and training methods developed in sport science are transformed into diagnosis and treatment of ageing-related impairments. Along the spectrum from low and to high levels of physical and cognitive function, the current symposium highlights how AI is leveraged to assess and increase top performance, predict motor and cognitive function, and ultimately deliver improved care for all individuals across the lifespan, including athletes and seniors (3).
Accordingly, the lead keynote will introduce AI and the following two keynotes will provide a state-of-the-art overview of AI in sport and ageing. From 6 countries, 12 invited area-expert speakers will give (big) data-based examples for how AI is used in sport and ageing with respect to: Body structure and exercise prescription; Motor-cognitive function; Injury and disease, and Performance assessment and prediction in a workshop format.
Welcome to Budapest! Network, learn, and enjoy the symposium!
Sincerely yours,
Prof. dr. Tamás Sterbenz, PhD, Rector and Patron of the symposium
Prof. dr. h. c. Tibor Hortobágyi, PhD, chair of the scientific committee
Mr. Dániel Mezei and Ms. Eszter Kerekes, chairs of the organizing committee
References:
- Turing AM. On computable numbers, with an application to the Entscheidungsproblem. Proc London Math Soc 58: 230–65, 1936.
- LeCun et al Deep learning. Nature 521: 436–44, 2015.
- Zhang et al Leveraging physiology and artificial intelligence to deliver advancements in health care. Physiol Rev 103: 2423–50, 2023.
