Volume 54, Issue 3 pp. 444-451
Original Article

Clinical feasibility of brain-computer interface based on steady-state visual evoked potential in patients with locked-in syndrome: Case studies

Han-Jeong Hwang

Han-Jeong Hwang

Department of Biomedical Engineering, Hanyang University, Seoul, Korea

Department of Medical IT Convergence Engineering, Kumoh National Institute of Technology, Gumi, Korea

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Chang-Hee Han

Chang-Hee Han

Department of Biomedical Engineering, Hanyang University, Seoul, Korea

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Jeong-Hwan Lim

Jeong-Hwan Lim

Department of Biomedical Engineering, Hanyang University, Seoul, Korea

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Yong-Wook Kim

Yong-Wook Kim

Department of Biomedical Engineering, Hanyang University, Seoul, Korea

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Soo-In Choi

Soo-In Choi

Department of Medical IT Convergence Engineering, Kumoh National Institute of Technology, Gumi, Korea

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Kwang-Ok An

Kwang-Ok An

Department of Rehabilitative Assistive Technology, National Rehabilitation Center, Seoul, Korea

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Jun-Hak Lee

Jun-Hak Lee

Department of Biomedical Engineering, Hanyang University, Seoul, Korea

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Ho-Seung Cha

Ho-Seung Cha

Department of Biomedical Engineering, Hanyang University, Seoul, Korea

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Seung Hyun Kim

Seung Hyun Kim

Department of Neurology, Hanyang University, Seoul, Korea

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Chang-Hwan Im

Corresponding Author

Chang-Hwan Im

Department of Biomedical Engineering, Hanyang University, Seoul, Korea

Address correspondence to: Chang-Hwan Im, Ph.D., Department of Biomedical Engineering, Hanyang University, 222 Wangsimni-ro, Seongdong-gu, Seoul, 04763, Republic of Korea. E-mail: [email protected]Search for more papers by this author
First published: 03 December 2016
Citations: 32

This work was supported by the National Research Foundation of Korea (NRF) grants funded by the Korea Government (MSIP) (No. 2015R1A 2A1A15054662 & 2014R1A2A1A11051796).

Abstract

Although the feasibility of brain-computer interface (BCI) systems based on steady-state visual evoked potential (SSVEP) has been extensively investigated, only a few studies have evaluated its clinical feasibility in patients with locked-in syndrome (LIS), who are the main targets of BCI technology. The main objective of this case report was to share our experiences of SSVEP-based BCI experiments involving five patients with LIS, thereby providing researchers with useful information that can potentially help them to design BCI experiments for patients with LIS. In our experiments, a four-class online SSVEP-based BCI system was implemented and applied to four of five patients repeatedly on multiple days to investigate its test-retest reliability. In the last experiments with two of the four patients, the practical usability of our BCI system was tested using a questionnaire survey. All five patients showed clear and distinct SSVEP responses at all four fundamental stimulation frequencies (6, 6.66, 7.5, 10 Hz), and responses at harmonic frequencies were also observed in three patients. Mean classification accuracy was 76.99% (chance level = 25%). The test-retest reliability experiments demonstrated stable performance of our BCI system over different days even when the initial experimental settings (e.g., electrode configuration, fixation time, visual angle) used in the first experiment were used without significant modifications. Our results suggest that SSVEP-based BCI paradigms might be successfully used to implement clinically feasible BCI systems for severely paralyzed patients.

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