Horse riding falls under the “Sport for Life” disciplines, where a long-term equestrian development can provide a clear pathway of developmental stages to help individuals, inclusive of those with a disability, to pursue their goals in sport and physical activity, providing long-term health benefits. However, the biomechanical interaction between horse and (disabled) rider is not wholly understood, leaving challenges and opportunities for the horse riding sport. Therefore, the purpose of this KIEM project is to start an interdisciplinary collaboration between parties interested in integrating existing knowledge on horse and (disabled) rider interaction with any novel insights to be gained from analysing recently collected sensor data using the EquiMoves™ system. EquiMoves is based on the state-of-the-art inertial- and orientational-sensor system ProMove-mini from Inertia Technology B.V., a partner in this proposal. On the basis of analysing previously collected data, machine learning algorithms will be selected for implementation in existing or modified EquiMoves sensor hardware and software solutions. Target applications and follow-ups include: - Improving horse and (disabled) rider interaction for riders of all skill levels; - Objective evidence-based classification system for competitive grading of disabled riders in Para Dressage events; - Identifying biomechanical irregularities for detecting and/or preventing injuries of horses. Topic-wise, the project is connected to “Smart Technologies and Materials”, “High Tech Systems & Materials” and “Digital key technologies”. The core consortium of Saxion University of Applied Sciences, Rosmark Consultancy and Inertia Technology will receive feedback to project progress and outcomes from a panel of international experts (Utrecht University, Sport Horse Health Plan, University of Central Lancashire, Swedish University of Agricultural Sciences), combining a strong mix of expertise on horse and rider biomechanics, veterinary medicine, sensor hardware, data analysis and AI/machine learning algorithm development and implementation, all together presenting a solid collaborative base for derived RAAK-mkb, -publiek and/or -PRO follow-up projects.
In societies where physical activity levels are declining, stimulating sports participation in youth is vital. While sports offer numerous benefits, injuries in youth are at an all-time high with potential long-term consequences. Particularly, women football's popularity surge has led to a rise in knee injuries, notably anterior cruciate ligament (ACL) injuries, with severe long-term effects. Urgent societal attention is warranted, supported by media coverage and calls for action by professional players. This project aims to evaluate the potential of novel artificial intelligence-based technology to enhance player monitoring for injury risk, and to integrate these monitoring pathways into regular training practice. Its success may pave the way for broader applications across different sports and injuries. Implementation of results from lab-based research into practice is hindered by the lack of skills and technology needed to perform the required measurements. There is a critical need for non-invasive systems used during regular training practice and allowing longitudinal monitoring. Markerless motion capture technology has recently been developed and has created new potential for field-based data collection in sport settings. This technology eliminates the need for marker/sensor placement on the participant and can be employed on-site, capturing movement patterns during training. Since a common AI algorithm for data processing is used, minimal technical knowledge by the operator is required. The experienced PLAYSAFE consortium will exploit this technology to monitor 300 young female football players over the course of 1 season. The successful implementation of non-invasive monitoring of football players’ movement patterns during regular practice is the primary objective of this project. In addition, the study will generate key insights into risk factors associated with ACL injury. Through this approach, PLAYSAFE aims to reduce the burden of ACL injuries in female football players.
