An assistive robotic manipulator (ARM) can provide independence and improve the quality of life for patients suffering from tetraplegia. However, to properly control such device to a satisfactory level without any motor functions requires a very high performing brain-computer interface (BCI). Steady-state visual evoked potentials (SSVEP) based BCI are among the best performing. Thus, this study investigates the design of a system for a full workspace control of a 7 degrees of freedom ARM. A SSVEP signal is elicited by observing a visual stimulus flickering at a specific frequency and phase. This study investigates the best combination of unique frequencies and phases to provide a 16-target BCI by testing three different systems offline. Furthermore, a fourth system is developed to investigate the impact of the stimulating monitor refresh rate. Experiments conducted on two subjects suggest that a 16-target BCI created by four unique frequencies and 16-unique phases provide the best performance. Subject 1 reaches a maximum estimated ITR of 235 bits/min while subject 2 reaches 140 bits/min. The findings suggest that the optimal SSVEP stimuli to generate 16 targets are a low number of frequencies and a high number of unique phases. Moreover, the findings do not suggest any need for considering the monitor refresh rate if stimuli are modulated using a sinusoidal signal sampled at the refresh rate.
Designing a brain computer interface for control of an assistive robotic manipulator using steady state visually evoked potentials
2019-07-01
Kæseler , R L , Jochumsen , M , Leerskov , K , Struijk , L N S A & Dremstrup , K 2019 , Designing a brain computer interface for control of an assistive robotic manipulator using steady state visually evoked potentials . in 2019 IEEE 16th International Conference on Rehabilitation Robotics, ICORR 2019 . , 8779376 , IEEE , I E E E International Conference on Rehabilitation Robotics. Proceedings , pp. 1067-1072 , International Conference on Rehabilitation Robotics 2019 (ICORR 2019) , Toronto , Canada , 24/06/2019 . https://doi.org/10.1109/ICORR.2019.8779376
Aufsatz (Zeitschrift)
Elektronische Ressource
Englisch
DDC: | 629 |
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