@article{Shi2020, 
author = {Nanlin Shi and Liping Wang and Yonghao Chen and Xinyi Yan and Chen Yang and Yijun Wang and Xiaorong Gao},
title = {Steady-state visual evoked potential (SSVEP)-based brain–computer interface (BCI) of Chinese speller for a patient with amyotrophic lateral sclerosis: A case report},
year = {2020},
journal = {Journal of Neurorestoratology},
volume = {8},
number = {1},
pages = {40-52},
keywords = {steady-state visual evoked potential (SSVEP), amyotrophic lateral sclerosis (ALS), brain–computer interface (BCI)},
url = {https://www.sciopen.com/article/10.26599/JNR.2020.9040003},
doi = {10.26599/JNR.2020.9040003},
abstract = {This study applied a steady-state visual evoked potential (SSVEP) based brain–computer interface (BCI) to a patient in lock-in state with amyotrophic lateral sclerosis (ALS) and validated its feasibility for communication. The developed calibration-free and asynchronous spelling system provided a natural and efficient communication experience for the patient, achieving a maximum free-spelling accuracy above 90% and an information transfer rate of over 22.203 bits/min. A set of standard frequency scanning and task spelling data were also acquired to evaluate the patient’s SSVEP response and to facilitate further personalized BCI design. The results demonstrated that the proposed SSVEP-based BCI system was practical and efficient enough to provide daily life communication for ALS patients.}
}