Methodological framework for a user-centered, structured, and digitized training program for exoskeleton pilots in CYBATHLON preparation.

PURPOSE: Successful participation in the CYBATHLON depends not only on technical innovation but also on effective, systematic training of pilots with spinal cord injury. Current research primarily focuses on clinical rehabilitation, while standardized, task-specific training protocols for applied competition settings are lacking. To address this gap, this methodology paper presents a scientifically grounded training concept for exoskeletons, focusing on the qualification of trainers as key facilitators who adapt exercises and mediate between human and machine.

RESULTS

A modular 12-week training program with 38 units was developed and implemented through a Moodle-based e-learning platform, demonstrating the practical applicability of the proposed methodological framework. The program progresses from basic movement exercises to competition-specific obstacle tasks from the CYBATHLON Exoskeleton Race. The curriculum integrates theoretical content on safety and exoskeleton handling with practical training scenarios. Trainer qualification forms the central element, enabling individualized adaptation of exercises to pilot capabilities and exoskeleton requirements. The concept allows for scalable application and provides a consistent framework that can be updated according to future CYBATHLON regulations and technological developments.

CONCLUSION

The developed user-centered and digitized training program provides an effective structure for preparing trainers and pilots for the CYBATHLON. Combining modular design, digital learning tools, and individualizable adaptation, it establishes a transferable framework applicable to other exoskeleton systems. Beyond its practical use, the framework introduces a replicable methodology for developing and implementing training concepts in human–machine interaction, forming a foundation for evidence-based and transferable training standards in assistive robotics.