The European project ProeTEX realized a novel set of prototypes based on smart garments
that integrate sensors for the real-time monitoring of physiological, activity-related and environmental
parameters of the emergency operators during their interventions. The availability of these parameters
and the emergency scenario suggest the implementation of novel classification methods aimed at
detecting dangerous status of the rescuer automatically, and based not only on the classical activityrelated
signals, rather on a combination of these data with the physiological status of the subject. Here
we propose a heart rate and accelerometer data fusion algorithm for the activity classification of
rescuers in the emergency context
