CoWME: a general framework to evaluate cognitive workload during multimodal interaction

Evaluating human machine interaction in the case of multimodal systems is often a difficult task involving the monitoring of multiple sources, data fusion and results interpretation. While subtasks are highly dependent on the specific goal of the application and on the available interaction modalities, it is possible to formalize this workflow into a standard process and to consider a generic measure to estimate the ease of use of a specific application. In this work, we present CoWME, a modular software architecture describing multimodal human machine interaction evaluation, from data collection to final evaluation, in a formal way, in terms of cognitive workload. Communication protocols between modules are described in XML while data fusion is delegated to a configurable rule engine. An interface module is introduced between the monitoring modules and the rule engine to collect and summarize data streams for cognitive workload evaluation. We present a deployment example showing how this architecture is deployed by monitoring an interactive session with an Android application taking into account stressed speech detection, mydriasis and touch analysis.