Brain-computer interface (BCI) for robotic arm control has been studied to improve the life quality of people with severe motor disabilities.There are still challenges for robotic arm control in accomplishing a complex task with a series of actions.An efficient switch and a timely cancel command are helpful in the application of robotic arm.Based on the above, we proposed an asynchronous hybrid BCI in this study.
The basic control of a robotic arm with six degrees of freedom was a steady-state visual evoked potential (SSVEP) based BCI with fifteen target classes.We designed an EOG-based switch which used a triple blink to either activate or deactivate the flash of SSVEP-based Spatulas BCI.Stopping flash in the idle state can help to reduce visual fatigue and false activation rate (FAR).Additionally, users were allowed to cancel the current command simply by a wink in the feedback phase to avoid executing the incorrect command.
Fifteen subjects participated and completed the experiments.The cue-based Triathlon - Femme - Vetements - Singlet experiment obtained an average accuracy of 92.09%, and the information transfer rates (ITR) resulted in 35.98 bits/min.
The mean FAR of the switch was 0.01/min.Furthermore, all subjects succeeded in asynchronously operating the robotic arm to grasp, lift, and move a target object from the initial position to a specific location.The results indicated the feasibility of the combination of EOG and SSVEP signals and the flexibility of EOG signal in BCI to complete a complicated task of robotic arm control.