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Kukkar KK, Rao N, Huynh D, Shah S, Contreras-Vidal JL, Parikh PJ. Context-dependent reduction in corticomuscular coupling for balance control in chronic stroke survivors. Exp Brain Res 2024:10.1007/s00221-024-06884-x. [PMID: 38963559 DOI: 10.1007/s00221-024-06884-x] [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: 07/28/2023] [Accepted: 06/26/2024] [Indexed: 07/05/2024]
Abstract
Balance control is an important indicator of mobility and independence in activities of daily living. How the functional coupling between the cortex and the muscle for balance control is affected following stroke remains to be known. We investigated the changes in coupling between the cortex and leg muscles during a challenging balance task over multiple frequency bands in chronic stroke survivors. Fourteen participants with stroke and ten healthy controls performed a challenging balance task. They stood on a computerized support surface that was either fixed (low difficulty condition) or sway-referenced with varying gain (medium and high difficulty conditions). We computed corticomuscular coherence between electrodes placed over the sensorimotor area (electroencephalography) and leg muscles (electromyography) and assessed balance performance using clinical and laboratory-based tests. We found significantly lower delta frequency band coherence in stroke participants when compared with healthy controls under medium difficulty condition, but not during low and high difficulty conditions. These differences were found for most of the distal but not for proximal leg muscle groups. No differences were found at other frequency bands. Participants with stroke showed poor balance clinical scores when compared with healthy controls, but no differences were found for laboratory-based tests. The observation of effects at distal but not at proximal muscle groups suggests differences in the (re)organization of the descending connections across two muscle groups for balance control. We argue that the observed group difference in delta band coherence indicates balance context-dependent alteration in mechanisms for the detection of somatosensory modulation resulting from sway-referencing of the support surface for balance maintenance following stroke.
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Affiliation(s)
- Komal K Kukkar
- Center for Neuromotor and Biomechanics Research, Department of Health and Human Performance, University of Houston, 3875 Holman Street, suite 104R GAR, Houston, TX, 77204, USA
| | - Nishant Rao
- Yale Child Study Center, Yale University, New Haven, Connecticut, USA
| | - Diana Huynh
- Center for Neuromotor and Biomechanics Research, Department of Health and Human Performance, University of Houston, 3875 Holman Street, suite 104R GAR, Houston, TX, 77204, USA
| | - Sheel Shah
- Center for Neuromotor and Biomechanics Research, Department of Health and Human Performance, University of Houston, 3875 Holman Street, suite 104R GAR, Houston, TX, 77204, USA
| | - Jose L Contreras-Vidal
- Laboratory for Noninvasive Brain-Machine Interface Systems, Department of Electrical and Computer Engineering, University of Houston, Houston, TX, USA
| | - Pranav J Parikh
- Center for Neuromotor and Biomechanics Research, Department of Health and Human Performance, University of Houston, 3875 Holman Street, suite 104R GAR, Houston, TX, 77204, USA.
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Wang T, Xia M, Wang J, Zhilenkov A, Wang J, Xi X, Li L. Delay estimation for cortical-muscular interaction with wavelet coherence time lag. J Neurosci Methods 2024; 405:110098. [PMID: 38423364 DOI: 10.1016/j.jneumeth.2024.110098] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/28/2023] [Revised: 02/09/2024] [Accepted: 02/23/2024] [Indexed: 03/02/2024]
Abstract
BACKGROUND Cortico-muscular coherence (CMC) between the cerebral cortex and muscle activity is an effective tool for studying neural communication in the motor control system. To accurately evaluate the coherence between electroencephalogram (EEG) and electromyogram (EMG) signals, it is necessary to accurately calculate the time delay between physiological signals to ensure signal synchronization. NEW METHOD We proposed a new delay estimation method, named wavelet coherence time lag (WCTL) and the significant increase areas (SIA) index as a measure of the specific region enhancement effect of the magnitude squared coherence (MSC) image. RESULTS The grip strength level had a small effect on the information transmission time from the cortex to the muscles, while the transmission time from the cortex to different muscle channels was different for the same task. A positive correlation was found between the grip strength level and the SIA index on the β band of C3-B and the α and β bands of C3-FDS. COMPARISON WITH EXISTING METHOD The WCTL method was found to accurately calculate the delay time even when the number of repeated segments was low in a simple motor control model, and the results were more accurate than the rate of voxels change (RVC) and CMC with time lag (CMCTL) methods. CONCLUSIONS The WCTL is an effective method for detecting the transmission time of information between the cortex and muscles, laying the foundation for future rehabilitation treatment for stroke patients.
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Affiliation(s)
- Ting Wang
- School of Automation, Hangzhou Dianzi University, Hangzhou 310018, China.
| | - Mingze Xia
- School of Automation, Hangzhou Dianzi University, Hangzhou 310018, China
| | - Junhong Wang
- School of Automation, Hangzhou Dianzi University, Hangzhou 310018, China
| | - Anton Zhilenkov
- Department of Cyber-Physical Systems, St. Petersburg State Marine Technical University, Saint-Petersburg 190121, Russia
| | - Jian Wang
- School of Automation, Hangzhou Dianzi University, Hangzhou 310018, China
| | - Xugang Xi
- School of Automation, Hangzhou Dianzi University, Hangzhou 310018, China
| | - Lihua Li
- School of Automation, Hangzhou Dianzi University, Hangzhou 310018, China
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Zhang J, Wang M, Alam M, Zheng YP, Ye F, Hu X. Effects of non-invasive cervical spinal cord neuromodulation by trans-spinal electrical stimulation on cortico-muscular descending patterns in upper extremity of chronic stroke. Front Bioeng Biotechnol 2024; 12:1372158. [PMID: 38576448 PMCID: PMC10991759 DOI: 10.3389/fbioe.2024.1372158] [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: 01/17/2024] [Accepted: 03/11/2024] [Indexed: 04/06/2024] Open
Abstract
Background: Trans-spinal electrical stimulation (tsES) to the intact spinal cord poststroke may modulate the cortico-muscular control in stroke survivors with diverse lesions in the brain. This work aimed to investigate the immediate effects of tsES on the cortico-muscular descending patterns during voluntary upper extremity (UE) muscle contractions by analyzing cortico-muscular coherence (CMCoh) and electromyography (EMG) in people with chronic stroke. Methods: Twelve chronic stroke participants were recruited to perform wrist-hand extension and flexion tasks at submaximal levels of voluntary contraction for the corresponding agonist flexors and extensors. During the tasks, the tsES was delivered to the cervical spinal cord with rectangular biphasic pulses. Electroencephalography (EEG) data were collected from the sensorimotor cortex, and the EMG data were recorded from both distal and proximal UE muscles. The CMCoh, laterality index (LI) of the peak CMCoh, and EMG activation level parameters under both non-tsES and tsES conditions were compared to evaluate the immediate effects of tsES on the cortico-muscular descending pathway. Results: The CMCoh and LI of peak CMCoh in the agonist distal muscles showed significant increases (p < 0.05) during the wrist-hand extension and flexion tasks with the application of tsES. The EMG activation levels of the antagonist distal muscle during wrist-hand extension were significantly decreased (p < 0.05) with tsES. Additionally, the proximal UE muscles exhibited significant decreases (p < 0.05) in peak CMCoh and EMG activation levels by applying tsES. There was a significant increase (p < 0.05) in LI of peak CMCoh of proximal UE muscles during tsES. Conclusion: The cervical spinal cord neuromodulation via tsES enhanced the residual descending excitatory control, activated the local inhibitory circuits within the spinal cord, and reduced the cortical and proximal muscular compensatory effects. These results suggested the potential of tsES as a supplementary input for improving UE motor functions in stroke rehabilitation.
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Affiliation(s)
- Jianing Zhang
- Department of Biomedical Engineering, The Hong Kong Polytechnic University, Kowloon, China
| | - Maner Wang
- Department of Biomedical Engineering, The Hong Kong Polytechnic University, Kowloon, China
| | - Monzurul Alam
- Department of Biomedical Engineering, The Hong Kong Polytechnic University, Kowloon, China
| | - Yong-Ping Zheng
- Department of Biomedical Engineering, The Hong Kong Polytechnic University, Kowloon, China
| | - Fuqiang Ye
- Department of Biomedical Engineering, The Hong Kong Polytechnic University, Kowloon, China
| | - Xiaoling Hu
- Department of Biomedical Engineering, The Hong Kong Polytechnic University, Kowloon, China
- Research Institute for Smart Ageing (RISA), Hong Kong SAR, China
- Research Centre of Data Science and Artificial Intelligence (RC-DSAI), Hong Kong SAR, China
- Joint Research Centre for Biosensing and Precision Theranostics, Hong Kong SAR, China
- University Research Facility in Behavioral and Systems Neuroscience (UBSN), The Hong Kong Polytechnic University, Hong Kong SAR, China
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Lin L, Qing W, Huang Y, Ye F, Rong W, Li W, Jiao J, Hu X. Comparison of Immediate Neuromodulatory Effects between Focal Vibratory and Electrical Sensory Stimulations after Stroke. Bioengineering (Basel) 2024; 11:286. [PMID: 38534560 DOI: 10.3390/bioengineering11030286] [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: 02/21/2024] [Revised: 03/14/2024] [Accepted: 03/15/2024] [Indexed: 03/28/2024] Open
Abstract
Focal vibratory stimulation (FVS) and neuromuscular electrical stimulation (NMES) are promising technologies for sensory rehabilitation after stroke. However, the differences between these techniques in immediate neuromodulatory effects on the poststroke cortex are not yet fully understood. In this research, cortical responses in persons with chronic stroke (n = 15) and unimpaired controls (n = 15) were measured by whole-brain electroencephalography (EEG) when FVS and NMES at different intensities were applied transcutaneously to the forearm muscles. Both FVS and sensory-level NMES induced alpha and beta oscillations in the sensorimotor cortex after stroke, significantly exceeding baseline levels (p < 0.05). These oscillations exhibited bilateral sensory deficiency, early adaptation, and contralesional compensation compared to the control group. FVS resulted in a significantly faster P300 response (p < 0.05) and higher theta oscillation (p < 0.05) compared to NMES. The beta desynchronization over the contralesional frontal-parietal area remained during NMES (p > 0.05), but it was significantly weakened during FVS (p < 0.05) after stroke. The results indicated that both FVS and NMES effectively activated the sensorimotor cortex after stroke. However, FVS was particularly effective in eliciting transient involuntary attention, while NMES primarily fostered the cortical responses of the targeted muscles in the contralesional motor cortex.
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Affiliation(s)
- Legeng Lin
- Department of Biomedical Engineering, The Hong Kong Polytechnic University, Hong Kong, China
- Research Institute for Smart Ageing (RISA), The Hong Kong Polytechnic University, Hong Kong, China
| | - Wanyi Qing
- Department of Biomedical Engineering, The Hong Kong Polytechnic University, Hong Kong, China
- Research Institute for Smart Ageing (RISA), The Hong Kong Polytechnic University, Hong Kong, China
| | - Yanhuan Huang
- Department of Biomedical Engineering, The Hong Kong Polytechnic University, Hong Kong, China
- Research Institute for Smart Ageing (RISA), The Hong Kong Polytechnic University, Hong Kong, China
| | - Fuqiang Ye
- Department of Biomedical Engineering, The Hong Kong Polytechnic University, Hong Kong, China
- Research Institute for Smart Ageing (RISA), The Hong Kong Polytechnic University, Hong Kong, China
| | - Wei Rong
- Department of Biomedical Engineering, The Hong Kong Polytechnic University, Hong Kong, China
| | - Waiming Li
- Department of Biomedical Engineering, The Hong Kong Polytechnic University, Hong Kong, China
| | - Jiao Jiao
- Department of Sport, Physical Education and Health, Hong Kong Baptist University, Hong Kong, China
| | - Xiaoling Hu
- Department of Biomedical Engineering, The Hong Kong Polytechnic University, Hong Kong, China
- Research Institute for Smart Ageing (RISA), The Hong Kong Polytechnic University, Hong Kong, China
- University Research Facility in Behavioral and Systems Neuroscience (UBSN), The Hong Kong Polytechnic University, Hong Kong, China
- Joint Research Centre for Biosensing and Precision Theranostics, The Hong Kong Polytechnic University, Hong Kong, China
- Research Centre on Data Science and Artificial Intelligence, The Hong Kong Polytechnic University, Hong Kong, China
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Ti CHE, Hu C, Yuan K, Chu WCW, Tong RKY. Uncovering the Neural Mechanisms of Inter-Hemispheric Balance Restoration in Chronic Stroke Through EMG-Driven Robot Hand Training: Insights From Dynamic Causal Modeling. IEEE Trans Neural Syst Rehabil Eng 2024; 32:1-11. [PMID: 38051622 DOI: 10.1109/tnsre.2023.3339756] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/07/2023]
Abstract
EMG-driven robot hand training can facilitate motor recovery in chronic stroke patients by restoring the interhemispheric balance between motor networks. However, the underlying mechanisms of reorganization between interhemispheric regions remain unclear. This study investigated the effective connectivity (EC) between the ventral premotor cortex (PMv), supplementary motor area (SMA), and primary motor cortex (M1) using Dynamic Causal Modeling (DCM) during motor tasks with the paretic hand. Nineteen chronic stroke subjects underwent 20 sessions of EMG-driven robot hand training, and their Action Reach Arm Test (ARAT) showed significant improvement ( β =3.56, [Formula: see text]). The improvement was correlated with the reduction of inhibitory coupling from the contralesional M1 to the ipsilesional M1 (r=0.58, p=0.014). An increase in the laterality index was only observed in homotopic M1, but not in the premotor area. Additionally, we identified an increase in resting-state functional connectivity (FC) between bilateral M1 ( β =0.11, p=0.01). Inter-M1 FC demonstrated marginal positive relationships with ARAT scores (r=0.402, p=0.110), but its changes did not correlate with ARAT improvements. These findings suggest that the improvement of hand functions brought about by EMG-driven robot hand training was driven explicitly by task-specific reorganization of motor networks. Particularly, the restoration of interhemispheric balance was induced by a reduction in interhemispheric inhibition from the contralesional M1 during motor tasks of the paretic hand. This finding sheds light on the mechanistic understanding of interhemispheric balance and functional recovery induced by EMG-driven robot training.
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Zhou S, Zhang J, Chen F, Wong TWL, Ng SSM, Li Z, Zhou Y, Zhang S, Guo S, Hu X. Automatic theranostics for long-term neurorehabilitation after stroke. Front Aging Neurosci 2023; 15:1154795. [PMID: 37261267 PMCID: PMC10228725 DOI: 10.3389/fnagi.2023.1154795] [Citation(s) in RCA: 1] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Key Words] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/31/2023] [Accepted: 04/25/2023] [Indexed: 06/02/2023] Open
Affiliation(s)
- Sa Zhou
- Department of Biomedical Engineering, The Hong Kong Polytechnic University, Kowloon, Hong Kong SAR, China
| | - Jianing Zhang
- Department of Biomedical Engineering, The Hong Kong Polytechnic University, Kowloon, Hong Kong SAR, China
| | - Fei Chen
- Department of Electrical and Electronic Engineering, Southern University of Science and Technology, Shenzhen, China
| | - Thomson Wai-Lung Wong
- Department of Rehabilitation Sciences, The Hong Kong Polytechnic University, Kowloon, Hong Kong SAR, China
| | - Shamay S. M. Ng
- Department of Rehabilitation Sciences, The Hong Kong Polytechnic University, Kowloon, Hong Kong SAR, China
| | - Zengyong Li
- Beijing Key Laboratory of Rehabilitation Technical Aids for Old-Age Disability, National Research Centre for Rehabilitation Technical Aids Beijing, Beijing, China
| | - Yongjin Zhou
- Health Science Center, School of Biomedical Engineering, Shenzhen University, Shenzhen, China
| | - Shaomin Zhang
- Key Laboratory of Biomedical Engineering of Education Ministry, Zhejiang Provincial Key Laboratory of Cardio-Cerebral Vascular Detection Technology and Medicinal Effectiveness Appraisal, Department of Biomedical Engineering, School of Biomedical Engineering and Instrument Science, Zhejiang University, Hangzhou, China
| | - Song Guo
- Department of Computing, The Hong Kong Polytechnic University, Kowloon, Hong Kong SAR, China
| | - Xiaoling Hu
- Department of Biomedical Engineering, The Hong Kong Polytechnic University, Kowloon, Hong Kong SAR, China
- Shenzhen Research Institute, The Hong Kong Polytechnic University, Shenzhen, China
- University Research Facility in Behavioural and Systems Neuroscience (UBSN), The Hong Kong Polytechnic University, Kowloon, Hong Kong SAR, China
- Research Institute for Smart Ageing (RISA), The Hong Kong Polytechnic University, Kowloon, Hong Kong SAR, China
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Characteristics analysis of muscle function network and its application to muscle compensatory in repetitive movement. Biomed Signal Process Control 2023. [DOI: 10.1016/j.bspc.2023.104639] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 02/08/2023]
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Fujimoto A, Enoki H, Hatano K, Sato K, Okanishi T. Finger movement functions remain in the ipsilesional hemisphere and compensation by the contralesional hemisphere might not be expected after hemispherotomy -pre- and post-hemispherotomy evaluations in 8 cases. Brain Dev 2023:S0387-7604(23)00063-3. [PMID: 37028994 DOI: 10.1016/j.braindev.2023.03.007] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 01/12/2023] [Revised: 03/14/2023] [Accepted: 03/22/2023] [Indexed: 04/09/2023]
Abstract
BACKGROUND We hypothesized that fine finger motor functions are controlled by the ipsilesional hemisphere, and that gross motor functions are compensated for by the contralesional hemisphere after brain injury in humans. The purpose of this study was to compare finger movements before and after hemispherotomy that defunctionated the ipsilesional hemisphere for patients with hemispherical lesions. METHODS We statistically compared Brunnstrom stage of the fingers, arm (upper extremity), and leg (lower extremity) before and after hemispherotomy. Inclusion criteria for this study were: 1) hemispherotomy for hemispherical epilepsy; 2) a ≥ 6-month history of hemiparesis; 3) post-operative follow-up ≥ 6 months; 4) complete freedom from seizures without aura; and 5) application of our protocol for hemispherotomy. RESULTS Among 36 patients who underwent multi-lobe disconnection surgeries, 8 patients (2 girls, 6 boys) met the study criteria. Mean age at surgery was 6.38 years (range, 2-12 years; median, 6 years; standard deviation, 3.5 years). Paresis of the fingers was significantly exacerbated (p = 0.011) compared to pre-operatively, whereas that of the upper limbs (p = 0.07) and lower limbs (p = 0.103) was not. CONCLUSION Finger movement functions tend to remain in the ipsilesional hemisphere after brain injury, whereas gross motor movement functions such as those of the arms and legs are compensated for by the contralesional hemisphere in humans.
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Affiliation(s)
- Ayataka Fujimoto
- Department of Neurosurgery, Seirei Hamamatsu General Hospital, Shizuoka, Japan; Comprehensive Epilepsy Center, Seirei Hamamatsu General Hospital, Shizuoka, Japan; School of Rehabilitation Sciences, Seirei Christopher University, Shizuoka, Japan.
| | - Hideo Enoki
- Comprehensive Epilepsy Center, Seirei Hamamatsu General Hospital, Shizuoka, Japan
| | - Keisuke Hatano
- Comprehensive Epilepsy Center, Seirei Hamamatsu General Hospital, Shizuoka, Japan
| | - Keishiro Sato
- Comprehensive Epilepsy Center, Seirei Hamamatsu General Hospital, Shizuoka, Japan
| | - Tohru Okanishi
- Comprehensive Epilepsy Center, Seirei Hamamatsu General Hospital, Shizuoka, Japan
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Pichiorri F, Toppi J, de Seta V, Colamarino E, Masciullo M, Tamburella F, Lorusso M, Cincotti F, Mattia D. Exploring high-density corticomuscular networks after stroke to enable a hybrid Brain-Computer Interface for hand motor rehabilitation. J Neuroeng Rehabil 2023; 20:5. [PMID: 36639665 PMCID: PMC9840279 DOI: 10.1186/s12984-023-01127-6] [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: 08/02/2022] [Accepted: 01/07/2023] [Indexed: 01/15/2023] Open
Abstract
BACKGROUND Brain-Computer Interfaces (BCI) promote upper limb recovery in stroke patients reinforcing motor related brain activity (from electroencephalogaphy, EEG). Hybrid BCIs which include peripheral signals (electromyography, EMG) as control features could be employed to monitor post-stroke motor abnormalities. To ground the use of corticomuscular coherence (CMC) as a hybrid feature for a rehabilitative BCI, we analyzed high-density CMC networks (derived from multiple EEG and EMG channels) and their relation with upper limb motor deficit by comparing data from stroke patients with healthy participants during simple hand tasks. METHODS EEG (61 sensors) and EMG (8 muscles per arm) were simultaneously recorded from 12 stroke (EXP) and 12 healthy participants (CTRL) during simple hand movements performed with right/left (CTRL) and unaffected/affected hand (EXP, UH/AH). CMC networks were estimated for each movement and their properties were analyzed by means of indices derived ad-hoc from graph theory and compared among groups. RESULTS Between-group analysis showed that CMC weight of the whole brain network was significantly reduced in patients during AH movements. The network density was increased especially for those connections entailing bilateral non-target muscles. Such reduced muscle-specificity observed in patients was confirmed by muscle degree index (connections per muscle) which indicated a connections' distribution among non-target and contralateral muscles and revealed a higher involvement of proximal muscles in patients. CMC network properties correlated with upper-limb motor impairment as assessed by Fugl-Meyer Assessment and Manual Muscle Test in patients. CONCLUSIONS High-density CMC networks can capture motor abnormalities in stroke patients during simple hand movements. Correlations with upper limb motor impairment support their use in a BCI-based rehabilitative approach.
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Affiliation(s)
- Floriana Pichiorri
- Neuroelectrical Imaging and Brain Computer Interface Lab, IRCCS Fondazione Santa Lucia, Via Ardeatina, 306, 00179, Rome, Italy.
| | - Jlenia Toppi
- grid.417778.a0000 0001 0692 3437Neuroelectrical Imaging and Brain Computer Interface Lab, IRCCS Fondazione Santa Lucia, Via Ardeatina, 306, 00179 Rome, Italy ,grid.7841.aDept. of Computer, Control and Management Engineering, Sapienza University of Rome, Rome, Italy
| | - Valeria de Seta
- grid.417778.a0000 0001 0692 3437Neuroelectrical Imaging and Brain Computer Interface Lab, IRCCS Fondazione Santa Lucia, Via Ardeatina, 306, 00179 Rome, Italy ,grid.7841.aDept. of Computer, Control and Management Engineering, Sapienza University of Rome, Rome, Italy
| | - Emma Colamarino
- grid.417778.a0000 0001 0692 3437Neuroelectrical Imaging and Brain Computer Interface Lab, IRCCS Fondazione Santa Lucia, Via Ardeatina, 306, 00179 Rome, Italy ,grid.7841.aDept. of Computer, Control and Management Engineering, Sapienza University of Rome, Rome, Italy
| | - Marcella Masciullo
- grid.414396.d0000 0004 1760 8127Neurology and Neurovascular Treatment Unit, Belcolle Hospital, Viterbo, Italy
| | - Federica Tamburella
- grid.417778.a0000 0001 0692 3437Laboratory of Robotic Neurorehabilitation (NeuroRobot Lab), Neurorehabilitation 1 Department, IRCCS Fondazione Santa Lucia, Rome, Italy
| | - Matteo Lorusso
- grid.417778.a0000 0001 0692 3437Laboratory of Robotic Neurorehabilitation (NeuroRobot Lab), Neurorehabilitation 1 Department, IRCCS Fondazione Santa Lucia, Rome, Italy
| | - Febo Cincotti
- grid.417778.a0000 0001 0692 3437Neuroelectrical Imaging and Brain Computer Interface Lab, IRCCS Fondazione Santa Lucia, Via Ardeatina, 306, 00179 Rome, Italy ,grid.7841.aDept. of Computer, Control and Management Engineering, Sapienza University of Rome, Rome, Italy
| | - Donatella Mattia
- grid.417778.a0000 0001 0692 3437Neuroelectrical Imaging and Brain Computer Interface Lab, IRCCS Fondazione Santa Lucia, Via Ardeatina, 306, 00179 Rome, Italy
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Zhang Y, Chen W, Lin CL, Pei Z, Chen J, Wang D. Synchronous analyses between electroencephalogram and surface electromyogram based on motor imagery and motor execution. THE REVIEW OF SCIENTIFIC INSTRUMENTS 2022; 93:115114. [PMID: 36461556 DOI: 10.1063/5.0110827] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 07/17/2022] [Accepted: 11/01/2022] [Indexed: 06/17/2023]
Abstract
The functional coupling of the cerebral cortex and muscle contraction indicates that electroencephalogram (EEG) and surface electromyogram (sEMG) signals are coherent. The objective of this study is to clearly describe the coupling relationship between EEG and sEMG through a variety of analysis methods. We collected the EEG and sEMG data of left- or right-hand motor imagery and motor execution from six healthy subjects and six stroke patients. To enhance the coherence coefficient between EEG and sEMG signals, the algorithm of EEG modification based on the peak position of sEMG signals is proposed. Through analyzing a variety of signal synchronization analysis methods, the most suitable coherence analysis algorithm is selected. In addition, the wavelet coherence analysis method based on time spectrum estimation was used to study the linear correlation characteristics of the frequency domain components of EEG and sEMG signals, which verified that wavelet coherence analysis can effectively describe the temporal variation characteristics of EEG-sEMG coherence. In the task of motor imagery, the significant EEG-sEMG coherence is mainly in the imagination process with the frequency distribution of the alpha and beta frequency bands; in the task of motor execution, the significant EEG-sEMG coherence mainly concentrates before and during the task with the frequency distribution of the alpha, beta, and gamma frequency bands. The results of this study may provide a theoretical basis for the cooperative working mode of neurorehabilitation training and introduce a new method for evaluating the functional state of neural rehabilitation movement.
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Affiliation(s)
- Yue Zhang
- School of Automation Science and Electrical Engineering, Beihang University, Beijing, China
| | - Weihai Chen
- School of Automation Science and Electrical Engineering, Beihang University, Beijing, China
| | - Chun-Liang Lin
- Department of Electrical Engineering, National Chung Hsing University, Taichung, Taiwan
| | - Zhongcai Pei
- School of Automation Science and Electrical Engineering, Beihang University, Beijing, China
| | - Jianer Chen
- Department of Geriatric Rehabilitation, The Third Affiliated Hospital of Zhejiang Chinese Medical University, Hangzhou, Zhejiang Province, China
| | - Daming Wang
- Department of Rehabilitation Medicine, The First Affiliated Hospital, College of Medicine, Zhejiang University, Hangzhou, Zhejiang Province, China
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Guo Z, Zhou S, Ji K, Zhuang Y, Song J, Nam C, Hu X, Zheng Y. Corticomuscular integrated representation of voluntary motor effort in robotic control for wrist-hand rehabilitation after stroke. J Neural Eng 2022; 19. [PMID: 35193124 DOI: 10.1088/1741-2552/ac5757] [Citation(s) in RCA: 7] [Impact Index Per Article: 3.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/27/2021] [Accepted: 02/22/2022] [Indexed: 11/12/2022]
Abstract
OBJECTIVE The central-to-peripheral voluntary motor effort (VME) in physical practice of the paretic limb is a dominant force for driving functional neuroplasticity on motor restoration post-stroke. However, current rehabilitation robots isolated the central and peripheral involvements in the control design, resulting in limited rehabilitation effectiveness. The purpose of this study was to design a corticomuscular coherence (CMC) and electromyography (EMG)-driven (CMC-EMG-driven) system with central-and-peripheral integrated representation of VME for wrist-hand rehabilitation after stroke. APPROACH The CMC-EMG-driven control was developed in a neuromuscular electrical stimulation (NMES)-robot system, i.e., CMC-EMG-driven NMES-robot system, to instruct and assist the wrist-hand extension and flexion in persons after stroke. A pilot single-group trial of 20 training sessions was conducted with the developed system to assess the feasibility for wrist-hand practice on the chronic strokes (n=16). The rehabilitation effectiveness was evaluated through clinical assessments, CMC, and EMG activation levels. MAIN RESULTS The trigger success rate and laterality index (LI) of CMC were significantly increased in wrist-hand extension across training sessions (p<0.05). After the training, significant improvements in the target wrist-hand joints and suppressed compensation from the proximal shoulder-elbow joints were observed through the clinical scores and EMG activation levels (p<0.05). The central-to-peripheral VME distribution across upper extremity (UE) muscles was also significantly improved, as revealed by the CMC values (p<0.05). SIGNIFICANCE Precise wrist-hand rehabilitation was achieved by the developed system, presenting suppressed cortical and muscular compensation from the contralesional hemisphere and the proximal UE, and improved distribution of the central-and-peripheral VME on UE muscles.
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Affiliation(s)
- Ziqi Guo
- The Hong Kong Polytechnic University, Rm S107a, Dept. of BME, PolyU, Hung H, Hung Hom, Kowloon, Kowloon, Nil, HONG KONG
| | - Sa Zhou
- The Hong Kong Polytechnic University, Rm S107a, Dept. of BME, PolyU, Hung H, Hung Hom, Kowloon, Hong Kong, Kowloon, HONG KONG
| | - Kailai Ji
- The Hong Kong Polytechnic University, Dept. of BME, PolyU, Hung H, Hung Hom, Kowloon, Kowloon, Hong Kong, HONG KONG
| | - Yongqi Zhuang
- Biomedical Engineering, Hong Kong Polytechnic University, BME PolyU, Kowloon, HONG KONG
| | - Jie Song
- The Hong Kong Polytechnic University, Rm S107a, Dept. of BME, PolyU, Hung H, Hung Hom, Kowloon, Hong Kong, Kowloon, Nil, HONG KONG
| | - Chingyi Nam
- The Hong Kong Polytechnic University, Rm S107a, Dept. of BME, PolyU, Hung H, Hung Hom, Kowloon, Hong Kong, Kowloon, Nil, HONG KONG
| | - Xiaoling Hu
- Biomedical Engineering, Hong Kong Polytechnic University, Rm ST420, Dept. of BME, PolyU, Hung H, Hung Hom, Kowloon, Hong Kong, Kowloon, HONG KONG
| | - Yongping Zheng
- Biomedical Engineering, The Hong Kong Polytechnic University, BME PolyU, Hong Kong, Nil, CHINA
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