AISep 30, 2025

Quantitative Evaluation of KIRETT Wearable Demonstrator for Rescue Operations

arXiv:2509.25928v11 citationsh-index: 112024 IEEE World AI IoT Congress (AIIoT)
Originality Synthesis-oriented
AI Analysis

This addresses the problem of time-critical medical emergencies for rescue services by introducing a wearable demonstrator, but it appears incremental as it builds on existing technologies like AI and vitals-monitoring.

The paper presents quantitative results from a two-day evaluation of the KIRETT wearable device, which aims to provide treatment recommendations and real-time monitoring for rescue operations, involving 14 participants to analyze rescue operators' needs.

Healthcare and Medicine are under constant pressure to provide patient-driven medical expertise to ensure a fast and accurate treatment of the patient. In such scenarios, the diagnosis contains, the family history, long term medical data and a detailed consultation with the patient. In time-critical emergencies, such conversation and time-consuming elaboration are not possible. Rescue services need to provide fast, reliable treatments for the patient in need. With the help of modern technologies, like treatment recommendations, real-time vitals-monitoring, and situation detection through artificial intelligence (AI) a situation can be analyzed and supported in providing fast, accurate patient-data-driven medical treatments. In KIRETT, a wearable device is developed to support in such scenarios and presents a way to provide treatment recommendation in rescue services. The objective of this paper is to present the quantitative results of a two-day KIRETT evaluation (14 participants) to analyze the needs of rescue operators in healthcare.

Foundations

The foundational work for this paper's niche, ranked by how specifically the neighbourhood builds on it — not by global fame.

Your Notes