Inferring mental workload changes of subjects unfamiliar with a touch screen game through physiological and behavioral measurements

• Online Access: http://hdl.handle.net/2047/D20214104

Many tasks can be demanding for human operators, including operating an aircraft, driving a vehicle, and making decisions in an air traffic control setting. These tasks, depending on their complexity, cause increased mental workload on humans, which could then lead to human errors. Understanding the interaction dynamics between the human operators and tasks requires effectively detecting and carefully evaluating human mental states. If done successfully, this would help design ways by which the machine can infer mental states and respond intelligently to the operator in a way to assist with the objective to reduce the probability of human error in a task.