Continuous 2-D control via state-machine triggered by endogenous sensory discrimination and a fast brain switch

Ren Xu, Strahinja Dosen, Ning Jiang, Lin Yao, Asma Farooq, Mads Jochumsen, Natalie Mrachacz-Kersting, Kim Dremstrup, Dario Farina

Research output: Contribution to journalJournal articleResearchpeer-review

Abstract

Objective. Brain computer interfacing (BCI) is a promising method to control assistive systems for patients with severe disabilities. However, only a small number of commands (2 to 3) can be discriminated from EEG signals. Recently, we have presented a novel BCI approach that combines an electrotactile menu and a brain switch, which allows the user to trigger many commands robustly and efficiently. However, the commands are timed to periodic tactile cues and this may challenge online control. In the present study, therefore, we implemented and evaluated a novel approach for online closed-loop control using the proposed BCI. Approach. Seven healthy subjects used the novel method to move a cursor in a 2D space. To assure robust control with properly timed commands, the BCI was integrated within a state machine allowing the subject to start the cursor movement in the selected direction and asynchronously stop the cursor. The brain switch was controlled using motor execution (ME) or imagery (MI) and the menu implemented 4 (straight movements) or 8 commands (straight and diagonal movements). Main results. The results showed a high completion rate of a target hitting task (~95% and ~88% for ME and MI, respectively), with a small number of collisions, when 4-channel control was used. There was no significant difference in outcome measures between MI and ME, and performance was similar for 4 and 8 commands. Significance. These results demonstrate that the novel state-based scheme driven by a robust BCI can be successfully utilized for online control. Therefore, it can be an attractive solution for providing the user an online-control interface with many commands, which is difficult to achieve using classic BCI solutions.
Original languageEnglish
JournalJournal of Neural Engineering
ISSN1741-2552
DOIs
Publication statusAccepted/In press - 10 May 2019

Cite this

@article{128592b9393f490ea443e17ad07dc394,
title = "Continuous 2-D control via state-machine triggered by endogenous sensory discrimination and a fast brain switch",
abstract = "Objective. Brain computer interfacing (BCI) is a promising method to control assistive systems for patients with severe disabilities. However, only a small number of commands (2 to 3) can be discriminated from EEG signals. Recently, we have presented a novel BCI approach that combines an electrotactile menu and a brain switch, which allows the user to trigger many commands robustly and efficiently. However, the commands are timed to periodic tactile cues and this may challenge online control. In the present study, therefore, we implemented and evaluated a novel approach for online closed-loop control using the proposed BCI. Approach. Seven healthy subjects used the novel method to move a cursor in a 2D space. To assure robust control with properly timed commands, the BCI was integrated within a state machine allowing the subject to start the cursor movement in the selected direction and asynchronously stop the cursor. The brain switch was controlled using motor execution (ME) or imagery (MI) and the menu implemented 4 (straight movements) or 8 commands (straight and diagonal movements). Main results. The results showed a high completion rate of a target hitting task (~95{\%} and ~88{\%} for ME and MI, respectively), with a small number of collisions, when 4-channel control was used. There was no significant difference in outcome measures between MI and ME, and performance was similar for 4 and 8 commands. Significance. These results demonstrate that the novel state-based scheme driven by a robust BCI can be successfully utilized for online control. Therefore, it can be an attractive solution for providing the user an online-control interface with many commands, which is difficult to achieve using classic BCI solutions.",
author = "Ren Xu and Strahinja Dosen and Ning Jiang and Lin Yao and Asma Farooq and Mads Jochumsen and Natalie Mrachacz-Kersting and Kim Dremstrup and Dario Farina",
year = "2019",
month = "5",
day = "10",
doi = "10.1088/1741-2552/ab20e5",
language = "English",
journal = "Journal of Neural Engineering",
issn = "1741-2560",
publisher = "IOP Publishing",

}

Continuous 2-D control via state-machine triggered by endogenous sensory discrimination and a fast brain switch. / Xu, Ren; Dosen, Strahinja; Jiang, Ning; Yao, Lin; Farooq, Asma; Jochumsen, Mads; Mrachacz-Kersting, Natalie; Dremstrup, Kim; Farina, Dario.

In: Journal of Neural Engineering, 10.05.2019.

Research output: Contribution to journalJournal articleResearchpeer-review

TY - JOUR

T1 - Continuous 2-D control via state-machine triggered by endogenous sensory discrimination and a fast brain switch

AU - Xu, Ren

AU - Dosen, Strahinja

AU - Jiang, Ning

AU - Yao, Lin

AU - Farooq, Asma

AU - Jochumsen, Mads

AU - Mrachacz-Kersting, Natalie

AU - Dremstrup, Kim

AU - Farina, Dario

PY - 2019/5/10

Y1 - 2019/5/10

N2 - Objective. Brain computer interfacing (BCI) is a promising method to control assistive systems for patients with severe disabilities. However, only a small number of commands (2 to 3) can be discriminated from EEG signals. Recently, we have presented a novel BCI approach that combines an electrotactile menu and a brain switch, which allows the user to trigger many commands robustly and efficiently. However, the commands are timed to periodic tactile cues and this may challenge online control. In the present study, therefore, we implemented and evaluated a novel approach for online closed-loop control using the proposed BCI. Approach. Seven healthy subjects used the novel method to move a cursor in a 2D space. To assure robust control with properly timed commands, the BCI was integrated within a state machine allowing the subject to start the cursor movement in the selected direction and asynchronously stop the cursor. The brain switch was controlled using motor execution (ME) or imagery (MI) and the menu implemented 4 (straight movements) or 8 commands (straight and diagonal movements). Main results. The results showed a high completion rate of a target hitting task (~95% and ~88% for ME and MI, respectively), with a small number of collisions, when 4-channel control was used. There was no significant difference in outcome measures between MI and ME, and performance was similar for 4 and 8 commands. Significance. These results demonstrate that the novel state-based scheme driven by a robust BCI can be successfully utilized for online control. Therefore, it can be an attractive solution for providing the user an online-control interface with many commands, which is difficult to achieve using classic BCI solutions.

AB - Objective. Brain computer interfacing (BCI) is a promising method to control assistive systems for patients with severe disabilities. However, only a small number of commands (2 to 3) can be discriminated from EEG signals. Recently, we have presented a novel BCI approach that combines an electrotactile menu and a brain switch, which allows the user to trigger many commands robustly and efficiently. However, the commands are timed to periodic tactile cues and this may challenge online control. In the present study, therefore, we implemented and evaluated a novel approach for online closed-loop control using the proposed BCI. Approach. Seven healthy subjects used the novel method to move a cursor in a 2D space. To assure robust control with properly timed commands, the BCI was integrated within a state machine allowing the subject to start the cursor movement in the selected direction and asynchronously stop the cursor. The brain switch was controlled using motor execution (ME) or imagery (MI) and the menu implemented 4 (straight movements) or 8 commands (straight and diagonal movements). Main results. The results showed a high completion rate of a target hitting task (~95% and ~88% for ME and MI, respectively), with a small number of collisions, when 4-channel control was used. There was no significant difference in outcome measures between MI and ME, and performance was similar for 4 and 8 commands. Significance. These results demonstrate that the novel state-based scheme driven by a robust BCI can be successfully utilized for online control. Therefore, it can be an attractive solution for providing the user an online-control interface with many commands, which is difficult to achieve using classic BCI solutions.

U2 - 10.1088/1741-2552/ab20e5

DO - 10.1088/1741-2552/ab20e5

M3 - Journal article

JO - Journal of Neural Engineering

JF - Journal of Neural Engineering

SN - 1741-2560

ER -