Decoding the EEG patterns induced by sequential finger movement for brain-computer interfaces

Frontiers in Neuroscience

Neuroscience

Chang Liu¹  Yining Huang¹  Kun Wang¹  Dong Ming²  Minpeng Xu³  Jia You⁴  Shanshan Zhang⁴ 

[1] Academy of Medical Engineering and Translational Medicine, Tianjin University, Tianjin, China;Academy of Medical Engineering and Translational Medicine, Tianjin University, Tianjin, China;School of Precision Instruments and Optoelectronics Engineering, Tianjin University, Tianjin, China;Academy of Medical Engineering and Translational Medicine, Tianjin University, Tianjin, China;School of Precision Instruments and Optoelectronics Engineering, Tianjin University, Tianjin, China;International School for Optoelectronic Engineering, Qilu University of Technology (Shandong Academy of Sciences), Jinan, China;School of Precision Instruments and Optoelectronics Engineering, Tianjin University, Tianjin, China;

关键词: electroencephalography;    sequential finger movements;    movement related cortical potentials;    event-related desynchronization;    brain-computer interface;   

DOI  :  10.3389/fnins.2023.1180471

 received in 2023-03-06, accepted in 2023-07-26,  发布年份 2023

来源: Frontiers

【 摘 要 】

ObjectiveIn recent years, motor imagery-based brain–computer interfaces (MI-BCIs) have developed rapidly due to their great potential in neurological rehabilitation. However, the controllable instruction set limits its application in daily life. To extend the instruction set, we proposed a novel movement-intention encoding paradigm based on sequential finger movement.ApproachTen subjects participated in the offline experiment. During the experiment, they were required to press a key sequentially [i.e., Left→Left (LL), Right→Right (RR), Left→Right (LR), and Right→Left (RL)] using the left or right index finger at about 1 s intervals under an auditory prompt of 1 Hz. The movement-related cortical potential (MRCP) and event-related desynchronization (ERD) features were used to investigate the electroencephalography (EEG) variation induced by the sequential finger movement tasks. Twelve subjects participated in an online experiment to verify the feasibility of the proposed paradigm.Main resultsAs a result, both the MRCP and ERD features showed the specific temporal–spatial EEG patterns of different sequential finger movement tasks. For the offline experiment, the average classification accuracy of the four tasks was 71.69%, with the highest accuracy of 79.26%. For the online experiment, the average accuracies were 83.33% and 82.71% for LL-versus-RR and LR-versus-RL, respectively.SignificanceThis paper demonstrated the feasibility of the proposed sequential finger movement paradigm through offline and online experiments. This study would be helpful for optimizing the encoding method of motor-related EEG information and providing a promising approach to extending the instruction set of the movement intention-based BCIs.

【 授权许可】

Unknown   
Copyright © 2023 Liu, You, Wang, Zhang, Huang, Xu and Ming.