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, yielding recognition rates of up to for three levels of workload.