Multimodal Recognition of Cognitive Workload for Multitasking in the Car

This work describes the development and evaluation of a recognizer for different levels of cognitive workload in the car. We collected multiple biosignal streams (skin conductance, pulse, respiration, EEG) during an experiment in a driving simulator in which the drivers performed a primary driving task and several secondary tasks of varying difficulty. From this data, an SVM based workload classifier was trained and evaluated.