Sports Medicine and AI: What Lies Ahead?
Xavier Valle, Hospital Universitario DEXEUS-ICATME, Spain
Resistive and Propulsive Forces in Swimming: Challenges and Novel Insights
Paola Zamparo, University of Verona, Italy
Sports Medicine and AI: What Lies Ahead?
Xavier Valle
Hospital Universitario DEXEUS-ICATME
Spain
Brief Bio
Sports physician with over 20 years of experience working with elite athletes from different sports, international artists, and global business leaders. Expert in managing multidisciplinary teams, developing innovative health projects, and implementing cutting-edge medical technologies. Proven track record of leading high-performance medical units and contributing to advancements in sports medicine at a global level.
Adrian Martínez
University of Lucerne
Switzerland
Brief Bio
Adrian Martinez de la Torre is an Assistant Professor in Functioning Epidemiology at the University of Lucerne, Switzerland, and Group Leader at the Swiss Paraplegic Research. He holds a PhD in Machine Learning for Pharmacoepidemiology from ETH Zurich. Adrian’s research focuses on developing and applying advanced statistical methods and machine learning models to analyze how functioning progresses and interacts with disease progression. His work leverages extensive electronic health records and clinical databases to gain insights into these complex relationships. Adrian has a strong interest in sports rehabilitation, particularly in predicting return-to-play timelines for football players, and has collaborated with FC Barcelona on related projects.
Abstract
Artificial Intelligence (AI) is transforming various medical fields by enabling advanced data analysis and predictive modeling. In sports medicine, AI offers innovative solutions for injury diagnosis, management, and prognosis, enhancing athlete care and recovery. This presentation provides an overview of AI principles and explores their application in the assessment of muscle injuries, including diagnostic accuracy and prognosis prediction. We will discuss how AI-driven tools can assist clinicians in early detection, personalized treatment planning, and outcome forecasting. Additionally, the talk will emphasize the importance of collaboration between medical associations (ECOSEP) and industrial partners to achieve these goals and accelerate the integration of AI into sports medicine practice.
Resistive and Propulsive Forces in Swimming: Challenges and Novel Insights
Paola Zamparo
University of Verona
Italy
Brief Bio
Paola Zamparo graduated in biology at the University of Trieste (I) and worked for about 20 years in the field of exercise physiology at the University of Udine (I), under the supervision of Prof. di Prampero. She then moved to the University of Verona (I) and now are about 20 years that she is working in the field of biomechanics. She did her PhD at Manchester Metropolitan University (UK) under the supervision of Prof. Minetti, and she is author of more than 100 papers published in international scientific, peer-reviewed journals. Her main field of interest is the interplay between the biomechanics and energetics of human locomotion: i.e., how the mechanical determinants of cyclic sports activities (such as cycling, swimming and running) influence their physiological responses.
Abstract
Measuring propulsive and resistive forces in the water environment is not an easy task. Propulsive forces are necessarily reduced in water due to a lower propelling efficiency compared to land locomotion, and resistive forces are easy to measure in passive conditions but not during actual swimming movements. After reviewing the pros and cons of the most common methods to determine propulsive and resistive forces at constant speed (a condition in which these should be equal and opposite), a novel method will be presented, based on a standing start test (where the velocity steadily increases up to a maximum value). This method is particularly interesting as it can be implemented in practice with low-cost equipment (such as an IMU) or any velocity measurement system. Based on data of maximum velocity and acceleration time, it is possible to estimate the propulsive and resistive forces generated by the swimmer; since in this test the speed is (typically) not constant, the added mass of the swimmer must also be known. Notably, the values of propulsive force and active drag coefficient calculated in this manner are similar to those obtained by means of the residual thrust method (which is based on full and semi-tethered tests), which will also be presented and discussed.