Ankle ReLoad
Xsens is participating in Ankle ReLoad, an EU Interreg-funded cross-border project focused on improving ankle fracture recovery monitoring in both clinical and home settings. The project aims to enable accurate estimation of ankle load outside the lab by combining lab-grade measurements with wearable IMU data, supported by machine learning and musculoskeletal simulation. The outcome is a demonstrator and digital application that provides continuous, personalized feedback for patients and healthcare professionals.
Project partners: Roessingh Research and Development, GEBIOM GmbH, Medisch Spectrum Twente, Medizinische Hochschule Hannover, Predimo GmbH, Sint Maartenskliniek (SMK), Saxion University, University of Münster, University of Twente, Center for Ambulatory Rehabilitation, Ziekenhuisgroep Twente.
Runner Assist
Runner Assist is a project funded by the European Union within the European Fund for Regional Development (EFRO). The project aims at developing a wearable measurement system to monitor running technique and to provide feedback to the runner during and after the activity, with the goal of increasing performance and reducing injuries.
Compared to other available systems, Runner Assist distinguishes itself through a personal approach by extracting and providing feedback based on individual runner data and personalized parameters. The consortium consists of Roessingh Research and Development, Sensorun, Trimm, and Xsens, and is supported by Demcon Advanced Mechatronics.
AnDy
Recent technological progress in robot physical interaction has permitted robots to actively and safely share a common workspace with humans. Leveraging these technologies, AnDy aims to strengthen European leadership in the robotic market by endowing robots with the ability to control physical collaboration through intentional interaction. AnDy will innovate the way of measuring human whole-body motions developing a wearable force and motion tracking technology (AnDy suit), and proposing technologies to learn cognitive models of human behavior in collaborative tasks (AnDy model) and to help humans, through predictive physical collaboration (AnDy control).
