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

2025-09-30

AI Summary

To address critical delays in vital-sign data fusion and low decision-making efficiency in emergency rescue scenarios, this study proposes a wearable intelligent decision support system tailored for prehospital care. The system uniquely integrates real-time multimodal physiological signal acquisition (e.g., heart rate, blood oxygen saturation, galvanic skin response), lightweight edge-based machine learning classification—trained on clinical emergency protocols—and context-aware decision modeling directly onto a wrist-worn device, enabling sub-second patient assessment and actionable intervention recommendations. Leveraging physiological signal processing, dynamic multi-source data weighting, and embedded edge computing, the system demonstrates robust performance under high-stress, real-world rescue conditions: average decision latency is reduced by 62%, and intervention accuracy improves by 28%. This work establishes a deployable, low-latency, and highly robust technical paradigm for intelligent emergency response systems.

Technology Category

• Intelligent Robots: Multimodal Perception & Sensor Fusion
• Humans and AI: Planning and Decision Support for Human-Machine Teams
• Machine Learning: Hardware-aware ML

Application Category

• Systems and Infrastructure for Web, Mobile and WoT: Applied ML and AI for Web-based mobile applications
• Responsible Web: Machine-in-the-loop, human agency and autonomy
• Search and Retrieval-Augmented AI: Web evaluation methodologies and metrics

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.

Problem

• Integrating vital signs for intelligent rescue decision support
• Providing treatment recommendations via wearable devices
• Improving time utilization during critical rescue operations

Innovation

• Smart integration of vital signs data
• Wrist-worn wearable for rescue operations
• Provides treatment recommendations and situation detection