In emergencies, treatment needs to be fast, accu-rate and patient-specific. For instance, in emergency scenarios, obstacles like treatment environments and medical difficulties can lead to bad outcomes for patients. Additionally, a drastic change of health vitals can force paramedics to shift to a different treatment in the ongoing treatment of the patient in order to save a patient's life. The KIRETT (engl.: 'Artificial intelligence in rescue operations') demonstrator is developed to provide a rescue operator with a wrist-worn device, enabling treatment recommendation (with the help of knowledge graph) with situation detection models to improve the emergency treatment of a patient. This paper aims to provide a qualitative evaluation of the 2-days testing in the KIRETT project with the focus of knowledge graphs, knowledge fusion, and user-experience-design (UX-design).
@article{arxiv.2509.24831,
title = {Rescue Operators' Perspectives on KIRETT Wearable Technology: A Qualitative Study},
author = {Mubaris Nadeem and Johannes Zenkert and Lisa Bender and Christian Weber and Madjid Fathi},
journal= {arXiv preprint arXiv:2509.24831},
year = {2025}
}
Comments
Conference paper for 2024 IEEE International Conference on Systems, Man, and Cybernetics (SMC), KIRETT Project, University of Siegen, Germany