Finalisation of the KIRETT funding project

Funded by the Federal Ministry of Education and Research (BMBF) as part of the ‘KMU-innovativ’ initiative, the KIRETT project has gained valuable insights for emergency medicine. The aim of the project in the ‘Research for Civil Security’ programme was to investigate whether first aid during rescue operations can be improved by a portable device, a so-called wearable. This device is used for computer-aided situation recognition and provides rescue personnel with context-dependent recommendations on the course of treatment using artificial intelligence and machine learning.

The KIRETT wearable integrates several innovative functions into the rescue operation. By combining data from the control centre, medical devices and input from the emergency services, the aim is to significantly increase the efficiency and quality of first aid. The demonstrator developed enables the emergency services to focus their full attention on the emergency patient by automatically providing relevant operational data during the course of treatment. The operational data collected is used to optimise first aid algorithms and training in the emergency services.

A key aspect of the project was to improve the quality of care in special emergency situations. In mass casualty scenarios, where many injured people have to be treated at the same time, and in rare emergencies, such as a snake bite, uncertainty, high workloads and excessive demands on the emergency services can occur. The wearable makes an important contribution here by automatically recording and analysing vital data such as oxygen saturation and heart rate as well as operational data from the control centre and input from the emergency services. This makes it possible to close experience gaps and increase the degree of fulfilment of the necessary measures
 

From concept development to implementation

The KIRETT project began in July 2021 with the design and development of a portable demonstrator. At the beginning, the concept was jointly developed on the basis of use cases to ensure that the solutions developed would meet the real requirements of rescue operations. The project partners contributed their expertise in various areas: The development included interface programming to medical devices, machine learning for artificial intelligence on a field programmable gate array (FPGA) and the implementation of a graph database to select treatment alternatives provided by the rescue service for the project from a knowledge graph. This early demonstrator was continuously improved and finally evaluated in co-operation with the associated partners in Siegen. The local support from the city of Siegen and the Jung-Stilling Hospital during the conception phase enabled the development of a practical solution.
 

The development of a portable device for rescue operations poses numerous technical challenges. One of the biggest hurdles is the integration of various data sources. The wearable must be able to process data from medical devices, such as ECGs and ventilators, as well as operational data from the control centre and manual input from rescue workers. At the same time, advanced artificial intelligence algorithms can be used to analyse the collected data quickly and reliably and generate context-dependent recommendations for action. The treatment alternatives are selected from a knowledge graph depending on the situation and displayed on the screen. Various treatment steps are confirmed and selected via touch input.
 

Evaluation and local partnerships

During the evaluation phase in Siegen, relevant key figures on the quality of situation recognition and context-dependent recommendations for action were collected. The portable device was tested and trialled in various deployment scenarios at the Siegen fire and rescue station. This was followed by a digitally supported quantitative survey and a qualitative evaluation in the form of interviews. The local partners played a crucial role by providing valuable feedback and support during the tests. These partnerships made it possible to test and optimise the KIRETT demonstrator in various application scenarios.

The results of the KIRETT project lay the foundation for a sustainable improvement in emergency medicine. The technologies and methods developed in the project can be further used and optimised in future projects and applications. In particular, the combination of wearable devices and artificial intelligence offers great potential for the further development of medical care. One possible future area of application for the KIRETT wearable is preclinical care in rural areas. In regions where access to medical care is limited, the wearable could play an important role by supporting initial treatment by less experienced personnel and thus increasing patients' chances of survival. The knowledge and experience gained in the project can also be incorporated into the further development of training programmes for rescue workers.
 

Joint closing event

At the end of the project period, a final project meeting was held on 7 June 2024 to present and celebrate the results achieved. The results of the project partners with presentations and the demonstrations with the final wearable model showed impressively how the integration of artificial intelligence and wearable devices can shape the future of emergency medicine. The continuation of research and development in this field will be crucial to further improve the quality of care and set new standards.
 

The KIRETT project was a joint endeavour between the following partners: CRS medical GmbH (Aßlar), mbeder GmbH (Siegen), the Chair of Embedded Systems (Prof. Dr Roman Obermaisser) and the Institute for Knowledge-Based Systems and Knowledge Management (Prof. Dr Madjid Fathi) at the University of Siegen. The associated partners were the district of Siegen-Wittgenstein, the city of Siegen, the German Red Cross Siegen and the Jung Stilling Hospital in Siegen. The total funding for the project totalled 1.3 million euros. The KIRETT project was a joint venture between the following partners: CRS medical GmbH (Asslar), mbeder GmbH (Siegen), the Chair of Embedded Systems (Prof. Dr Roman Obermaisser) and the Institute for Knowledge-Based Systems and Knowledge Management (Prof. Dr Madjid Fathi) at the University of Siegen. The associated partners were the district of Siegen-Wittgenstein, the city of Siegen, the German Red Cross Siegen and the Jung Stilling Hospital in Siegen. The total funding for the project totalled 1.3 million euros.