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Wang W, Shi B, Wang D, Wang J, Liu G. Enhanced lower-limb motor imagery by kinesthetic illusion. Front Neurosci 2023; 17:1077479. [PMID: 37409102 PMCID: PMC10319417 DOI: 10.3389/fnins.2023.1077479] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/23/2022] [Accepted: 05/30/2023] [Indexed: 07/07/2023] Open
Abstract
Brain-computer interface (BCI) based on lower-limb motor imagery (LMI) enables hemiplegic patients to stand and walk independently. However, LMI ability is usually poor for BCI-illiterate (e.g., some stroke patients), limiting BCI performance. This study proposed a novel LMI-BCI paradigm with kinesthetic illusion(KI) induced by vibratory stimulation on Achilles tendon to enhance LMI ability. Sixteen healthy subjects were recruited to carry out two research contents: (1) To verify the feasibility of induced KI by vibrating Achilles tendon and analyze the EEG features produced by KI, research 1 compared the subjective feeling and brain activity of participants during rest task with and without vibratory stimulation (V-rest, rest). (2) Research 2 compared the LMI-BCI performance with and without KI (KI-LMI, no-LMI) to explore whether KI enhances LMI ability. The analysis methods of both experiments included classification accuracy (V-rest vs. rest, no-LMI vs. rest, KI-LMI vs. rest, KI-LMI vs. V-rest), time-domain features, oral questionnaire, statistic analysis and brain functional connectivity analysis. Research 1 verified that induced KI by vibrating Achilles tendon might be feasible, and provided a theoretical basis for applying KI to LMI-BCI paradigm, evidenced by oral questionnaire (Q1) and the independent effect of vibratory stimulation during rest task. The results of research 2 that KI enhanced mesial cortex activation and induced more intensive EEG features, evidenced by ERD power, topographical distribution, oral questionnaire (Q2 and Q3), and brain functional connectivity map. Additionally, the KI increased the offline accuracy of no-LMI/rest task by 6.88 to 82.19% (p < 0.001). The simulated online accuracy was also improved for most subjects (average accuracy for all subjects: 77.23% > 75.31%, and average F1_score for all subjects: 76.4% > 74.3%). The LMI-BCI paradigm of this study provides a novel approach to enhance LMI ability and accelerates the practical applications of the LMI-BCI system.
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Affiliation(s)
- Weizhen Wang
- Institute of Robotics and Intelligent Systems, School of Mechanical Engineering, Xi’an Jiaotong University, Xi’an, China
| | - Bin Shi
- Institute of Robotics and Intelligent Systems, School of Mechanical Engineering, Xi’an Jiaotong University, Xi’an, China
| | - Dong Wang
- Institute of Robotics and Intelligent Systems, School of Mechanical Engineering, Xi’an Jiaotong University, Xi’an, China
| | - Jing Wang
- Institute of Robotics and Intelligent Systems, School of Mechanical Engineering, Xi’an Jiaotong University, Xi’an, China
| | - Gang Liu
- Henan Key Laboratory of Brain Science and Brain-Computer Interface Technology, School of Electrical Engineering, Zhengzhou University, Zhengzhou, China
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Won K, Kim H, Gwon D, Ahn M, Nam CS, Jun SC. Can vibrotactile stimulation and tDCS help inefficient BCI users? J Neuroeng Rehabil 2023; 20:60. [PMID: 37143057 PMCID: PMC10157902 DOI: 10.1186/s12984-023-01181-0] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/12/2022] [Accepted: 04/19/2023] [Indexed: 05/06/2023] Open
Abstract
Brain-computer interface (BCI) has helped people by allowing them to control a computer or machine through brain activity without actual body movement. Despite this advantage, BCI cannot be used widely because some people cannot achieve controllable performance. To solve this problem, researchers have proposed stimulation methods to modulate relevant brain activity to improve BCI performance. However, multiple studies have reported mixed results following stimulation, and the comparative study of different stimulation modalities has been overlooked. Accordingly, this study was designed to compare vibrotactile stimulation and transcranial direct current stimulation's (tDCS) effects on brain activity modulation and motor imagery BCI performance among inefficient BCI users. We recruited 44 subjects and divided them into sham, vibrotactile stimulation, and tDCS groups, and low performers were selected from each stimulation group. We found that the latter's BCI performance in the vibrotactile stimulation group increased significantly by 9.13% (p < 0.01), and while the tDCS group subjects' performance increased by 5.13%, it was not significant. In contrast, sham group subjects showed no increased performance. In addition to BCI performance, pre-stimulus alpha band power and the phase locking values (PLVs) averaged over sensory motor areas showed significant increases in low performers following stimulation in the vibrotactile stimulation and tDCS groups, while sham stimulation group subjects and high performers showed no significant stimulation effects across all groups. Our findings suggest that stimulation effects may differ depending upon BCI efficiency, and inefficient BCI users have greater plasticity than efficient BCI users.
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Affiliation(s)
- Kyungho Won
- School of Electrical Engineering and Computer Science, Gwangju Institute of Science and Technology, Gwangju, South Korea
| | - Heegyu Kim
- School of Electrical Engineering and Computer Science, Gwangju Institute of Science and Technology, Gwangju, South Korea
| | - Daeun Gwon
- Department of Computer Science and Electrical Engineering, Handong Global University, Pohang, South Korea
| | - Minkyu Ahn
- Department of Computer Science and Electrical Engineering, Handong Global University, Pohang, South Korea
- School of Computer Science and Electrical Engineering, Handong Global University, Pohang, South Korea
| | - Chang S Nam
- Edward P. Fitts Department of Industrial and Systems Engineering, North Carolina State University, North Carolina, USA
| | - Sung Chan Jun
- School of Electrical Engineering and Computer Science, Gwangju Institute of Science and Technology, Gwangju, South Korea.
- Artificial Intelligence Graduate School, Gwangju Institute of Science and Technology, Gwangju, South Korea.
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Wang L, Li X, Zheng W, Chen X, Chen Q, Hu Y, Cao L, Ren J, Qin W, Lu J, Chen N. Motor imagery evokes strengthened activation in sensorimotor areas and its effective connectivity related to cognitive regions in patients with complete spinal cord injury. Brain Imaging Behav 2022; 16:2049-2060. [PMID: 35994188 DOI: 10.1007/s11682-022-00675-0] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Accepted: 04/05/2022] [Indexed: 11/28/2022]
Abstract
The objective of this study was to investigate the alterations of brain activation and effective connectivity during motor imagery (MI) in complete spinal cord injury (CSCI) patients and to reveal a potential mechanism of MI in motor rehabilitation of CSCI patients. Fifteen CSCI patients and twenty healthy controls underwent the MI task-related fMRI scan, and the motor execution (ME) task only for healthy controls. The brain activation patterns of the two groups during MI, and CSCI patients during the MI task and healthy controls during the ME task were compared. Then the significantly changed brain activation areas in CSCI patients during the MI task were used as regions of interest for effective connectivity analysis, using a voxel-wise granger causality analysis (GCA) method. Compared with healthy controls, increased activations in left primary sensorimotor cortex and bilateral cerebellar lobules IV-VI were detected in CSCI patients during the MI task, and the activation level of these areas even equaled that of healthy controls during the ME task. Furthermore, GCA revealed decreased effective connectivity from sensorimotor related areas (primary sensorimotor cortex and cerebellar lobules IV-VI) to cognitive related areas (prefrontal cortex, precuneus, middle temporal gyrus, and inferior temporal gyrus) in CSCI patients. Our findings demonstrated that motor related brain areas can be functionally preserved and activated through MI after CSCI, it maybe the potential mechanism of MI in the motor rehabilitation of CSCI patients. In addition, Sensorimotor related brain regions have less influence on the cognitive related regions in CSCI patients during MI (The trial registration number: ChiCTR2000032793).
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Affiliation(s)
- Ling Wang
- Department of Radiology, Xuanwu Hospital, Capital Medical University, Beijing, 100053, China.,Beijing Key Laboratory of Magnetic Resonance Imaging and Brain Informatics, Beijing, 100053, China
| | - Xuejing Li
- Department of Radiology, Xuanwu Hospital, Capital Medical University, Beijing, 100053, China.,Department of Radiology, China Rehabilitation Research Center, Beijing, 100068, China
| | - Weimin Zheng
- Department of Radiology, Xuanwu Hospital, Capital Medical University, Beijing, 100053, China.,Beijing Key Laboratory of Magnetic Resonance Imaging and Brain Informatics, Beijing, 100053, China
| | - Xin Chen
- Department of Radiology, Xuanwu Hospital, Capital Medical University, Beijing, 100053, China.,Beijing Key Laboratory of Magnetic Resonance Imaging and Brain Informatics, Beijing, 100053, China
| | - Qian Chen
- Department of Radiology, Beijing Friendship Hospital, Capital Medical University, Beijing, 100050, China
| | - Yongsheng Hu
- Department of Functional Neurosurgery, Xuanwu Hospital, Capital Medical University, Beijing, 100053, China
| | - Lei Cao
- Department of Rehabilitation Medicine, Xuanwu Hospital, Capital Medical University, Beijing, 100053, China
| | - Jian Ren
- Department of Neurosurgery, Xuanwu Hospital, Capital Medical University, Beijing, 100053, China
| | - Wen Qin
- Department of Radiology, Tianjin Medical University General Hospital, Tianjin, 300052, China
| | - Jie Lu
- Department of Radiology, Xuanwu Hospital, Capital Medical University, Beijing, 100053, China.,Beijing Key Laboratory of Magnetic Resonance Imaging and Brain Informatics, Beijing, 100053, China
| | - Nan Chen
- Department of Radiology, Xuanwu Hospital, Capital Medical University, Beijing, 100053, China. .,Beijing Key Laboratory of Magnetic Resonance Imaging and Brain Informatics, Beijing, 100053, China.
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Chen L, Zhang L, Wang Z, Gu B, Zhang X, Ming D. The Effects of Sensory Threshold Somatosensory Electrical Stimulation on Users With Different MI-BCI Performance. Front Neurosci 2022; 16:909434. [PMID: 35784856 PMCID: PMC9247255 DOI: 10.3389/fnins.2022.909434] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/31/2022] [Accepted: 05/23/2022] [Indexed: 11/13/2022] Open
Abstract
Motor imagery-based brain-computer interface (MI-BCI) has been largely studied to improve motor learning and promote motor recovery. However, the difficulty in performing MI limits the widespread application of MI-BCI. It has been suggested that the usage of sensory threshold somatosensory electrical stimulation (st-SES) is a promising way to guide participants on MI tasks, but it is still unclear whether st-SES is effective for all users. In the present study, we aimed to examine the effects of st-SES on the MI-BCI performance in two BCI groups (High Performers and Low Performers). Twenty healthy participants were recruited to perform MI and resting tasks with EEG recordings. These tasks were modulated with or without st-SES. We demonstrated that st-SES improved the performance of MI-BCI in the Low Performers, but led to a decrease in the accuracy of MI-BCI in the High Performers. Furthermore, for the Low Performers, the combination of st-SES and MI resulted in significantly greater event-related desynchronization (ERD) and sample entropy of sensorimotor rhythm than MI alone. However, the ERD and sample entropy values of MI did not change significantly during the st-SES intervention in the High Performers. Moreover, we found that st-SES had an effect on the functional connectivity of the fronto-parietal network in the alpha band of Low Performers and the beta band of High Performers, respectively. Our results demonstrated that somatosensory input based on st-SES was only beneficial for sensorimotor cortical activation and MI-BCI performance in the Low Performers, but not in the High Performers. These findings help to optimize guidance strategies to adapt to different categories of users in the practical application of MI-BCI.
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Affiliation(s)
- Long Chen
- Department of Biomedical Engineering, Academy of Medical Engineering and Translational Medicine, Tianjin University, Tianjin, China
| | - Lei Zhang
- Department of Biomedical Engineering, Academy of Medical Engineering and Translational Medicine, Tianjin University, Tianjin, China
| | - Zhongpeng Wang
- Department of Biomedical Engineering, College of Precision Instruments & Optoelectronics Engineering, Tianjin University, Tianjin, China
| | - Bin Gu
- Department of Biomedical Engineering, College of Precision Instruments & Optoelectronics Engineering, Tianjin University, Tianjin, China
| | - Xin Zhang
- Department of Biomedical Engineering, College of Precision Instruments & Optoelectronics Engineering, Tianjin University, Tianjin, China
| | - Dong Ming
- Department of Biomedical Engineering, Academy of Medical Engineering and Translational Medicine, Tianjin University, Tianjin, China
- Department of Biomedical Engineering, College of Precision Instruments & Optoelectronics Engineering, Tianjin University, Tianjin, China
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Geng Y, Qin L, Li Y, Yu Z, Li L, Asogbon MG, Zhan Y, Yan N, Guo X, Li G. Identifying Oscillations under Multi-site Sensory Stimulation for High-level Peripheral Nerve Injured Patients:A Pilot Study. J Neural Eng 2022; 19. [PMID: 35580572 DOI: 10.1088/1741-2552/ac7079] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/19/2021] [Accepted: 05/17/2022] [Indexed: 11/11/2022]
Abstract
OBJECTIVE For high-level peripheral nerve injured (PNI) patients with severe sensory dysfunction of upper extremities, identifying the multi-site tactile stimulation is of great importance to provide neurorehabilitation with sensory feedback. In this pilot study, we showed the feasibility of identifying multi-site and multi-intensity tactile stimulation in terms of electroencephalography (EEG). APPROACH Three high-level PNI patients and eight non-PNI participants were recruited in this study. Four different sites over the upper arm, forearm, thumb finger and little finger were randomly stimulated at two intensities (both sensory-level) based on the transcutaneous electrical nerve stimulation (TENS). Meanwhile, 64-channel EEG signals were recorded during the passive tactile sense stimulation on each side. MAIN RESULTS The spatial-spectral distribution of brain oscillations underlying multi-site sensory stimulation showed dominant power attenuation over the somatosensory and prefrontal cortices in both alpha-band (8-12 Hz) and beta-band (13-30 Hz). But there was no significant difference among different stimulation sites in terms of the averaged power spectral density over the region of interest (ROI). By further identifying different stimulation sites using temporal-spectral features, we found the classification accuracies were all above 89% for the affected arm of PNI patients, comparable to that from their intact side and that from the non-PNI group. When the stimulation site-intensity combinations were treated as eight separate classes, the classification accuracies were ranging from 88.89% to 99.30% for the affected side of PNI subjects, similar to that from their non-affected side and that from the non-PNI group. Other performance metrics, including Specificity, Precision, and F1-Score, also showed a sound identification performance for both PNI patients and non-PNI subjects. SIGNIFICANCE These results suggest that reliable brain oscillations could be evoked and identified well, even though induced tactile sense could not be discerned by the PNI patients. This study have implication for facilitating bidirectional neurorehabilitation systems with sensory feedback.
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Affiliation(s)
- Yanjuan Geng
- Shenzhen Institutes of Advanced Technology Chinese Academy of Sciences, 1068 Xueyuan Boulevard, University Town of Shenzhen, Xili Nanshan, Shenzhen 518055, China, Shenzhen, Guangdong, 518055, CHINA
| | - Liuni Qin
- Shenzhen Institutes of Advanced Technology Chinese Academy of Sciences, 1068 Xueyuan Boulevard, University Town of Shenzhen, Xili Nanshan, Shenzhen 518055, China, Shenzhen, Guangdong, 518055, CHINA
| | - Yongcheng Li
- Shenzhen Institutes of Advanced Technology Chinese Academy of Sciences, 1068 Xueyuan Boulevard, University Town of Shenzhen, Xili Nanshan, Shenzhen 518055, China, Shenzhen, Guangdong, 518055, CHINA
| | - Zhebin Yu
- Shenzhen Institutes of Advanced Technology Chinese Academy of Sciences, 1068 Xueyuan Boulevard, University Town of Shenzhen, Xili Nanshan, Shenzhen 518055, China, Shenzhen, Guangdong, 518055, CHINA
| | - Linling Li
- Shenzhen University, 1066 Xueyuan Boulevard, University Town of Shenzhen, Xili Nanshan, Shenzhen 518055, China, Shenzhen, 518060, CHINA
| | - Mojisola Grace Asogbon
- Shenzhen Institutes of Advanced Technology, 1068 Xueyuan Boulevard, University Town of Shenzhen, Xili Nanshan, Shenzhen 518055, China, Shenzhen, Guangdong, 518055, CHINA
| | - Yang Zhan
- Shenzhen Institutes of Advanced Technology Chinese Academy of Sciences, 1068 Xueyuan Boulevard, University Town of Shenzhen, Xili Nanshan, Shenzhen 518055, China, Shenzhen, Guangdong, 518055, CHINA
| | - Nan Yan
- Shenzhen Institutes of Advanced Technology Chinese Academy of Sciences, 1068 Xueyuan Boulevard, University Town of Shenzhen, Xili Nanshan, Shenzhen 518055, China, Shenzhen, Guangdong, 518055, CHINA
| | - Xin Guo
- Hebei University of Technology, Hebei University of Technology, Tianjin 300130, China, Tianjin, Tianjin, 300401, CHINA
| | - Guanglin Li
- Shenzhen Institutes of Advanced Technology Chinese Academy of Sciences, 1068 Xueyuan Boulevard, University Town of Shenzhen, Xili Nanshan, Shenzhen 518055, China, Shenzhen, Guangdong, 518055, CHINA
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