KIRETT: Smart Integration of Vital Signs Data for Intelligent Decision Support in Rescue Scenarios

TL;DR

The paper tackles decision support in rescue operations by integrating vital signs into a knowledge-graph-based framework. It introduces KIRETT, a wrist-worn wearable that combines situation detection and treatment recommendations derived from a rescue-operation knowledge graph and real-time vital data. The authors analyze how often vital signs appear in emergency treatment paths and present an implementation where vital data can influence or skip steps, visualized within a treatment graph. They discuss evaluation findings, practical benefits, and future directions, including machine-learning extensions, alarms, interoperability, and usability studies.

Abstract

The integration of vital signs in healthcare has witnessed a steady rise, promising health professionals to assist in their daily tasks to improve patient treatment. In life-threatening situations, like rescue operations, crucial decisions need to be made in the shortest possible amount of time to ensure that excellent treatment is provided during life-saving measurements. The integration of vital signs in the treatment holds the potential to improve time utilization for rescuers in such critical situations. They furthermore serve to support health professionals during the treatment with useful information and suggestions. To achieve such a goal, the KIRETT project serves to provide treatment recommendations and situation detection, combined on a wrist-worn wearable for rescue operations.This paper aims to present the significant role of vital signs in the improvement of decision-making during rescue operations and show their impact on health professionals and patients in need.

Figures (3)

• Figure 1: This figure outlines the integration of vital signs into a knowledge graph through three modules: GUI, Graph, and Middleware. The GUI visually displays treatment steps with vital signs, sourced from the database. The Graph hosts the knowledge graph, providing content for visualization and managing data retrieval from the database. The Middleware component stores values from medical devices and control center information in a structured database, facilitating data retrieval for inquiries through the graph.
• Figure 2: This figure presents the visualization of vital signs on the KIRETT wearable. Providing buttons to accept and decline, the Graphical User Interface (GUI) provides the ability to actively decide whether the value provided in the treatment step matches with the data from the database. This is an additional security layer for the rescue operator, to actively change, observe and decide on the best treatment of the patient.
• Figure 3: This figure outlines a proactive notification system designed to adjust treatment paths based on historical data and vital signs. When a threshold is breached, an alarm is activated, storing the current vital signs and treatment step. Rescue operators can review the alarm and decide whether to modify their treatment path approach accordingly.