BCI-based user training in surgical robotics

Human error is a critical risk in surgery, so an important aim of surgical robotic systems is to improve the performance and the safety of surgical operations. Such systems can be potentially enhanced by a brain-computer interface (BCI) able to monitor the user´s mental focus and use this information to improve the level of safety of the procedures. In order to evaluate such potential usage of BCIs, this paper describes a novel framework for training the user to regulate his/her own mental state while performing surgery-like tasks using a robotic system. This self-regulation is based on augmented reality (AR) feedback representing the BCI-monitored mental state, which helps the user´s effort in maintaining a high level of mental focus during the task. A comparison between a BCI-based training and a training without a BCI highlighted a reduction of post-training trial times as a result of the enhanced training setup, without any loss in performance or in user experience. Such finding allows the identification of further improvements and novel potential applications of this training and interaction paradigm.