EEG-Based Workload Index as a Taxonomic Tool to Evaluate the Similarity of Different Robot-Assisted Surgery Systems

In operational fields, there is a growing use of simulators during training protocols because of their versatility, the possibility of limiting costs and increasing efficiency. This work aimed at proposing an EEG-based neurometric of mental workload, previously validated in other contexts, as a taxonomic tool to evaluate the similarity, in terms of cognitive demands, of two different systems: the da Vinci surgical system, leader in the field of robotic surgery, and the Actaeon Console by BBZ, basically a cheaper simulator aimed to train students to use the da Vinci system. Such a neurophysiologic evaluation of the workload demand was also integrated by information derived by the task performance and self-reports. The results validated the proposed EEG-based workload index and indicated the potentially fruitful use of simulators because of their high similarity in terms of cognitive demands.