Designing a brain computer interface for control of an assistive robotic manipulator using steady state visually evoked potentials

Research output: Contribution to book/anthology/report/conference proceedingArticle in proceedingResearchpeer-review

Abstract

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.
Original languageEnglish
Title of host publicationInternational Conference on Rehabilitation Robotics
Number of pages6
PublisherIEEE
Publication date1 Apr 2019
Pages1-6
Publication statusAccepted/In press - 1 Apr 2019

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Brain computer interface
Bioelectric potentials
Manipulators
Robotics
Flickering
Degrees of freedom (mechanics)
Testing
Experiments

Cite this

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title = "Designing a brain computer interface for control of an assistive robotic manipulator using steady state visually evoked potentials",
abstract = "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.",
author = "K{\ae}seler, {Rasmus Leck} and Mads Jochumsen and Kasper Leerskov and Struijk, {Lotte N. S. Andreasen} and Kim Dremstrup",
year = "2019",
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booktitle = "International Conference on Rehabilitation Robotics",
publisher = "IEEE",
address = "United States",

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Designing a brain computer interface for control of an assistive robotic manipulator using steady state visually evoked potentials. / Kæseler, Rasmus Leck; Jochumsen, Mads; Leerskov, Kasper; Struijk, Lotte N. S. Andreasen; Dremstrup, Kim.

International Conference on Rehabilitation Robotics. IEEE, 2019. p. 1-6.

Research output: Contribution to book/anthology/report/conference proceedingArticle in proceedingResearchpeer-review

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