Ricerc@Sapienza

Human physiological parameters have been proven as reliable and objective indicators of user’s mental states, such as the Mental Workload. However, standard methodologies for evaluating physiological parameters generally imply a certain grade of invasiveness. It is largely demonstrated the relevance of monitoring workers to improve their working conditions. A contactless approach to estimate workers’ physiological parameters would be highly suitable because it would not interfere with the working activities and comfort of the workers.

Car driving is considered a very complex activity, consisting of different concomitant tasks and subtasks, thus it is crucial to understand the impact of different factors, such as road complexity, traffic, dashboard devices, and external events on the driver’s behavior and performance. For this reason, in particular situations the cognitive demand experienced by the driver could be very high, inducing an excessive experienced mental workload and consequently an increasing of error commission probability.

Car driving is considered a very complex activity, consisting of different main tasks and subtasks. For this reason, in particular situations the cognitive demand on the driver can be very high, and this large mental workload decreases performance and increases the probability of error commission. In this preliminary study a workload index based on electroencephalography (EEG), i.e., brain activity of eight drivers in real traffic conditions, is validated.

Car driving is a complex activity, consisting of an integrated multi-task behavior and requiring different interrelated skills. Over the last years, the number of Advanced Driver Assistance systems integrated into cars has grown exponentially. So it is very important to evaluate the interaction between these devices and drivers in order to study if they can represent an additional source of driving-related distraction.

One century after the first recording of human electroencephalographic (EEG) signals, EEG has become one of the most used neuroimaging techniques. The medical devices industry is now able to produce small and reliable EEG systems, enabling a wide variety of applications also with no-clinical aims, providing a powerful tool to neuroscientific research. However, these systems still suffer from a critical limitation, consisting in the use of wet electrodes, that are uncomfortable and require expertise to install and time from the user.

The human capacity to simultaneously perform several tasks depends on the quantity and the mode of mentally processing the information imposed by the tasks. Since operational environments are highly dynamic, priorities across tasks will be expected to change as the mission evolves, thus the capability to reallocate the mental resources dynamically depending on such changes is very important. The resources required in very complex situations, such as air traffic management (ATM), can exceed the user's available resources leading to increased workload and performance impairments.