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.
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