This project concerns the use of a neural interface for the command and control of automatic devices. In particular, the objective of the research, currently underway, is to outline the horizon by identifying the technical solutions and algorithms available on the market or in mature scientific literature suitable for industrial applications. Through the neural interface it will be possible to extend the range of use of driving simulators not only for the motorsport sector but also for autonomous driving and for the functional rehabilitation of patients recovering from injuries. The experience of using the neural interface in the simulation system will provide the operational frame for developing the use of this technology in the industrial field, both for the support of HMI platforms controlling and monitoring the production plants and for platforms of augmented reality. The use of an OPENBCI EEG Electrode Cap type helmet with 16 channels will allow the analysis of the subject’s neural electromagnetic impulses that will be interpreted by the openBCI software connected to the cyton board and daisy module and analyzed directly in Matlab / Simulink by means of tools like BCIlab.
Requirement: Dedicated hardware, man-machine interface on a neural basis, advanced robotics, biomechanics
Partner: University of Pavia – ApiTech
Milestones: started in 2019, in progress