Firefighters are often exposed to a variety of harmful influences at incident scenes, and therefore, subjected to extreme levels of physical and mental stress, due to their operations being intrinsically linked with health risks and life-threatening events. However, innovative technical solutions can offer a way to minimize such hazards.
The objectives of the project are based on the intent to introduce sensors which are able to measure the vital signs of on-site firefighter personnel and wirelessly transmit the details to mission control. This innovation is intended to protect emergency forces and to provide support for decisions such as modifications or cancellation of the operation.
On behalf of the Bundesanstalt für Arbeitsschutz und Arbeitsmedizin (BAuA, German Federal Institute for Occupational Safety and Health) and in cooperation with the Deutsches Institut für Katastrophenmedizin (DIFKM, German Institute for Crisis Medicine), the Zentrum für Brand- und Explosionsschutz (DMT, Centre for Fire and Explosion Prevention) and the company MSA-Auer, a mathematical model was developed, which consists of environmental parameters, motion parameters, vital signs, individual fitness values as well as the subjective assessment of physical and mental stress levels of firefighters.
The project began with a comprehensive literature analysis and review of relevant studies, with a focus on findings on the measurement of vital parameters in due consideration of the inter-individual limit values and the influence of environmental factors. The insights accumulated in this initial phase are then used as a theoretical basis for the first stage of mathematical modeling by HFC. To create a sufficient set of data as training material for the algorithm, HFC and DMT also conducted a series of field experiments with relief forces.
In these studies, several physiological and psychological parameters of about 40 firefighters were recorded during a training exercise involving a fire tunnel. In a further step, a multidimensional classification model was derived, reduced to a set of mathematical functions based on the data acquired by HFC. The result was an algorithm, which derives individualized sensor information and the workload levels of fire fighters, and uses them to indicate the exceedance of relevant limit values.
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