Objectives This paper presents a remote triage support algorithm as a part of a complex military telemedicine system which provides continuous monitoring of soldiers’ vital sign data gathered on-site using unobtrusive set of sensors.

Methods The proposed fuzzy logic-based algorithm takes physiological data and classifies the casualties according to their health risk level, calculated following the Modified Early Warning Score (MEWS) methodology.

Results To verify the algorithm, eight different evaluation scenarios using random vital sign data have been created. In each scenario, the hypothetical condition of the victims was assessed in parallel both by the system as well as by 50 doctors with significant experience in the field. The results showed that there is high (0.928) average correlation of the classification results.

Discussion This suggests that the proposed algorithm can be used for automated remote triage in real life-saving situations even before the medical team arrives at the spot, and shorten the response times. Moreover, an additional study has been conducted in order to increase the computational efficiency of the algorithm, without compromising the quality of the classification results.