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Hualiang L, Xupeng Y, Yuzhong L, Tingjun X, Wei T, Yali S, Qiru W, Chaolin X, Yu W, Weilin L, Long J. A novel noninvasive brain-computer interface by imagining isometric force levels. Cogn Neurodyn 2023; 17:975-983. [PMID: 37522042 PMCID: PMC10374494 DOI: 10.1007/s11571-022-09875-2] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/27/2022] [Revised: 07/22/2022] [Accepted: 08/19/2022] [Indexed: 11/03/2022] Open
Abstract
Physiological circuits differ across increasing isometric force levels during unilateral contraction. Therefore, we first explored the possibility of predicting the force level based on electroencephalogram (EEG) activity recorded during a single trial of unilateral 5% or 40% of maximal isometric voluntary contraction (MVC) in right-hand grip imagination. Nine healthy subjects were involved in this study. The subjects were required to randomly perform 20 trials for each force level while imagining a right-hand grip. We proposed the use of common spatial patterns (CSPs) and coherence between EEG signals as features in a support vector machine for force level prediction. The results showed that the force levels could be predicted through single-trial EEGs while imagining the grip (mean accuracy = 81.4 ± 13.29%). Additionally, we tested the possibility of online control of a ball game using the above paradigm through unilateral grip imagination at different force levels (i.e., 5% of MVC imagination and 40% of MVC imagination for right-hand movement control). Subjects played the ball games effectively by controlling direction with our novel BCI system (n = 9, mean accuracy = 76.67 ± 9.35%). Data analysis validated the use of our BCI system in the online control of a ball game. This information may provide additional commands for the control of robots by users through combinations with other traditional brain-computer interfaces, e.g., different limb imaginations.
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Affiliation(s)
- Li Hualiang
- Key Laboratory of Occupational Health and Safety of Guangdong Power Grid Co., Ltd., Guangzhou, Guangdong China
- Electric Power Research Institute of Guangdong Power Grid Co., Ltd., Guangzhou, Guangdong China
| | - Ye Xupeng
- College of Information Science and Technology, and Guangdong Key Lab of Traditional Chinese Medicine Information Technology, Jinan University, Guangzhou, 510632 China
| | - Liu Yuzhong
- Key Laboratory of Occupational Health and Safety of Guangdong Power Grid Co., Ltd., Guangzhou, Guangdong China
- Electric Power Research Institute of Guangdong Power Grid Co., Ltd., Guangzhou, Guangdong China
| | - Xie Tingjun
- Guangdong Power Grid Co., Ltd., Guangzhou, China
| | - Tan Wei
- Guangdong Power Grid Co., Ltd., Guangzhou, China
| | - Shen Yali
- Key Laboratory of Occupational Health and Safety of Guangdong Power Grid Co., Ltd., Guangzhou, Guangdong China
- Electric Power Research Institute of Guangdong Power Grid Co., Ltd., Guangzhou, Guangdong China
| | - Wang Qiru
- Key Laboratory of Occupational Health and Safety of Guangdong Power Grid Co., Ltd., Guangzhou, Guangdong China
- Electric Power Research Institute of Guangdong Power Grid Co., Ltd., Guangzhou, Guangdong China
| | - Xiong Chaolin
- Key Laboratory of Occupational Health and Safety of Guangdong Power Grid Co., Ltd., Guangzhou, Guangdong China
- Electric Power Research Institute of Guangdong Power Grid Co., Ltd., Guangzhou, Guangdong China
| | - Wang Yu
- Key Laboratory of Occupational Health and Safety of Guangdong Power Grid Co., Ltd., Guangzhou, Guangdong China
- Electric Power Research Institute of Guangdong Power Grid Co., Ltd., Guangzhou, Guangdong China
| | - Lin Weilin
- College of Information Science and Technology, and Guangdong Key Lab of Traditional Chinese Medicine Information Technology, Jinan University, Guangzhou, 510632 China
| | - Jinyi Long
- College of Information Science and Technology, and Guangdong Key Lab of Traditional Chinese Medicine Information Technology, Jinan University, Guangzhou, 510632 China
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Guang Y, Yuzhong L, Hui L. Statistical and Experimental Evidence in a Design of Pooled Serum Sample Measurements to Improve Research Efficiency. Indian J Pharm Sci 2020. [DOI: 10.36468/pharmaceutical-sciences.spl.54] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/22/2022] Open
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