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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; 242:2093-2112. [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] [MESH Headings] [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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Krueger J, Krauth R, Reichert C, Perdikis S, Vogt S, Huchtemann T, Dürschmid S, Sickert A, Lamprecht J, Huremovic A, Görtler M, Nasuto SJ, Tsai IC, Knight RT, Hinrichs H, Heinze HJ, Lindquist S, Sailer M, Millán JDR, Sweeney-Reed CM. Hebbian plasticity induced by temporally coincident BCI enhances post-stroke motor recovery. Sci Rep 2024; 14:18700. [PMID: 39134592 DOI: 10.1038/s41598-024-69037-8] [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: 04/14/2023] [Accepted: 07/30/2024] [Indexed: 08/15/2024] Open
Abstract
Functional electrical stimulation (FES) can support functional restoration of a paretic limb post-stroke. Hebbian plasticity depends on temporally coinciding pre- and post-synaptic activity. A tight temporal relationship between motor cortical (MC) activity associated with attempted movement and FES-generated visuo-proprioceptive feedback is hypothesized to enhance motor recovery. Using a brain-computer interface (BCI) to classify MC spectral power in electroencephalographic (EEG) signals to trigger FES-delivery with detection of movement attempts improved motor outcomes in chronic stroke patients. We hypothesized that heightened neural plasticity earlier post-stroke would further enhance corticomuscular functional connectivity and motor recovery. We compared subcortical non-dominant hemisphere stroke patients in BCI-FES and Random-FES (FES temporally independent of MC movement attempt detection) groups. The primary outcome measure was the Fugl-Meyer Assessment, Upper Extremity (FMA-UE). We recorded high-density EEG and transcranial magnetic stimulation-induced motor evoked potentials before and after treatment. The BCI group showed greater: FMA-UE improvement; motor evoked potential amplitude; beta oscillatory power and long-range temporal correlation reduction over contralateral MC; and corticomuscular coherence with contralateral MC. These changes are consistent with enhanced post-stroke motor improvement when movement is synchronized with MC activity reflecting attempted movement.
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Affiliation(s)
- Johanna Krueger
- Neurocybernetics and Rehabilitation, Department of Neurology, Otto von Guericke University, Magdeburg, Germany
| | - Richard Krauth
- Neurocybernetics and Rehabilitation, Department of Neurology, Otto von Guericke University, Magdeburg, Germany
| | | | - Serafeim Perdikis
- School of Computer Science and Electronic Engineering, University of Essex, Colchester, UK
| | - Susanne Vogt
- Neurocybernetics and Rehabilitation, Department of Neurology, Otto von Guericke University, Magdeburg, Germany
- Department of Neurology, Otto von Guericke University, Magdeburg, Germany
- Department of Psychosomatic Medicine and Psychotherapy, Otto von Guericke University, Magdeburg, Germany
| | - Tessa Huchtemann
- Neurocybernetics and Rehabilitation, Department of Neurology, Otto von Guericke University, Magdeburg, Germany
- Department of Neurology, Otto von Guericke University, Magdeburg, Germany
- Department of Neurology, University Hospital Münster, Münster, Germany
| | - Stefan Dürschmid
- Leibniz Institute for Neurobiology, Magdeburg, Germany
- Center for Behavioral Brain Sciences (CBBS), Otto von Guericke University, Magdeburg, Germany
| | - Almut Sickert
- Neurorehabilitation Centre, MEDIAN, Magdeburg, Germany
| | - Juliane Lamprecht
- Neurorehabilitation Centre, MEDIAN, Magdeburg, Germany
- Health and Care Sciences, Martin Luther University Halle-Wittenberg, Halle, Germany
| | - Almir Huremovic
- Neurorehabilitation Centre, MEDIAN, Magdeburg, Germany
- Department of Neurology, Ingolstadt Hospital, Ingolstadt, Germany
| | - Michael Görtler
- Department of Neurology, Otto von Guericke University, Magdeburg, Germany
| | | | - I-Chin Tsai
- Neurocybernetics and Rehabilitation, Department of Neurology, Otto von Guericke University, Magdeburg, Germany
| | - Robert T Knight
- Helen Wills Neuroscience Institute, University of California -Berkeley, Berkeley, USA
- Department of Psychology, University of California -Berkeley, Berkeley, USA
| | - Hermann Hinrichs
- Leibniz Institute for Neurobiology, Magdeburg, Germany
- Department of Neurology, Otto von Guericke University, Magdeburg, Germany
- Center for Behavioral Brain Sciences (CBBS), Otto von Guericke University, Magdeburg, Germany
| | - Hans-Jochen Heinze
- Leibniz Institute for Neurobiology, Magdeburg, Germany
- University Hospital Magdeburg, Otto von Guericke University, Magdeburg, Germany
| | - Sabine Lindquist
- Department of Neurology, Pfeiffersche Stiftung, Magdeburg, Germany
| | | | - Jose Del R Millán
- Chandra Family Department of Electrical and Computer Engineering, The University of Texas at Austin, Austin, USA
- Department of Neurology, The University of Texas at Austin, Austin, USA
- Mulva Clinic for the Neurosciences, The University of Texas at Austin, Austin, USA
- Department of Biomedical Engineering, The University of Texas at Austin, Austin, USA
| | - Catherine M Sweeney-Reed
- Neurocybernetics and Rehabilitation, Department of Neurology, Otto von Guericke University, Magdeburg, Germany.
- Center for Behavioral Brain Sciences (CBBS), Otto von Guericke University, Magdeburg, Germany.
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Marin-Pardo O, Donnelly MR, Phanord CS, Wong K, Liew SL. Improvements in motor control are associated with improved quality of life following an at-home muscle biofeedback program for chronic stroke. Front Hum Neurosci 2024; 18:1356052. [PMID: 38818030 PMCID: PMC11138207 DOI: 10.3389/fnhum.2024.1356052] [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: 12/14/2023] [Accepted: 04/29/2024] [Indexed: 06/01/2024] Open
Abstract
Introduction Chronic stroke survivors with severe arm impairment have limited options for effective rehabilitation. High intensity, repetitive task practice (RTP) is known to improve upper limb function among stroke survivors who have some volitional muscle activation. However, clients without volitional movement of their arm are ineligible for RTP-based interventions and require hands-on facilitation from a clinician or robotic therapy to simulate task practice. Such approaches can be expensive, burdensome, and have marginal effects. Alternatively, supervised at-home telerehabilitation using muscle biofeedback may provide a more accessible, affordable, and effective rehabilitation option for stroke survivors with severe arm impairment, and could potentially help people with severe stroke regain enough volitional activation to be eligible for RTP-types of therapies. Feedback of muscle activity via electromyography (EMG) has been previously used with clients who have minimal or no movement to improve functional performance. Specifically, training to reduce unintended co-contractions of the impaired hand using EMG biofeedback may modestly improve motor control in people with limited movement. Importantly, these modest and covert functional changes may influence the perceived impact of stroke-related disability in daily life. In this manuscript, we examine whether physical changes following use of a portable EMG biofeedback system (Tele-REINVENT) for severe upper limb hemiparesis also relate to perceived quality of life improvements. Secondarily, we examined the effects of Tele-REINVENT, which uses EMG to quantify antagonistic muscle activity during movement attempt trials and transform individuated action into computer game control, on several different domains of stroke recovery. Methods For this pilot study, nine stroke survivors (age = 37-73 years) with chronic impairment (Fugl-Meyer = 14-40/66) completed 30 1-hour sessions of home-based training, consisting of six weeks of gaming that reinforced wrist extensor muscle activity while attenuating coactivation of flexor muscles. To assess motor control and performance, we measured changes in active wrist ranges of motion, the Fugl-Meyer Assessment, and Action Research Arm Test. We also collected an EMG-based test of muscle control to examine more subtle changes. To examine changes in perceived quality of life, we utilized the Stroke Impact Scale along with participant feedback. Results Results from our pilot data suggest that 30 sessions of remote training can induce modest changes on clinical and functional assessments, showing a statistically significant improvement of active wrist ranges of motion at the group level, changes that could allow some people with severe stroke to be eligible for other therapeutic approaches, such as RTP. Additionally, changes in motor control were correlated with the perceived impact of stroke on participation and impairment after training. We also report changes in corticomuscular coherence, which showed a laterality change from the ipsilesional motor cortex towards the contralesional hemisphere during wrist extension attempts. Finally, all participants showed high adherence to the protocol and reported enjoying using the system. Conclusion Overall, Tele-REINVENT represents a promising telerehabilitation intervention that might improve sensorimotor outcomes in severe chronic stroke, and that improving sensorimotor abilities even modestly may improve quality of life. We propose that Tele-REINVENT may be used as a precursor to help participants gain enough active movement to participate other occupational therapy interventions, such as RTP. Future work is needed to examine if home-based telerehabilitation to provide feedback of individuated muscle activity could increase meaningful rehabilitation accessibility and outcomes for underserved populations.
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Affiliation(s)
- Octavio Marin-Pardo
- Chan Division of Occupational Science and Occupational Therapy, University of Southern California, Los Angeles, CA, United States
| | - Miranda Rennie Donnelly
- Chan Division of Occupational Science and Occupational Therapy, University of Southern California, Los Angeles, CA, United States
| | - Coralie S. Phanord
- Chan Division of Occupational Science and Occupational Therapy, University of Southern California, Los Angeles, CA, United States
| | - Kira Wong
- Chan Division of Occupational Science and Occupational Therapy, University of Southern California, Los Angeles, CA, United States
| | - Sook-Lei Liew
- Chan Division of Occupational Science and Occupational Therapy, University of Southern California, Los Angeles, CA, United States
- Stevens Neuroimaging and Neuroinformatics Institute, Keck School of Medicine, University of Southern California, Los Angeles, CA, United States
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Gao Z, Lv S, Ran X, Wang Y, Xia M, Wang J, Qiu M, Wei Y, Shao Z, Zhao Z, Zhang Y, Zhou X, Yu Y. Influencing factors of corticomuscular coherence in stroke patients. Front Hum Neurosci 2024; 18:1354332. [PMID: 38562230 PMCID: PMC10982423 DOI: 10.3389/fnhum.2024.1354332] [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: 12/12/2023] [Accepted: 03/05/2024] [Indexed: 04/04/2024] Open
Abstract
Stroke, also known as cerebrovascular accident, is an acute cerebrovascular disease with a high incidence, disability rate, and mortality. It can disrupt the interaction between the cerebral cortex and external muscles. Corticomuscular coherence (CMC) is a common and useful method for studying how the cerebral cortex controls muscle activity. CMC can expose functional connections between the cortex and muscle, reflecting the information flow in the motor system. Afferent feedback related to CMC can reveal these functional connections. This paper aims to investigate the factors influencing CMC in stroke patients and provide a comprehensive summary and analysis of the current research in this area. This paper begins by discussing the impact of stroke and the significance of CMC in stroke patients. It then proceeds to elaborate on the mechanism of CMC and its defining formula. Next, the impacts of various factors on CMC in stroke patients were discussed individually. Lastly, this paper addresses current challenges and future prospects for CMC.
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Affiliation(s)
- Zhixian Gao
- School of Medical Engineering, Xinxiang Medical University, Xinxiang, China
- Engineering Technology Research Center of Neurosense and Control of Henan Province, Xinxiang, China
- Henan International Joint Laboratory of Neural Information Analysis and Drug Intelligent Design, Xinxiang, China
| | - Shiyang Lv
- School of Medical Engineering, Xinxiang Medical University, Xinxiang, China
- Engineering Technology Research Center of Neurosense and Control of Henan Province, Xinxiang, China
- Henan International Joint Laboratory of Neural Information Analysis and Drug Intelligent Design, Xinxiang, China
| | - Xiangying Ran
- School of Medical Engineering, Xinxiang Medical University, Xinxiang, China
- Engineering Technology Research Center of Neurosense and Control of Henan Province, Xinxiang, China
- Henan International Joint Laboratory of Neural Information Analysis and Drug Intelligent Design, Xinxiang, China
| | - Yuxi Wang
- School of Medical Engineering, Xinxiang Medical University, Xinxiang, China
- Engineering Technology Research Center of Neurosense and Control of Henan Province, Xinxiang, China
- Henan International Joint Laboratory of Neural Information Analysis and Drug Intelligent Design, Xinxiang, China
| | - Mengsheng Xia
- School of Medical Engineering, Xinxiang Medical University, Xinxiang, China
- Engineering Technology Research Center of Neurosense and Control of Henan Province, Xinxiang, China
- Henan International Joint Laboratory of Neural Information Analysis and Drug Intelligent Design, Xinxiang, China
| | - Junming Wang
- School of Medical Engineering, Xinxiang Medical University, Xinxiang, China
- Engineering Technology Research Center of Neurosense and Control of Henan Province, Xinxiang, China
- Henan International Joint Laboratory of Neural Information Analysis and Drug Intelligent Design, Xinxiang, China
| | - Mengyue Qiu
- School of Medical Engineering, Xinxiang Medical University, Xinxiang, China
- Engineering Technology Research Center of Neurosense and Control of Henan Province, Xinxiang, China
- Henan International Joint Laboratory of Neural Information Analysis and Drug Intelligent Design, Xinxiang, China
| | - Yinping Wei
- School of Medical Engineering, Xinxiang Medical University, Xinxiang, China
- Engineering Technology Research Center of Neurosense and Control of Henan Province, Xinxiang, China
- Henan International Joint Laboratory of Neural Information Analysis and Drug Intelligent Design, Xinxiang, China
| | - Zhenpeng Shao
- School of Medical Engineering, Xinxiang Medical University, Xinxiang, China
- Engineering Technology Research Center of Neurosense and Control of Henan Province, Xinxiang, China
- Henan International Joint Laboratory of Neural Information Analysis and Drug Intelligent Design, Xinxiang, China
| | - Zongya Zhao
- School of Medical Engineering, Xinxiang Medical University, Xinxiang, China
- Engineering Technology Research Center of Neurosense and Control of Henan Province, Xinxiang, China
- Henan International Joint Laboratory of Neural Information Analysis and Drug Intelligent Design, Xinxiang, China
| | - Yehong Zhang
- School of Medical Engineering, Xinxiang Medical University, Xinxiang, China
- Engineering Technology Research Center of Neurosense and Control of Henan Province, Xinxiang, China
- Henan International Joint Laboratory of Neural Information Analysis and Drug Intelligent Design, Xinxiang, China
| | - Xuezhi Zhou
- School of Medical Engineering, Xinxiang Medical University, Xinxiang, China
- Engineering Technology Research Center of Neurosense and Control of Henan Province, Xinxiang, China
| | - Yi Yu
- School of Medical Engineering, Xinxiang Medical University, Xinxiang, China
- Engineering Technology Research Center of Neurosense and Control of Henan Province, Xinxiang, China
- Henan International Joint Laboratory of Neural Information Analysis and Drug Intelligent Design, Xinxiang, China
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Zaidi KF, Harris-Love M. Upper extremity kinematics: development of a quantitative measure of impairment severity and dissimilarity after stroke. PeerJ 2023; 11:e16374. [PMID: 38089910 PMCID: PMC10712307 DOI: 10.7717/peerj.16374] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/03/2023] [Accepted: 10/08/2023] [Indexed: 12/18/2023] Open
Abstract
Background Strokes are a leading cause of disability worldwide, with many survivors experiencing difficulty in recovering upper extremity movement, particularly hand function and grasping ability. There is currently no objective measure of movement quality, and without it, rehabilitative interventions remain at best informed estimations of the underlying neural structures' response to produce movement. In this article, we utilize a novel modification to Procrustean distance to quantify curve dissimilarity and propose the Reach Severity and Dissimilarity Index (RSDI) as an objective measure of motor deficits. Methods All experiments took place at the Medstar National Rehabilitation Hospital; persons with stroke were recruited from the hospital patient population. Using Fugl-Meyer (FM) scores and reach capacities, stroke survivors were placed in either mild or severe impairment groups. Individuals completed sets of reach-to-target tasks to extrapolate kinematic metrics describing motor performance. The Procrustes method of statistical shape analysis was modified to identify reaching sub-movements that were congruous to able-bodied sub-movements. Findings Movement initiation proceeds comparably to the reference curve in both two- and three-dimensional representations of mild impairment movement. There were significant effects of the location of congruent segments between subject and reference curves, mean velocities, peak roll angle, and target error. These metrics were used to calculate a preliminary RSDI score with severity and dissimilarity sub-scores, and subjects were reclassified in terms of rehabilitation goals as Speed Emphasis, Strength Emphasis, and Combined Emphasis. Interpretation The modified Procrustes method shows promise in identifying disruptions in movement and monitoring recovery without adding to patient or clinician burden. The proposed RSDI score can be adapted and expanded to other functional movements and used as an objective clinical tool. By reducing the impact of stroke on disability, there is a significant potential to improve quality of life through individualized rehabilitation.
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Affiliation(s)
- Khadija F. Zaidi
- Department of Bioengineering, George Mason University, Fairfax, United States
| | - Michelle Harris-Love
- University of Colorado, Anschutz Medical Campus, Aurora, Colorado, United States
- Medstar National Rehabilitation Hospital, Washington, District of Columbia, United States of America
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Lv Y, Zhang JJ, Wang K, Ju L, Zhang H, Zhao Y, Pan Y, Gong J, Wang X, Fong KNK. Determining the Optimal Stimulation Sessions for TMS-Induced Recovery of Upper Extremity Motor Function Post Stroke: A Randomized Controlled Trial. Brain Sci 2023; 13:1662. [PMID: 38137110 PMCID: PMC10741851 DOI: 10.3390/brainsci13121662] [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: 10/29/2023] [Revised: 11/23/2023] [Accepted: 11/28/2023] [Indexed: 12/24/2023] Open
Abstract
To find out the optimal treatment sessions of repetitive transcranial magnetic stimulation (TMS) over the primary motor cortex (M1) for upper extremity dysfunction after stroke during the 6-week treatment and to explore its mechanism using motor-evoked potentials (MEPs) and resting-state functional magnetic resonance imaging (rs-fMRI), 72 participants with upper extremity motor dysfunction after ischemic stroke were randomly divided into the control group, 10-session, 20-session, and 30-session rTMS groups. Low-frequency (1 Hz) rTMS over the contralesional M1 was applied in all rTMS groups. The motor function of the upper extremity was assessed before and after treatment. In addition, MEPs and rs-fMRI data were analyzed to detect its effect on brain reorganization. After 6 weeks of treatment, there were significant differences in the Fugl-Meyer Assessment of the upper extremity and the Wolf Motor Function Test scores between the 10-session group and the 30-session group and between the 20- and 30-session groups and the control group, while there was no significant difference between the 20-session group and the 30-session group. Meanwhile, no significant difference was found between the 10-session group and the control group. The 20-session group of rTMS decreased the excitability of the contralesional corticospinal tract represented by the amplitudes of MEPs and enhanced the functional connectivity of the ipsilesional M1 or premotor cortex with the the precentral gyrus, postcentral gyrus, and cingulate gyrus, etc. In conclusion, the 20-session of rTMS protocol is the optimal treatment sessions of TMS for upper extremity dysfunction after stroke during the 6-week treatment. The potential mechanism is related to its influence on the excitability of the corticospinal tract and the remodeling of corticomotor functional networks.
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Affiliation(s)
- Yichen Lv
- School of Rehabilitation Medicine, Binzhou Medical University, Yantai 264000, China
- Department of Rehabilitation Medicine, Clinical Medical College, Yangzhou University, Yangzhou 225001, China
| | - Jack Jiaqi Zhang
- Department of Rehabilitation Sciences, The Hong Kong Polytechnic University, Kowloon, Hong Kong SAR, China
| | - Kui Wang
- Department of Rehabilitation Medicine, Clinical Medical College, Yangzhou University, Yangzhou 225001, China
| | - Leilei Ju
- Department of Rehabilitation Medicine, Clinical Medical College, Yangzhou University, Yangzhou 225001, China
| | - Hongying Zhang
- Department of Medical Imaging, Clinical Medical College, Yangzhou University, Yangzhou 225001, China
| | - Yuehan Zhao
- School of Rehabilitation Medicine, Binzhou Medical University, Yantai 264000, China
- Department of Rehabilitation Medicine, Clinical Medical College, Yangzhou University, Yangzhou 225001, China
| | - Yao Pan
- School of Rehabilitation Medicine, Binzhou Medical University, Yantai 264000, China
- Department of Rehabilitation Medicine, Clinical Medical College, Yangzhou University, Yangzhou 225001, China
| | - Jianwei Gong
- School of Rehabilitation Medicine, Binzhou Medical University, Yantai 264000, China
| | - Xin Wang
- Department of Rehabilitation Medicine, Clinical Medical College, Yangzhou University, Yangzhou 225001, China
| | - Kenneth N. K. Fong
- Department of Rehabilitation Sciences, The Hong Kong Polytechnic University, Kowloon, Hong Kong SAR, China
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Vidaurre C, Irastorza-Landa N, Sarasola-Sanz A, Insausti-Delgado A, Ray AM, Bibián C, Helmhold F, Mahmoud WJ, Ortego-Isasa I, López-Larraz E, Lozano Peiteado H, Ramos-Murguialday A. Challenges of neural interfaces for stroke motor rehabilitation. Front Hum Neurosci 2023; 17:1070404. [PMID: 37789905 PMCID: PMC10543821 DOI: 10.3389/fnhum.2023.1070404] [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: 10/14/2022] [Accepted: 08/28/2023] [Indexed: 10/05/2023] Open
Abstract
More than 85% of stroke survivors suffer from different degrees of disability for the rest of their lives. They will require support that can vary from occasional to full time assistance. These conditions are also associated to an enormous economic impact for their families and health care systems. Current rehabilitation treatments have limited efficacy and their long-term effect is controversial. Here we review different challenges related to the design and development of neural interfaces for rehabilitative purposes. We analyze current bibliographic evidence of the effect of neuro-feedback in functional motor rehabilitation of stroke patients. We highlight the potential of these systems to reconnect brain and muscles. We also describe all aspects that should be taken into account to restore motor control. Our aim with this work is to help researchers designing interfaces that demonstrate and validate neuromodulation strategies to enforce a contingent and functional neural linkage between the central and the peripheral nervous system. We thus give clues to design systems that can improve or/and re-activate neuroplastic mechanisms and open a new recovery window for stroke patients.
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Affiliation(s)
- Carmen Vidaurre
- TECNALIA, Basque Research and Technology Alliance (BRTA), San Sebastian, Spain
- Ikerbasque Science Foundation, Bilbao, Spain
| | | | | | | | - Andreas M. Ray
- Institute for Medical Psychology and Behavioral Neurobiology, University of Tübingen, Tübingen, Germany
| | - Carlos Bibián
- Institute for Medical Psychology and Behavioral Neurobiology, University of Tübingen, Tübingen, Germany
| | - Florian Helmhold
- Institute for Medical Psychology and Behavioral Neurobiology, University of Tübingen, Tübingen, Germany
| | - Wala J. Mahmoud
- Institute for Medical Psychology and Behavioral Neurobiology, University of Tübingen, Tübingen, Germany
| | - Iñaki Ortego-Isasa
- TECNALIA, Basque Research and Technology Alliance (BRTA), San Sebastian, Spain
| | - Eduardo López-Larraz
- Institute for Medical Psychology and Behavioral Neurobiology, University of Tübingen, Tübingen, Germany
- Bitbrain, Zaragoza, Spain
| | | | - Ander Ramos-Murguialday
- TECNALIA, Basque Research and Technology Alliance (BRTA), San Sebastian, Spain
- Institute for Medical Psychology and Behavioral Neurobiology, University of Tübingen, Tübingen, Germany
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8
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Ko NH, Laine CM, Valero-Cuevas FJ. Task-dependent alteration of beta-band intermuscular coherence is associated with ipsilateral corticospinal tract excitability. Front Sports Act Living 2023; 5:1177004. [PMID: 37576608 PMCID: PMC10416639 DOI: 10.3389/fspor.2023.1177004] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/01/2023] [Accepted: 07/18/2023] [Indexed: 08/15/2023] Open
Abstract
Beta-band (15-30 Hz) synchronization between the EMG signals of active limb muscles can serve as a non-invasive assay of corticospinal tract integrity. Tasks engaging a single limb often primarily utilize one corticospinal pathway, although bilateral neural circuits can participate in goal-directed actions involving multi-muscle coordination and utilization of feedback. Suboptimal utilization of such circuits after CNS injury can result in unintended mirror movements and activation of pathological synergies. Accordingly, it is important to understand how the actions of one limb (e.g., a less-affected limb after strokes) influence the opposite corticospinal pathway for the rehabilitation target. Certain unimanual actions decrease the excitability of the "unengaged" corticospinal tract, presumably to prevent mirror movement, but there is no direct way to predict the extent to which this will occur. In this study, we tested the hypothesis that task-dependent changes in beta-band drives to muscles of one hand will inversely correlate with changes in the opposite corticospinal tract excitability. Ten participants completed spring pinching tasks known to induce differential 15-30 Hz drive to muscles. During compressions, transcranial magnetic stimulation single pulses to the ipsilateral M1 were delivered to generate motor-evoked potentials in the unengaged hand. The task-induced changes in ipsilateral corticospinal excitability were inversely correlated with associated changes in EMG-EMG coherence of the task hand. These results demonstrate a novel connection between intermuscular coherence and the excitability of the "unengaged" corticospinal tract and provide a springboard for further mechanistic studies of unimanual tasks of varying difficulty and their effects on neural pathways relevant to rehabilitation.
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Affiliation(s)
- Na-hyeon Ko
- Department of Physical Therapy, California State University, Fresno, CA, United States
| | - Christopher M. Laine
- Division of Occupational Science and Occupational Therapy, University of Southern California, Los Angeles, CA, United States
| | - Francisco J. Valero-Cuevas
- Brain Body Dynamics Lab, Division of Biokinesiology and Physical Therapy, Department of Biomedical Engineering, University of Southern California, Los Angeles, CA, United States
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Glassen M, Ames G, Yue G, Nolan KJ, Saleh S. EEG Based Cortico-Muscular Connectivity During Standing Early Post Stroke. ANNUAL INTERNATIONAL CONFERENCE OF THE IEEE ENGINEERING IN MEDICINE AND BIOLOGY SOCIETY. IEEE ENGINEERING IN MEDICINE AND BIOLOGY SOCIETY. ANNUAL INTERNATIONAL CONFERENCE 2023; 2023:1-4. [PMID: 38083609 DOI: 10.1109/embc40787.2023.10341014] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 12/18/2023]
Abstract
In this exploratory study we studied brain activation and corticomuscular connectivity during standing in healthy individuals and persons with stroke within 40 days of cerebrovascular accident (CVA). EEG and EMG data were acquired during standing and analysis showed a trend of higher EEG power (hyper activation) in the stroke group. Direct corticomuscular connectivity between sensorimotor cortices and contralateral lower extremity muscles showed lower connectivity between affected motor, premotor, and sensory cortices, and contralateral lower extremity peripheral muscles with moderate effect size. The preliminary data in this paper suggest re-organization in left sensorimotor cortex role in controlling contralateral lower extremity muscles during standing. Correlational analysis in stroke group within 40 days of CVA showed a relationship between higher corticomuscular connectivity and better scores on balance assessments.Clinical Relevance- This study evaluates corticomuscular connectivity during standing in healthy controls and individuals with subacute stroke (within 40 days of injury). Better understanding of cortical control of standing post stroke is important to improve strategies used in mobility rehabilitation.
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Delcamp C, Gasq D, Cormier C, Amarantini D. Corticomuscular and intermuscular coherence are correlated after stroke: a simplified motor control? Brain Commun 2023; 5:fcad187. [PMID: 37377979 PMCID: PMC10292907 DOI: 10.1093/braincomms/fcad187] [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: 06/20/2022] [Revised: 05/11/2023] [Accepted: 06/16/2023] [Indexed: 06/29/2023] Open
Abstract
During movement, corticomuscular coherence is a measure of central-peripheral communication, while intermuscular coherence is a measure of the amount of common central drive to the muscles. Although these two measures are modified in stroke subjects, no author has explored a correlation between them, neither in stroke subjects nor in healthy subjects. Twenty-four chronic stroke subjects and 22 healthy control subjects were included in this cohort study, and they performed 20 active elbow extension movements. The electroencephalographic and electromyographic activity of the elbow flexors and extensors were recorded. Corticomuscular and intermuscular coherence were calculated in the time-frequency domain for each limb of stroke and control subjects. Partial rank correlations were performed to study the link between these two variables. Our results showed a positive correlation between corticomuscular and intermuscular coherence only for stroke subjects, for their paretic and non-paretic limbs (P < 0.022; Rho > 0.50). These results suggest, beyond the cortical and spinal hypotheses to explain them, that stroke subjects present a form of simplification of motor control. When central-peripheral communication increases, it is less modulated and more common to the muscles involved in the active movement. This motor control simplification suggests a new way of understanding the plasticity of the neuromuscular system after stroke.
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Affiliation(s)
- Célia Delcamp
- ToNIC, Toulouse NeuroImaging Center, Université de Toulouse, Inserm, Université Paul Sabatier, 31062 Toulouse, France
| | - David Gasq
- ToNIC, Toulouse NeuroImaging Center, Université de Toulouse, Inserm, Université Paul Sabatier, 31062 Toulouse, France
- Department of Functional Physiological Explorations, University Hospital of Toulouse, Hôpital de Rangueil, 31400 Toulouse, France
| | - Camille Cormier
- ToNIC, Toulouse NeuroImaging Center, Université de Toulouse, Inserm, Université Paul Sabatier, 31062 Toulouse, France
- Department of Functional Physiological Explorations, University Hospital of Toulouse, Hôpital de Rangueil, 31400 Toulouse, France
| | - David Amarantini
- Correspondence to: David Amarantini Unité ToNIC, UMR 1214, CHU PURPAN – Pavillon BAUDOT Place du Dr Joseph Baylac, 31024 Toulouse Cedex 3, France E-mail:
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Maura RM, Rueda Parra S, Stevens RE, Weeks DL, Wolbrecht ET, Perry JC. Literature review of stroke assessment for upper-extremity physical function via EEG, EMG, kinematic, and kinetic measurements and their reliability. J Neuroeng Rehabil 2023; 20:21. [PMID: 36793077 PMCID: PMC9930366 DOI: 10.1186/s12984-023-01142-7] [Citation(s) in RCA: 3] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/27/2021] [Accepted: 01/19/2023] [Indexed: 02/17/2023] Open
Abstract
BACKGROUND Significant clinician training is required to mitigate the subjective nature and achieve useful reliability between measurement occasions and therapists. Previous research supports that robotic instruments can improve quantitative biomechanical assessments of the upper limb, offering reliable and more sensitive measures. Furthermore, combining kinematic and kinetic measurements with electrophysiological measurements offers new insights to unlock targeted impairment-specific therapy. This review presents common methods for analyzing biomechanical and neuromuscular data by describing their validity and reporting their reliability measures. METHODS This paper reviews literature (2000-2021) on sensor-based measures and metrics for upper-limb biomechanical and electrophysiological (neurological) assessment, which have been shown to correlate with clinical test outcomes for motor assessment. The search terms targeted robotic and passive devices developed for movement therapy. Journal and conference papers on stroke assessment metrics were selected using PRISMA guidelines. Intra-class correlation values of some of the metrics are recorded, along with model, type of agreement, and confidence intervals, when reported. RESULTS A total of 60 articles are identified. The sensor-based metrics assess various aspects of movement performance, such as smoothness, spasticity, efficiency, planning, efficacy, accuracy, coordination, range of motion, and strength. Additional metrics assess abnormal activation patterns of cortical activity and interconnections between brain regions and muscle groups; aiming to characterize differences between the population who had a stroke and the healthy population. CONCLUSION Range of motion, mean speed, mean distance, normal path length, spectral arc length, number of peaks, and task time metrics have all demonstrated good to excellent reliability, as well as provide a finer resolution compared to discrete clinical assessment tests. EEG power features for multiple frequency bands of interest, specifically the bands relating to slow and fast frequencies comparing affected and non-affected hemispheres, demonstrate good to excellent reliability for populations at various stages of stroke recovery. Further investigation is needed to evaluate the metrics missing reliability information. In the few studies combining biomechanical measures with neuroelectric signals, the multi-domain approaches demonstrated agreement with clinical assessments and provide further information during the relearning phase. Combining the reliable sensor-based metrics in the clinical assessment process will provide a more objective approach, relying less on therapist expertise. This paper suggests future work on analyzing the reliability of metrics to prevent biasedness and selecting the appropriate analysis.
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Affiliation(s)
- Rene M. Maura
- Mechanical Engineering Department, University of Idaho, Moscow, ID USA
| | | | - Richard E. Stevens
- Engineering and Physics Department, Whitworth University, Spokane, WA USA
| | - Douglas L. Weeks
- College of Medicine, Washington State University, Spokane, WA USA
| | - Eric T. Wolbrecht
- Mechanical Engineering Department, University of Idaho, Moscow, ID USA
| | - Joel C. Perry
- Mechanical Engineering Department, University of Idaho, Moscow, ID USA
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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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Effect of music stimuli on corticomuscular coupling and the brain functional connectivity network. Biomed Signal Process Control 2023. [DOI: 10.1016/j.bspc.2022.104264] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/24/2022]
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Li H, Ji H, Yu J, Li J, Jin L, Liu L, Bai Z, Ye C. A sequential learning model with GNN for EEG-EMG-based stroke rehabilitation BCI. Front Neurosci 2023; 17:1125230. [PMID: 37139522 PMCID: PMC10150013 DOI: 10.3389/fnins.2023.1125230] [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: 12/16/2022] [Accepted: 03/27/2023] [Indexed: 05/05/2023] Open
Abstract
Introduction Brain-computer interfaces (BCIs) have the potential in providing neurofeedback for stroke patients to improve motor rehabilitation. However, current BCIs often only detect general motor intentions and lack the precise information needed for complex movement execution, mainly due to insufficient movement execution features in EEG signals. Methods This paper presents a sequential learning model incorporating a Graph Isomorphic Network (GIN) that processes a sequence of graph-structured data derived from EEG and EMG signals. Movement data are divided into sub-actions and predicted separately by the model, generating a sequential motor encoding that reflects the sequential features of the movements. Through time-based ensemble learning, the proposed method achieves more accurate prediction results and execution quality scores for each movement. Results A classification accuracy of 88.89% is achieved on an EEG-EMG synchronized dataset for push and pull movements, significantly outperforming the benchmark method's performance of 73.23%. Discussion This approach can be used to develop a hybrid EEG-EMG brain-computer interface to provide patients with more accurate neural feedback to aid their recovery.
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Affiliation(s)
- Haoyang Li
- Translational Research Center, Shanghai Yangzhi Rehabilitation Hospital (Shanghai Sunshine Rehabilitation Center), School of Electronic and Information Engineering, Tongji University, Shanghai, China
| | - Hongfei Ji
- Translational Research Center, Shanghai Yangzhi Rehabilitation Hospital (Shanghai Sunshine Rehabilitation Center), School of Electronic and Information Engineering, Tongji University, Shanghai, China
- Hongfei Ji
| | - Jian Yu
- Translational Research Center, Shanghai Yangzhi Rehabilitation Hospital (Shanghai Sunshine Rehabilitation Center), School of Electronic and Information Engineering, Tongji University, Shanghai, China
- Jian Yu
| | - Jie Li
- Translational Research Center, Shanghai Yangzhi Rehabilitation Hospital (Shanghai Sunshine Rehabilitation Center), School of Electronic and Information Engineering, Tongji University, Shanghai, China
- *Correspondence: Jie Li
| | - Lingjing Jin
- Department of Neurology and Neurological Rehabilitation, Shanghai Disabled Person's Federation Key Laboratory of Intelligent Rehabilitation Assistive Devices and Technologies, Yangzhi Rehabilitation Hospital (Shanghai Sunshine Rehabilitation Center), School of Medicine, Tongji University, Shanghai, China
- Neurotoxin Research Center of Key Laboratory of Spine and Spinal Cord Injury Repair and Regeneration of Ministry of Education, Neurological Department of Tongji Hospital, School of Medicine, Tongji University, Shanghai, China
| | - Lingyu Liu
- Department of Neurology and Neurological Rehabilitation, Shanghai Disabled Person's Federation Key Laboratory of Intelligent Rehabilitation Assistive Devices and Technologies, Yangzhi Rehabilitation Hospital (Shanghai Sunshine Rehabilitation Center), School of Medicine, Tongji University, Shanghai, China
| | - Zhongfei Bai
- Department of Neurology and Neurological Rehabilitation, Shanghai Disabled Person's Federation Key Laboratory of Intelligent Rehabilitation Assistive Devices and Technologies, Yangzhi Rehabilitation Hospital (Shanghai Sunshine Rehabilitation Center), School of Medicine, Tongji University, Shanghai, China
| | - Chen Ye
- Translational Research Center, Shanghai Yangzhi Rehabilitation Hospital (Shanghai Sunshine Rehabilitation Center), School of Electronic and Information Engineering, Tongji University, Shanghai, China
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de Seta V, Toppi J, Colamarino E, Molle R, Castellani F, Cincotti F, Mattia D, Pichiorri F. Cortico-muscular coupling to control a hybrid brain-computer interface for upper limb motor rehabilitation: A pseudo-online study on stroke patients. Front Hum Neurosci 2022; 16:1016862. [PMID: 36483633 PMCID: PMC9722732 DOI: 10.3389/fnhum.2022.1016862] [Citation(s) in RCA: 3] [Impact Index Per Article: 1.5] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/11/2022] [Accepted: 10/26/2022] [Indexed: 10/05/2023] Open
Abstract
Brain-Computer Interface (BCI) systems for motor rehabilitation after stroke have proven their efficacy to enhance upper limb motor recovery by reinforcing motor related brain activity. Hybrid BCIs (h-BCIs) exploit both central and peripheral activation and are frequently used in assistive BCIs to improve classification performances. However, in a rehabilitative context, brain and muscular features should be extracted to promote a favorable motor outcome, reinforcing not only the volitional control in the central motor system, but also the effective projection of motor commands to target muscles, i.e., central-to-peripheral communication. For this reason, we considered cortico-muscular coupling (CMC) as a feature for a h-BCI devoted to post-stroke upper limb motor rehabilitation. In this study, we performed a pseudo-online analysis on 13 healthy participants (CTRL) and 12 stroke patients (EXP) during executed (CTRL, EXP unaffected arm) and attempted (EXP affected arm) hand grasping and extension to optimize the translation of CMC computation and CMC-based movement detection from offline to online. Results showed that updating the CMC computation every 125 ms (shift of the sliding window) and accumulating two predictions before a final classification decision were the best trade-off between accuracy and speed in movement classification, independently from the movement type. The pseudo-online analysis on stroke participants revealed that both attempted and executed grasping/extension can be classified through a CMC-based movement detection with high performances in terms of classification speed (mean delay between movement detection and EMG onset around 580 ms) and accuracy (hit rate around 85%). The results obtained by means of this analysis will ground the design of a novel non-invasive h-BCI in which the control feature is derived from a combined EEG and EMG connectivity pattern estimated during upper limb movement attempts.
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Affiliation(s)
- Valeria de Seta
- Department of Computer, Control, and Management Engineering, Sapienza University of Rome, Rome, Italy
- Neuroelectric Imaging and BCI Lab, IRCCS Fondazione Santa Lucia, Rome, Italy
| | - Jlenia Toppi
- Department of Computer, Control, and Management Engineering, Sapienza University of Rome, Rome, Italy
- Neuroelectric Imaging and BCI Lab, IRCCS Fondazione Santa Lucia, Rome, Italy
| | - Emma Colamarino
- Department of Computer, Control, and Management Engineering, Sapienza University of Rome, Rome, Italy
- Neuroelectric Imaging and BCI Lab, IRCCS Fondazione Santa Lucia, Rome, Italy
| | - Rita Molle
- Neuroelectric Imaging and BCI Lab, IRCCS Fondazione Santa Lucia, Rome, Italy
| | - Filippo Castellani
- Neuroelectric Imaging and BCI Lab, IRCCS Fondazione Santa Lucia, Rome, Italy
| | - Febo Cincotti
- Department of Computer, Control, and Management Engineering, Sapienza University of Rome, Rome, Italy
- Neuroelectric Imaging and BCI Lab, IRCCS Fondazione Santa Lucia, Rome, Italy
| | - Donatella Mattia
- Neuroelectric Imaging and BCI Lab, IRCCS Fondazione Santa Lucia, Rome, Italy
| | - Floriana Pichiorri
- Neuroelectric Imaging and BCI Lab, IRCCS Fondazione Santa Lucia, Rome, Italy
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Marin-Pardo O, Donnelly MR, Phanord CS, Wong K, Pan J, Liew SL. Functional and neuromuscular changes induced via a low-cost, muscle-computer interface for telerehabilitation: A feasibility study in chronic stroke. FRONTIERS IN NEUROERGONOMICS 2022; 3:1046695. [PMID: 38235476 PMCID: PMC10790881 DOI: 10.3389/fnrgo.2022.1046695] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Subscribe] [Scholar Register] [Received: 09/16/2022] [Accepted: 10/31/2022] [Indexed: 01/19/2024]
Abstract
Stroke is a leading cause of adult disability in the United States. High doses of repeated task-specific practice have shown promising results in restoring upper limb function in chronic stroke. However, it is currently challenging to provide such doses in clinical practice. At-home telerehabilitation supervised by a clinician is a potential solution to provide higher-dose interventions. However, telerehabilitation systems developed for repeated task-specific practice typically require a minimum level of active movement. Therefore, severely impaired people necessitate alternative therapeutic approaches. Measurement and feedback of electrical muscle activity via electromyography (EMG) have been previously implemented in the presence of minimal or no volitional movement to improve motor performance in people with stroke. Specifically, muscle neurofeedback training to reduce unintended co-contractions of the impaired hand may be a targeted intervention to improve motor control in severely impaired populations. Here, we present the preliminary results of a low-cost, portable EMG biofeedback system (Tele-REINVENT) for supervised and unsupervised upper limb telerehabilitation after stroke. We aimed to explore the feasibility of providing higher doses of repeated task-specific practice during at-home training. Therefore, we recruited 5 participants (age = 44-73 years) with chronic, severe impairment due to stroke (Fugl-Meyer = 19-40/66). They completed a 6-week home-based training program that reinforced activity of the wrist extensor muscles while avoiding coactivation of flexor muscles via computer games. We used EMG signals to quantify the contribution of two antagonistic muscles and provide biofeedback of individuated activity, defined as a ratio of extensor and flexor activity during movement attempt. Our data suggest that 30 1-h sessions over 6 weeks of at-home training with our Tele-REINVENT system is feasible and may improve individuated muscle activity as well as scores on standard clinical assessments (e.g., Fugl-Meyer Assessment, Action Research Arm Test, active wrist range of motion) for some individuals. Furthermore, tests of neuromuscular control suggest modest changes in the synchronization of electroencephalography (EEG) and EMG signals within the beta band (12-30 Hz). Finally, all participants showed high adherence to the training protocol and reported enjoying using the system. These preliminary results suggest that using low-cost technology for home-based telerehabilitation after severe chronic stroke is feasible and may be effective in improving motor control via feedback of individuated muscle activity.
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Affiliation(s)
- Octavio Marin-Pardo
- Department of Biomedical Engineering, University of Southern California, Los Angeles, CA, United States
| | - Miranda Rennie Donnelly
- Chan Division of Occupational Science and Occupational Therapy, University of Southern California, Los Angeles, CA, United States
| | - Coralie S. Phanord
- Chan Division of Occupational Science and Occupational Therapy, University of Southern California, Los Angeles, CA, United States
| | - Kira Wong
- Chan Division of Occupational Science and Occupational Therapy, University of Southern California, Los Angeles, CA, United States
| | - Jessica Pan
- Dornsife College of Letters, Arts, and Sciences, University of Southern California, Los Angeles, CA, United States
| | - Sook-Lei Liew
- Department of Biomedical Engineering, University of Southern California, Los Angeles, CA, United States
- Chan Division of Occupational Science and Occupational Therapy, University of Southern California, Los Angeles, CA, United States
- Stevens Neuroinformatics Institute, Department of Neurology, University of Southern California, Los Angeles, CA, United States
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Delcamp C, Cormier C, Chalard A, Amarantini D, Gasq D. Changes in intermuscular connectivity during active elbow extension reveal a functional simplification of motor control after stroke. Front Neurosci 2022; 16:940907. [PMID: 36278013 PMCID: PMC9583396 DOI: 10.3389/fnins.2022.940907] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/10/2022] [Accepted: 09/09/2022] [Indexed: 11/30/2022] Open
Abstract
Background Stroke alters muscle co-activation and notably leads to exaggerated antagonist co-contraction responsible for impaired motor function. However, the mechanisms underlying this exaggerated antagonist co-contraction remain unclear. To fill this gap, the analysis of oscillatory synchronicity in electromyographic signals from synergistic muscles, also called intermuscular coherence, was a relevant tool. Objective This study compares functional intermuscular connectivity between muscle pairs of the paretic and non-paretic upper limbs of stroke subjects and the dominant limb of control subjects, concomitantly between two muscle pairs with a different functional role, through an intermuscular coherence analysis. Methods Twenty-four chronic stroke subjects and twenty-four healthy control subjects were included. Subjects performed twenty elbow extensions while kinematic data and electromyographic activity of both flexor and extensor elbow muscles were recorded. Intermuscular coherence was analyzed in the beta frequency band compared to the assessment of antagonist co-contraction. Results Intermuscular coherence was higher in the stroke subjects’ paretic limbs compared to control subjects. For stroke subjects, the intermuscular coherence of the antagonist-antagonist muscle pair (biceps brachii—brachioradialis) was higher than that of the agonist-antagonist muscle pair (triceps brachii—brachioradialis). For the paretic limb, intermuscular coherence of the antagonist-antagonist muscle pair presented a negative relationship with antagonist co-contraction. Conclusion Differences in intermuscular coherence between the paretic limbs of stroke subjects and control subjects suggest a higher common central drive during movement. Furthermore, results highlight the association between stroke-related alteration of intermuscular functional connectivity and the alteration of motor function.
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Affiliation(s)
- Célia Delcamp
- Toulouse NeuroImaging Center, Université de Toulouse, Inserm, UPS, Toulouse, France
| | - Camille Cormier
- Toulouse NeuroImaging Center, Université de Toulouse, Inserm, UPS, Toulouse, France
- Department of Functional Physiological Explorations, University Hospital of Toulouse, Hôpital de Rangueil, Toulouse, France
| | - Alexandre Chalard
- Department of Neurology, University of California, Los Angeles, Los Angeles, CA, United States
- California Rehabilitation Institute, Los Angeles, CA, United States
| | - David Amarantini
- Toulouse NeuroImaging Center, Université de Toulouse, Inserm, UPS, Toulouse, France
- *Correspondence: David Amarantini,
| | - David Gasq
- Toulouse NeuroImaging Center, Université de Toulouse, Inserm, UPS, Toulouse, France
- Department of Functional Physiological Explorations, University Hospital of Toulouse, Hôpital de Rangueil, Toulouse, France
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de Seta V, Colamarino E, Cincotti F, Mattia D, Mongiardini E, Pichiorri F, Toppi J. Cortico-Muscular Coupling Allows to Discriminate Different Types of Hand Movements. ANNUAL INTERNATIONAL CONFERENCE OF THE IEEE ENGINEERING IN MEDICINE AND BIOLOGY SOCIETY. IEEE ENGINEERING IN MEDICINE AND BIOLOGY SOCIETY. ANNUAL INTERNATIONAL CONFERENCE 2022; 2022:2324-2327. [PMID: 36086292 DOI: 10.1109/embc48229.2022.9871383] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 06/15/2023]
Abstract
Cortico-muscular coupling (CMC) could be used as potential input of a novel hybrid Brain-Computer Interface (hBCI) for motor re-learning after stroke. Here, we aim of addressing the design of a hBCI able to classify different movement tasks taking into account the interplay between the cerebral and residual or recovered muscular activity involved in a given movement. Hence, we compared the performances of four classification methods based on CMC features to evaluate their ability in discriminating finger extension from grasping movements executed by 17 healthy subjects. We also explored how the variation in the dimensionality of the feature domain would influence the different classifier performances. Results showed that, regardless of the model, few CMC features (up to 10) allow for a successful classification of two different movements type. Moreover, support vector machine classifier with linear kernel showed the best trade-off between performances and system usability (few electrodes). Thus, these results suggest that a hBCI based on brain-muscular interplay holds the potential to enable more informed neural plasticity and functional motor recovery after stroke. Furthermore, this CMC-based BCI could also allow for a more "natural control" (l.e., that resembling physiological control) of prosthetic devices.
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Keihani A, Mohammadi AM, Marzbani H, Nafissi S, Haidari MR, Jafari AH. Sparse representation of brain signals offers effective computation of cortico-muscular coupling value to predict the task-related and non-task sEMG channels: A joint hdEEG-sEMG study. PLoS One 2022; 17:e0270757. [PMID: 35776772 PMCID: PMC9249190 DOI: 10.1371/journal.pone.0270757] [Citation(s) in RCA: 2] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/26/2021] [Accepted: 06/17/2022] [Indexed: 11/19/2022] Open
Abstract
Cortico-muscular interactions play important role in sensorimotor control during motor task and are commonly studied by cortico-muscular coherence (CMC) method using joint electroencephalogram-surface electromyogram (EEG-sEMG) signals. As noise and time delay between the two signals weaken the CMC value, coupling difference between non-task sEMG channels is often undetectable. We used sparse representation of EEG channels to compute CMC and detect coupling for task-related and non-task sEMG signals. High-density joint EEG-sEMG (53 EEG channels, 4 sEMG bipolar channels) signals were acquired from 15 subjects (30.26 ± 4.96 years) during four specific hand and foot contraction tasks (2 dynamic and 2 static contraction). Sparse representations method was applied to detect projection of EEG signals on each sEMG channel. Bayesian optimization was employed to select best-fitted method with tuned hyperparameters on the input feeding data while using 80% data as the train set and 20% as test set. K-fold (K = 5) cross-validation method was used for evaluation of trained model. Two models were trained separately, one for CMC data and the other from sparse representation of EEG channels on each sEMG channel. Sensitivity, specificity, and accuracy criteria were obtained for test dataset to evaluate the performance of task-related and non-task sEMG channels detection. Coupling values were significantly different between grand average of task-related compared to the non-task sEMG channels (Z = -6.33, p< 0.001, task-related median = 2.011, non-task median = 0.112). Strong coupling index was found even in single trial analysis. Sparse representation approach (best fitted model: SVM, Accuracy = 88.12%, Sensitivity = 83.85%, Specificity = 92.45%) outperformed CMC method (best fitted model: KNN, Accuracy = 50.83%, Sensitivity = 52.17%, Specificity = 49.47%). Sparse representation approach offers high performance to detect CMC for discerning the EMG channels involved in the contraction tasks and non-tasks.
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Affiliation(s)
- Ahmadreza Keihani
- Department of Medical Physics and Biomedical Engineering, School of Medicine, Tehran University of Medical Sciences, Tehran, I.R. Iran
- Research Center for Biomedical Technologies and Robotics (RCBTR), Tehran University of Medical Sciences, Tehran, I.R. Iran
| | - Amin Mohammad Mohammadi
- Research Center for Biomedical Technologies and Robotics (RCBTR), Tehran University of Medical Sciences, Tehran, I.R. Iran
- Department of Electrical and Computer Engineering, University of Tehran, Tehran, I.R. Iran
| | - Hengameh Marzbani
- Department of Biomedical Engineering, Amirkabir University of Technology (Tehran Polytechnic), Tehran, I.R. Iran
| | - Shahriar Nafissi
- Department of Neurology, Neuromuscular Research Center, Shariati Hospital, Tehran University of Medical Sciences, Tehran, I.R. Iran
| | - Mohsen Reza Haidari
- Section of Neuroscience, Department of Neurology, Faculty of Medicine, Baqiyatallah University of Medical Sciences, Tehran, I.R. Iran
- * E-mail: (AHJ); (MRH)
| | - Amir Homayoun Jafari
- Department of Medical Physics and Biomedical Engineering, School of Medicine, Tehran University of Medical Sciences, Tehran, I.R. Iran
- Research Center for Biomedical Technologies and Robotics (RCBTR), Tehran University of Medical Sciences, Tehran, I.R. Iran
- * E-mail: (AHJ); (MRH)
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Liu J, Tan G, Wang J, Wei Y, Sheng Y, Chang H, Xie Q, Liu H. Closed-Loop Construction and Analysis of Cortico-Muscular-Cortical Functional Network After Stroke. IEEE TRANSACTIONS ON MEDICAL IMAGING 2022; 41:1575-1586. [PMID: 35030075 DOI: 10.1109/tmi.2022.3143133] [Citation(s) in RCA: 3] [Impact Index Per Article: 1.5] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 06/14/2023]
Abstract
Brain networks allow a topological understanding into the pathophysiology of stroke-induced motor deficits, and have been an influential tool for investigating brain functions. Unfortunately, currently applied methods generally lack in the recognition of the dynamic changes in the cortical networks related to muscle activity, which is crucial to clarify the alterations of the cooperative working patterns in the motor control system after stroke. In this study, we integrate corticomuscular and intermuscular interactions to cortico-cortical network and propose a novel closed-loop construction of cortico-muscular-cortical functional network, named closed-loop network (CLN). Directional characteristic in terms of differentiating causal interactions is endowed on basis of the CLN framework, further expanding the definition of functional connectivity (FC) and effective connectivity (EC) dedicated to CLN. Next, CLN is applied to stroke patients to reveal the underlying after-effects mechanism of low frequency repetitive transcranial magnetic stimulation (rTMS) induced alterations of cortical physiologic functions during movement. Results show that the short-term modulation of rTMS is reflected in the enhancement of information interaction within the interhemispheric primary motor regions and inhibition of the coupling between motor cortex and effector muscles. CLN provides a new perspective for the study of motor-related cortical networks with muscle activities involvement instead of being restricted to brain network analysis of behaviors.
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21
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Tan G, Wang J, Liu J, Sheng Y, Xie Q, Liu H. A framework for quantifying the effects of transcranial magnetic stimulation on motor recovery from hemiparesis: Corticomuscular Network. J Neural Eng 2022; 19. [PMID: 35366651 DOI: 10.1088/1741-2552/ac636b] [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] [Received: 01/11/2022] [Accepted: 04/01/2022] [Indexed: 11/12/2022]
Abstract
OBJECTIVE Transcranial magnetic stimulation (TMS) is an experimental therapy for promoting motor recovery from hemiparesis. At present, hemiparesis patients' responses to TMS are variable. To maximize its therapeutic potential, we need an approach that relates the electrophysiology of motor recovery and TMS. To this end, we propose Corticomuscular Network (CMN) representing the holistic motor system, including the cortico-cortical pathway, corticospinal tract, and muscle co-activation. METHODS CMN is made up of coherence between pairs of electrode signals and spatial locations of the electrodes. We associated coherence and graph features of CMN with Fugl-Meyer Assessment (FMA) for the upper extremity. Besides, we compared CMN between 8 patients with hemiparesis and 6 healthy controls and contrasted CMN of patients before and after a 1Hz TMS. MAIN RESULTS Corticomuscular coherence (CMC) correlated positively with FMA. The regression model between FMA and CMC between 5 pairs of channels had 0.99 adjusted R^2 and a p-value less than 0.01. Compared to healthy controls, CMN of patients tended to be a small-world network and was more interconnected with higher CMC. CMC between cortex and triceps brachii long head was higher in patients. 15-minute 1Hz TMS protocol induced coherence changes beyond the stimulation side and had a limited impact on CMN parameters that are related to motor recovery. SIGNIFICANCE CMN is a potential clinical approach to quantify rehabilitating progress. It also sheds light on the desirable electrophysiological effects of TMS based on which rehabilitating strategies can be optimized.
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Affiliation(s)
- Gansheng Tan
- Washington University in St Louis, 520 S Euclid Ave, St. Louis, MO 63110, St Louis, Missouri, 63130-4899, UNITED STATES
| | - Jixian Wang
- Shanghai Jiao Tong University Medical School Affiliated Ruijin Hospital, 800 Dongchuan Rd, Shanghai, 200025, CHINA
| | - Jinbiao Liu
- Shanghai Jiao Tong University, 800 Dongchuan Rd, Shanghai, 200240, CHINA
| | - Yixuan Sheng
- Shanghai Jiao Tong University, 800 Dongchuan Rd, Shanghai, 200240, CHINA
| | - Qing Xie
- Ruijin Hospital, 800 Dongchuan Rd, Shanghai, 200025, CHINA
| | - Honghai Liu
- Harbin Institute of Technology Shenzhen, Pingshan 1 Rd, Nanshan, Shenzhen, Guangdong, 518055, CHINA
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22
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Delcamp C, Cormier C, Chalard A, Amarantini D, Gasq D. Botulinum toxin injections combined with rehabilitation decrease corticomuscular coherence in stroke patients. Clin Neurophysiol 2022; 136:49-57. [DOI: 10.1016/j.clinph.2021.12.019] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/29/2021] [Revised: 12/20/2021] [Accepted: 12/28/2021] [Indexed: 11/03/2022]
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23
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Garro F, Chiappalone M, Buccelli S, De Michieli L, Semprini M. Neuromechanical Biomarkers for Robotic Neurorehabilitation. Front Neurorobot 2021; 15:742163. [PMID: 34776920 PMCID: PMC8579108 DOI: 10.3389/fnbot.2021.742163] [Citation(s) in RCA: 13] [Impact Index Per Article: 4.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/15/2021] [Accepted: 09/22/2021] [Indexed: 02/06/2023] Open
Abstract
One of the current challenges for translational rehabilitation research is to develop the strategies to deliver accurate evaluation, prediction, patient selection, and decision-making in the clinical practice. In this regard, the robot-assisted interventions have gained popularity as they can provide the objective and quantifiable assessment of the motor performance by taking the kinematics parameters into the account. Neurophysiological parameters have also been proposed for this purpose due to the novel advances in the non-invasive signal processing techniques. In addition, other parameters linked to the motor learning and brain plasticity occurring during the rehabilitation have been explored, looking for a more holistic rehabilitation approach. However, the majority of the research done in this area is still exploratory. These parameters have shown the capability to become the “biomarkers” that are defined as the quantifiable indicators of the physiological/pathological processes and the responses to the therapeutical interventions. In this view, they could be finally used for enhancing the robot-assisted treatments. While the research on the biomarkers has been growing in the last years, there is a current need for a better comprehension and quantification of the neuromechanical processes involved in the rehabilitation. In particular, there is a lack of operationalization of the potential neuromechanical biomarkers into the clinical algorithms. In this scenario, a new framework called the “Rehabilomics” has been proposed to account for the rehabilitation research that exploits the biomarkers in its design. This study provides an overview of the state-of-the-art of the biomarkers related to the robotic neurorehabilitation, focusing on the translational studies, and underlying the need to create the comprehensive approaches that have the potential to take the research on the biomarkers into the clinical practice. We then summarize some promising biomarkers that are being under investigation in the current literature and provide some examples of their current and/or potential applications in the neurorehabilitation. Finally, we outline the main challenges and future directions in the field, briefly discussing their potential evolution and prospective.
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Affiliation(s)
- Florencia Garro
- Rehab Technologies, Istituto Italiano di Tecnologia, Genoa, Italy.,Department of Informatics, Bioengineering, Robotics and Systems Engineering, University of Genoa, Genoa, Italy
| | - Michela Chiappalone
- Rehab Technologies, Istituto Italiano di Tecnologia, Genoa, Italy.,Department of Informatics, Bioengineering, Robotics and Systems Engineering, University of Genoa, Genoa, Italy
| | - Stefano Buccelli
- Rehab Technologies, Istituto Italiano di Tecnologia, Genoa, Italy
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24
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Kudo D, Koseki T, Katagiri N, Yoshida K, Takano K, Jin M, Nito M, Tanabe S, Yamaguchi T. Individualized beta-band oscillatory transcranial direct current stimulation over the primary motor cortex enhances corticomuscular coherence and corticospinal excitability in healthy individuals. Brain Stimul 2021; 15:46-52. [PMID: 34742996 DOI: 10.1016/j.brs.2021.11.004] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/16/2021] [Revised: 10/28/2021] [Accepted: 11/01/2021] [Indexed: 12/14/2022] Open
Abstract
BACKGROUND Simultaneously modulating individual neural oscillation and cortical excitability may be important for enhancing communication between the primary motor cortex and spinal motor neurons, which plays a key role in motor control. However, it is unknown whether individualized beta-band oscillatory transcranial direct current stimulation (otDCS) enhances corticospinal oscillation and excitability. OBJECTIVE This study investigated the effects of individualized beta-band otDCS on corticomuscular coherence (CMC) and corticospinal excitability in healthy individuals. METHODS In total, 29 healthy volunteers participated in separate experiments. They received the following stimuli for 10 min on different days: 1) 2-mA otDCS with individualized beta-band frequencies, 2) 2-mA transcranial alternating current stimulation (tACS) with individualized beta-band frequencies, and 3) 2-mA transcranial direct current stimulation (tDCS). The changes in CMC between the vertex and tibialis anterior (TA) muscle and TA muscle motor-evoked potentials (MEPs) were assessed before and after (immediately, 10 min, and 20 min after) stimulation on different days. Additionally, 20-Hz otDCS for 10 min was applied to investigate the effects of a fixed beta-band frequency on CMC. RESULTS otDCS significantly increased CMC and MEPs immediately after stimulation, whereas tACS and tDCS had no effects. There was a significant negative correlation between normalized CMC changes in response to 20-Hz otDCS and the numerical difference between the 20-Hz and individualized CMC peak frequency before the stimulation. CONCLUSIONS These findings suggest that simultaneous modulation of neural oscillation and cortical excitability is critical for enhancing corticospinal communication. Individualized otDCS holds potential as a useful method in the field of neurorehabilitation.
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Affiliation(s)
- Daisuke Kudo
- Department of Physical Therapy, Yamagata Prefectural University of Health Sciences, 260 Kamiyanagi, Yamagata-shi, Yamagata, 990-2212, Japan; Department of Physical Therapy, Graduate School of Health Sciences, Yamagata Prefectural University of Health Sciences, 260 Kamiyanagi, Yamagata-shi, Yamagata, 990-2212, Japan.
| | - Tadaki Koseki
- Department of Physical Therapy, Graduate School of Health Sciences, Yamagata Prefectural University of Health Sciences, 260 Kamiyanagi, Yamagata-shi, Yamagata, 990-2212, Japan.
| | - Natsuki Katagiri
- Department of Physical Therapy, Graduate School of Health Sciences, Yamagata Prefectural University of Health Sciences, 260 Kamiyanagi, Yamagata-shi, Yamagata, 990-2212, Japan.
| | - Kaito Yoshida
- Department of Physical Therapy, Graduate School of Health Sciences, Yamagata Prefectural University of Health Sciences, 260 Kamiyanagi, Yamagata-shi, Yamagata, 990-2212, Japan.
| | - Keita Takano
- Department of Physical Therapy, Graduate School of Health Sciences, Yamagata Prefectural University of Health Sciences, 260 Kamiyanagi, Yamagata-shi, Yamagata, 990-2212, Japan.
| | - Masafumi Jin
- Department of Physical Therapy, Graduate School of Health Sciences, Yamagata Prefectural University of Health Sciences, 260 Kamiyanagi, Yamagata-shi, Yamagata, 990-2212, Japan.
| | - Mitsuhiro Nito
- Department of Anatomy and Structural Science, Yamagata University School of Medicine, 2-2-2 Iida-Nishi, Yamagata, 990-9585, Japan.
| | - Shigeo Tanabe
- Faculty of Rehabilitation, School of Health Sciences, Fujita Health University, 1-98 Dengakugakubo, Kutsukake-cho, Toyoake-shi, Aichi, 470-1192, Japan.
| | - Tomofumi Yamaguchi
- Department of Physical Therapy, Faculty of Health Science, Juntendo University, 2-1-1 Hongo, Bunkyo-ku, Tokyo, 113-8421, Japan.
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25
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Brambilla C, Pirovano I, Mira RM, Rizzo G, Scano A, Mastropietro A. Combined Use of EMG and EEG Techniques for Neuromotor Assessment in Rehabilitative Applications: A Systematic Review. SENSORS (BASEL, SWITZERLAND) 2021; 21:7014. [PMID: 34770320 PMCID: PMC8588321 DOI: 10.3390/s21217014] [Citation(s) in RCA: 13] [Impact Index Per Article: 4.3] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Received: 08/23/2021] [Revised: 10/19/2021] [Accepted: 10/20/2021] [Indexed: 12/22/2022]
Abstract
Electroencephalography (EEG) and electromyography (EMG) are widespread and well-known quantitative techniques used for gathering biological signals at cortical and muscular levels, respectively. Indeed, they provide relevant insights for increasing knowledge in different domains, such as physical and cognitive, and research fields, including neuromotor rehabilitation. So far, EEG and EMG techniques have been independently exploited to guide or assess the outcome of the rehabilitation, preferring one technique over the other according to the aim of the investigation. More recently, the combination of EEG and EMG started to be considered as a potential breakthrough approach to improve rehabilitation effectiveness. However, since it is a relatively recent research field, we observed that no comprehensive reviews available nor standard procedures and setups for simultaneous acquisitions and processing have been identified. Consequently, this paper presents a systematic review of EEG and EMG applications specifically aimed at evaluating and assessing neuromotor performance, focusing on cortico-muscular interactions in the rehabilitation field. A total of 213 articles were identified from scientific databases, and, following rigorous scrutiny, 55 were analyzed in detail in this review. Most of the applications are focused on the study of stroke patients, and the rehabilitation target is usually on the upper or lower limbs. Regarding the methodological approaches used to acquire and process data, our results show that a simultaneous EEG and EMG acquisition is quite common in the field, but it is mostly performed with EMG as a support technique for more specific EEG approaches. Non-specific processing methods such as EEG-EMG coherence are used to provide combined EEG/EMG signal analysis, but rarely both signals are analyzed using state-of-the-art techniques that are gold-standard in each of the two domains. Future directions may be oriented toward multi-domain approaches able to exploit the full potential of combined EEG and EMG, for example targeting a wider range of pathologies and implementing more structured clinical trials to confirm the results of the current pilot studies.
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Affiliation(s)
- Cristina Brambilla
- Istituto di Sistemi e Tecnologie Industriali Intelligenti per il Manifatturiero Avanzato (STIIMA), Consiglio Nazionale delle Ricerche (CNR), Via Previati 1/E, 23900 Lecco, Italy; (C.B.); (R.M.M.); (A.S.)
| | - Ileana Pirovano
- Istituto di Tecnologie Biomediche (ITB), Consiglio Nazionale delle Ricerche (CNR), via Fratelli Cervi 93, 20054 Segrate, Italy; (I.P.); (A.M.)
| | - Robert Mihai Mira
- Istituto di Sistemi e Tecnologie Industriali Intelligenti per il Manifatturiero Avanzato (STIIMA), Consiglio Nazionale delle Ricerche (CNR), Via Previati 1/E, 23900 Lecco, Italy; (C.B.); (R.M.M.); (A.S.)
| | - Giovanna Rizzo
- Istituto di Tecnologie Biomediche (ITB), Consiglio Nazionale delle Ricerche (CNR), via Fratelli Cervi 93, 20054 Segrate, Italy; (I.P.); (A.M.)
| | - Alessandro Scano
- Istituto di Sistemi e Tecnologie Industriali Intelligenti per il Manifatturiero Avanzato (STIIMA), Consiglio Nazionale delle Ricerche (CNR), Via Previati 1/E, 23900 Lecco, Italy; (C.B.); (R.M.M.); (A.S.)
| | - Alfonso Mastropietro
- Istituto di Tecnologie Biomediche (ITB), Consiglio Nazionale delle Ricerche (CNR), via Fratelli Cervi 93, 20054 Segrate, Italy; (I.P.); (A.M.)
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Koseki T, Kudo D, Katagiri N, Nanba S, Nito M, Tanabe S, Yamaguchi T. Electrical stimulation of the common peroneal nerve and its effects on the relationship between corticomuscular coherence and motor control in healthy adults. BMC Neurosci 2021; 22:61. [PMID: 34645385 PMCID: PMC8513252 DOI: 10.1186/s12868-021-00665-w] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/13/2021] [Accepted: 10/01/2021] [Indexed: 02/06/2023] Open
Abstract
Background Sensory input via neuromuscular electrical stimulation (NMES) may contribute to synchronization between motor cortex and spinal motor neurons and motor performance improvement in healthy adults and stroke patients. However, the optimal NMES parameters used to enhance physiological activity and motor performance remain unclear. In this study, we focused on sensory feedback induced by a beta-band frequency NMES (β-NMES) based on corticomuscular coherence (CMC) and investigated the effects of β-NMES on CMC and steady-state of isometric ankle dorsiflexion in healthy volunteers. Twenty-four participants received β-NMES at the peak beta-band CMC or fixed NMES (f-NMES) at 100 Hz on different days. NMES was applied to the right part of the common peroneal nerve for 20 min. The stimulation intensity was 95% of the motor threshold with a pulse width of 1 ms. The beta-band CMC and the coefficient of variation of force (Force CV) were assessed during isometric ankle dorsiflexion for 2 min. In the complementary experiment, we applied β-NMES to 14 participants and assessed beta-band CMC and motor evoked potentials (MEPs) with transcranial magnetic stimulation. Results No significant changes in the means of beta-band CMC, Force CV, and MEPs were observed before and after NMES conditions. Changes in beta-band CMC were correlated to (a) changes in Force CV immediately, at 10 min, and at 20 min after β-NMES (all cases, p < 0.05) and (b) changes in MEPs immediately after β-NMES (p = 0.01). No correlations were found after f-NMES. Conclusions Our results suggest that the sensory input via NMES was inadequate to change the beta-band CMC, corticospinal excitability, and voluntary motor output. Whereas, the β-NMES affects the relationship between changes in beta-band CMC, Force CV, and MEPs. These findings may provide the information to develop NMES parameters for neurorehabilitation in patients with motor dysfunction.
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Affiliation(s)
- Tadaki Koseki
- Department of Physical Therapy, Yamagata Prefectural University of Health Sciences, 260 Kamiyanagi, Yamagata, 990-2212, Japan
| | - Daisuke Kudo
- Department of Physical Therapy, Yamagata Prefectural University of Health Sciences, 260 Kamiyanagi, Yamagata, 990-2212, Japan
| | - Natsuki Katagiri
- Department of Physical Therapy, Yamagata Prefectural University of Health Sciences, 260 Kamiyanagi, Yamagata, 990-2212, Japan
| | - Shigehiro Nanba
- Department of Physical Therapy, Yamagata Prefectural University of Health Sciences, 260 Kamiyanagi, Yamagata, 990-2212, Japan
| | - Mitsuhiro Nito
- Department of Anatomy and Structural Science, Yamagata University School of Medicine, 2-2-2 Iida-Nishi, Yamagata, 990-9585, Japan
| | - Shigeo Tanabe
- Faculty of Rehabilitation, School of Health Sciences, Fujita Health University, 1-98 Dengakugakubo, Kutsukake-cho, Toyoake, Aichi, 470-1192, Japan
| | - Tomofumi Yamaguchi
- Department of Physical Therapy, Yamagata Prefectural University of Health Sciences, 260 Kamiyanagi, Yamagata, 990-2212, Japan. .,Department of Physical Therapy, Faculty of Health Science, Juntendo University, 2-1-1 Hongo, Bunkyo-ku, Tokyo, 113-8421, Japan.
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Colamarino E, de Seta V, Masciullo M, Cincotti F, Mattia D, Pichiorri F, Toppi J. Corticomuscular and Intermuscular Coupling in Simple Hand Movements to Enable a Hybrid Brain-Computer Interface. Int J Neural Syst 2021; 31:2150052. [PMID: 34590990 DOI: 10.1142/s0129065721500520] [Citation(s) in RCA: 14] [Impact Index Per Article: 4.7] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/13/2022]
Abstract
Hybrid Brain-Computer Interfaces (BCIs) for upper limb rehabilitation after stroke should enable the reinforcement of "more normal" brain and muscular activity. Here, we propose the combination of corticomuscular coherence (CMC) and intermuscular coherence (IMC) as control features for a novel hybrid BCI for rehabilitation purposes. Multiple electroencephalographic (EEG) signals and surface electromyography (EMG) from 5 muscles per side were collected in 20 healthy participants performing finger extension (Ext) and grasping (Grasp) with both dominant and non-dominant hand. Grand average of CMC and IMC patterns showed a bilateral sensorimotor area as well as multiple muscles involvement. CMC and IMC values were used as features to classify each task versus rest and Ext versus Grasp. We demonstrated that a combination of CMC and IMC features allows for classification of both movements versus rest with better performance (Area Under the receiver operating characteristic Curve, AUC) for the Ext movement (0.97) with respect to Grasp (0.88). Classification of Ext versus Grasp also showed high performances (0.99). All in all, these preliminary findings indicate that the combination of CMC and IMC could provide for a comprehensive framework for simple hand movements to eventually be employed in a hybrid BCI system for post-stroke rehabilitation.
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Affiliation(s)
- Emma Colamarino
- Department of Computer, Control and Management Engineering, Sapienza University of Rome, Via Ariosto 25, Rome 00185, Italy.,Fondazione Santa Lucia IRCCS, Via Ardeatina 306-354, Rome 00179, Italy
| | - Valeria de Seta
- Department of Computer, Control and Management Engineering, Sapienza University of Rome, Via Ariosto 25, Rome 00185, Italy.,Fondazione Santa Lucia IRCCS, Via Ardeatina 306-354, Rome 00179, Italy
| | | | - Febo Cincotti
- Department of Computer, Control and Management Engineering, Sapienza University of Rome, Via Ariosto 25, Rome 00185, Italy.,Fondazione Santa Lucia IRCCS, Via Ardeatina 306-354, Rome 00179, Italy
| | - Donatella Mattia
- Fondazione Santa Lucia IRCCS, Via Ardeatina 306-354, Rome 00179, Italy
| | | | - Jlenia Toppi
- Department of Computer, Control and Management Engineering, Sapienza University of Rome, Via Ariosto 25, Rome 00185, Italy.,Fondazione Santa Lucia IRCCS, Via Ardeatina 306-354, Rome 00179, Italy
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28
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Fauvet M, Gasq D, Chalard A, Tisseyre J, Amarantini D. Temporal Dynamics of Corticomuscular Coherence Reflects Alteration of the Central Mechanisms of Neural Motor Control in Post-Stroke Patients. Front Hum Neurosci 2021; 15:682080. [PMID: 34366811 PMCID: PMC8342994 DOI: 10.3389/fnhum.2021.682080] [Citation(s) in RCA: 5] [Impact Index Per Article: 1.7] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/17/2021] [Accepted: 06/21/2021] [Indexed: 11/16/2022] Open
Abstract
The neural control of muscular activity during a voluntary movement implies a continuous updating of a mix of afferent and efferent information. Corticomuscular coherence (CMC) is a powerful tool to explore the interactions between the motor cortex and the muscles involved in movement realization. The comparison of the temporal dynamics of CMC between healthy subjects and post-stroke patients could provide new insights into the question of how agonist and antagonist muscles are controlled related to motor performance during active voluntary movements. We recorded scalp electroencephalography activity, electromyography signals from agonist and antagonist muscles, and upper limb kinematics in eight healthy subjects and seventeen chronic post-stroke patients during twenty repeated voluntary elbow extensions and explored whether the modulation of the temporal dynamics of CMC could contribute to motor function impairment. Concomitantly with the alteration of elbow extension kinematics in post-stroke patients, dynamic CMC analysis showed a continuous CMC in both agonist and antagonist muscles during movement and highlighted that instantaneous CMC in antagonist muscles was higher for post-stroke patients compared to controls during the acceleration phase of elbow extension movement. In relation to motor control theories, our findings suggest that CMC could be involved in the online control of voluntary movement through the continuous integration of sensorimotor information. Moreover, specific alterations of CMC in antagonist muscles could reflect central command alterations of the selectivity in post-stroke patients.
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Affiliation(s)
- Maxime Fauvet
- ToNIC-Toulouse NeuroImaging Center, Université de Toulouse, Inserm, UPS, Toulouse, France
| | - David Gasq
- ToNIC-Toulouse NeuroImaging Center, Université de Toulouse, Inserm, UPS, Toulouse, France.,Department of Functional Physiological Explorations, University Hospital of Toulouse, Hôpital Rangueil, Toulouse, France
| | - Alexandre Chalard
- ToNIC-Toulouse NeuroImaging Center, Université de Toulouse, Inserm, UPS, Toulouse, France.,Department of Neurology, University of California, Los Angeles, Los Angeles, CA, United States.,California Rehabilitation Institute, Los Angeles, CA, United States
| | - Joseph Tisseyre
- ToNIC-Toulouse NeuroImaging Center, Université de Toulouse, Inserm, UPS, Toulouse, France
| | - David Amarantini
- ToNIC-Toulouse NeuroImaging Center, Université de Toulouse, Inserm, UPS, Toulouse, France
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Tun NN, Sanuki F, Iramina K. Electroencephalogram-Electromyogram Functional Coupling and Delay Time Change Based on Motor Task Performance. SENSORS 2021; 21:s21134380. [PMID: 34206753 PMCID: PMC8271984 DOI: 10.3390/s21134380] [Citation(s) in RCA: 3] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Received: 05/09/2021] [Revised: 06/17/2021] [Accepted: 06/21/2021] [Indexed: 11/21/2022]
Abstract
Synchronous correlation brain and muscle oscillations during motor task execution is termed as functional coupling. Functional coupling between two signals appears with a delay time which can be used to infer the directionality of information flow. Functional coupling of brain and muscle depends on the type of muscle contraction and motor task performance. Although there have been many studies of functional coupling with types of muscle contraction and force level, there has been a lack of investigation with various motor task performances. Motor task types play an essential role that can reflect the amount of functional interaction. Thus, we examined functional coupling under four different motor tasks: real movement, intention, motor imagery and movement observation tasks. We explored interaction of two signals with linear and nonlinear information flow. The aim of this study is to investigate the synchronization between brain and muscle signals in terms of functional coupling and delay time. The results proved that brain–muscle functional coupling and delay time change according to motor tasks. Quick synchronization of localized cortical activity and motor unit firing causes good functional coupling and this can lead to short delay time to oscillate between signals. Signals can flow with bidirectionality between efferent and afferent pathways.
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Affiliation(s)
- Nyi Nyi Tun
- Graduate School of Information Science and Electrical Engineering, Kyushu University, 744 Motooka, Nishi-ku, Fukuoka 819-0395, Japan
- Correspondence: (N.N.T.); (K.I.); Tel.: +81-80-9392-9429 (N.N.T.); Fax: +81-92-802-3581 (N.N.T.)
| | - Fumiya Sanuki
- Graduate School of Systems Life Sciences, Kyushu University, 744 Motooka, Nishi-ku, Fukuoka 819-0395, Japan;
| | - Keiji Iramina
- Faulty of Information Science and Electrical Engineering, Kyushu University, 744 Motooka, Nishi-ku, Fukuoka 819-0395, Japan
- Correspondence: (N.N.T.); (K.I.); Tel.: +81-80-9392-9429 (N.N.T.); Fax: +81-92-802-3581 (N.N.T.)
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Xi X, Wu X, Zhao YB, Wang J, Kong W, Luo Z. Cortico-muscular functional network: an exploration of cortico-muscular coupling in hand movements. J Neural Eng 2021; 18. [PMID: 34038874 DOI: 10.1088/1741-2552/ac0586] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.7] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/23/2020] [Accepted: 05/26/2021] [Indexed: 11/12/2022]
Abstract
Objective. The main objective of this research was to study cortico-muscular, intra-cortical, and inter-muscular coupling. Herein, we established a cortico-muscular functional network (CMFN) to assess the network differences associated with making a fist, opening the hand, and wrist flexion.Approach. We used transfer entropy (TE) to calculate the causality between electroencephalographic and electromyographic data and established the TE connection matrix. We then applied graph theory to analyze the clustering coefficient, global efficiency, and small-world attributes of the CMFN. We also used Relief-F to extract the features of the TE connection matrix of the beta2 band for the different hand movements and observed high accuracy when this feature was used for action recognition.Main results. We found that the CMFN of the three actions in the beta band had small-world attributes, among which the beta2 band's small-world was stronger. Moreover, we found that the extracted features were mainly concentrated in the left frontal area, left motor area, occipital lobe, and related muscles, suggesting that the CMFN could be used to assess the coupling differences between the cortex and the muscles that are associated with different hand movements. Overall, our results showed that the beta2 (21-35 Hz) wave is the main information carrier between the cortex and the muscles, and the CMFN can be used in the beta2 band to assess cortico-muscular coupling.Significance. Our study preliminarily explored the CMFN associated with hand movements, providing additional insights regarding the transmission of information between the cortex and the muscles, thereby laying a foundation for future rehabilitation therapy targeting pathological cortical areas in stroke patients.
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Affiliation(s)
- Xugang Xi
- School of Automation, Hangzhou Dianzi University, Hangzhou 310018, People's Republic of China.,Key Laboratory of Brain Machine Collaborative Intelligence of Zhejiang Province, Hangzhou 310018, People's Republic of China
| | - Xiangxiang Wu
- School of Automation, Hangzhou Dianzi University, Hangzhou 310018, People's Republic of China.,Key Laboratory of Brain Machine Collaborative Intelligence of Zhejiang Province, Hangzhou 310018, People's Republic of China
| | - Yun-Bo Zhao
- Department of Automation, University of Science and Technology of China, Hefei, People's Republic of China
| | - Junhong Wang
- School of Automation, Hangzhou Dianzi University, Hangzhou 310018, People's Republic of China.,Key Laboratory of Brain Machine Collaborative Intelligence of Zhejiang Province, Hangzhou 310018, People's Republic of China
| | - Wanzeng Kong
- Key Laboratory of Brain Machine Collaborative Intelligence of Zhejiang Province, Hangzhou 310018, People's Republic of China.,School of Computer Science and Technology, Hangzhou Dianzi University, Hangzhou 310018, People's Republic of China
| | - Zhizeng Luo
- School of Automation, Hangzhou Dianzi University, Hangzhou 310018, People's Republic of China.,Key Laboratory of Brain Machine Collaborative Intelligence of Zhejiang Province, Hangzhou 310018, People's Republic of China
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31
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Krueger J, Reichert C, Dürschmid S, Krauth R, Vogt S, Huchtemann T, Lindquist S, Lamprecht J, Sailer M, Heinze HJ, Hinrichs H, Sweeney-Reed CM. Rehabilitation nach Schlaganfall: Durch Gehirn-Computer-Schnittstelle
vermittelte funktionelle Elektrostimulation. KLIN NEUROPHYSIOL 2020. [DOI: 10.1055/a-1205-7467] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 10/23/2022]
Abstract
ZusammenfassungEine Gehirn-Computer-Schnittstelle (BCI) in der Rehabilitation von
Schlaganfallpatienten ermöglicht die Steuerung einer funktionellen
Elektrostimulation (FES), um eine Muskelkontraktion in der gelähmten
Extremität zum Zeitpunkt der Bewegungsintention durch Erkennung
entsprechender Hirnsignale auszulösen. Es wird angenommen, dass eine
genaue zeitliche Kohärenz zwischen Bewegungsintention und visuellem
sowie propriozeptivem Feedback, ausgelöst durch eine reale Bewegung,
neuroplastische Prozesse begünstigen und eine funktionelle
Verbesserung der Parese bewirken kann. In dieser systematischen
Übersichtsarbeit zu randomisierten kontrollierten Studien wurden die
Datenbanken Pubmed, Scopus und Web of Science durchsucht und von 516
berücksichtigten Publikationen 13 ausgewählt, die auf 7
Studienpopulationen basierten. Ein direkter Vergleich der Studien ist durch
Unterschiede im Studiendesign erschwert. Fünf Studien berichten von
einer verbesserten motorischen Funktion in der BCI-FES-Gruppe, davon zeigen
3 signifikante Unterschiede zwischen der BCI-FES- und der
Kontrollgruppe.
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Affiliation(s)
- Johanna Krueger
- Neurokybernetik und Rehabilitation, Klinik für Neurologie,
Otto-von-Guericke Universität, Magdeburg
- Krankenhaus Barmherziger Brüder Regensburg
| | - Christoph Reichert
- Abteilung Verhaltensneurologie, Leibniz Institut für
Neurobiologie (LIN), Magdeburg
| | - Stefan Dürschmid
- Abteilung Verhaltensneurologie, Leibniz Institut für
Neurobiologie (LIN), Magdeburg
| | - Richard Krauth
- Neurokybernetik und Rehabilitation, Klinik für Neurologie,
Otto-von-Guericke Universität, Magdeburg
| | - Susanne Vogt
- Klinik für Neurologie, Otto-von-Guericke Universität,
Magdeburg
| | | | | | - Juliane Lamprecht
- MEDIAN Klinik NRZ Magdeburg, MEDIAN Klinik Flechtingen
- An-Institut für Neurorehabilitation, Otto-von-Guericke
Universität, Magdeburg
| | - Michael Sailer
- MEDIAN Klinik NRZ Magdeburg, MEDIAN Klinik Flechtingen
- An-Institut für Neurorehabilitation, Otto-von-Guericke
Universität, Magdeburg
| | - Hans-Jochen Heinze
- Abteilung Verhaltensneurologie, Leibniz Institut für
Neurobiologie (LIN), Magdeburg
- Klinik für Neurologie, Otto-von-Guericke Universität,
Magdeburg
- Deutsches Zentrum für Neurodegenerative Erkrankungen (DZNE),
Magdeburg
| | - Hermann Hinrichs
- Abteilung Verhaltensneurologie, Leibniz Institut für
Neurobiologie (LIN), Magdeburg
- Klinik für Neurologie, Otto-von-Guericke Universität,
Magdeburg
- Deutsches Zentrum für Neurodegenerative Erkrankungen (DZNE),
Magdeburg
- Center for Behavioral Brain Sciences (CBBS), Magdeburg
- Forschungscampus STIMULATE, Magdeburg
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Marin-Pardo O, Laine CM, Rennie M, Ito KL, Finley J, Liew SL. A Virtual Reality Muscle-Computer Interface for Neurorehabilitation in Chronic Stroke: A Pilot Study. SENSORS 2020; 20:s20133754. [PMID: 32635550 PMCID: PMC7374440 DOI: 10.3390/s20133754] [Citation(s) in RCA: 13] [Impact Index Per Article: 3.3] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Received: 05/28/2020] [Revised: 07/01/2020] [Accepted: 07/01/2020] [Indexed: 12/11/2022]
Abstract
Severe impairment of limb movement after stroke can be challenging to address in the chronic stage of stroke (e.g., greater than 6 months post stroke). Recent evidence suggests that physical therapy can still promote meaningful recovery after this stage, but the required high amount of therapy is difficult to deliver within the scope of standard clinical practice. Digital gaming technologies are now being combined with brain–computer interfaces to motivate engaging and frequent exercise and promote neural recovery. However, the complexity and expense of acquiring brain signals has held back widespread utilization of these rehabilitation systems. Furthermore, for people that have residual muscle activity, electromyography (EMG) might be a simpler and equally effective alternative. In this pilot study, we evaluate the feasibility and efficacy of an EMG-based variant of our REINVENT virtual reality (VR) neurofeedback rehabilitation system to increase volitional muscle activity while reducing unintended co-contractions. We recruited four participants in the chronic stage of stroke recovery, all with severely restricted active wrist movement. They completed seven 1-hour training sessions during which our head-mounted VR system reinforced activation of the wrist extensor muscles without flexor activation. Before and after training, participants underwent a battery of clinical and neuromuscular assessments. We found that training improved scores on standardized clinical assessments, equivalent to those previously reported for brain–computer interfaces. Additionally, training may have induced changes in corticospinal communication, as indexed by an increase in 12–30 Hz corticomuscular coherence and by an improved ability to maintain a constant level of wrist muscle activity. Our data support the feasibility of using muscle–computer interfaces in severe chronic stroke, as well as their potential to promote functional recovery and trigger neural plasticity.
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Affiliation(s)
- Octavio Marin-Pardo
- Department of Biomedical Engineering, University of Southern California, Los Angeles, CA 90089, USA; (O.M.-P.); (J.F.)
| | - Christopher M. Laine
- Chan Division of Occupational Science and Occupational Therapy, University of Southern California, Los Angeles, CA 90089, USA; (C.M.L.); (M.R.); (K.L.I.)
| | - Miranda Rennie
- Chan Division of Occupational Science and Occupational Therapy, University of Southern California, Los Angeles, CA 90089, USA; (C.M.L.); (M.R.); (K.L.I.)
| | - Kaori L. Ito
- Chan Division of Occupational Science and Occupational Therapy, University of Southern California, Los Angeles, CA 90089, USA; (C.M.L.); (M.R.); (K.L.I.)
| | - James Finley
- Department of Biomedical Engineering, University of Southern California, Los Angeles, CA 90089, USA; (O.M.-P.); (J.F.)
- Division of Biokinesiology and Physical Therapy, University of Southern California, Los Angeles, CA 90089, USA
| | - Sook-Lei Liew
- Department of Biomedical Engineering, University of Southern California, Los Angeles, CA 90089, USA; (O.M.-P.); (J.F.)
- Chan Division of Occupational Science and Occupational Therapy, University of Southern California, Los Angeles, CA 90089, USA; (C.M.L.); (M.R.); (K.L.I.)
- Division of Biokinesiology and Physical Therapy, University of Southern California, Los Angeles, CA 90089, USA
- Correspondence:
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Gennaro F, Maino P, Kaelin-Lang A, De Bock K, de Bruin ED. Corticospinal Control of Human Locomotion as a New Determinant of Age-Related Sarcopenia: An Exploratory Study. J Clin Med 2020; 9:E720. [PMID: 32155951 PMCID: PMC7141202 DOI: 10.3390/jcm9030720] [Citation(s) in RCA: 5] [Impact Index Per Article: 1.3] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/21/2020] [Revised: 02/25/2020] [Accepted: 03/02/2020] [Indexed: 12/11/2022] Open
Abstract
Sarcopenia is a muscle disease listed within the ICD-10 classification. Several operational definitions have been created for sarcopenia screening; however, an international consensus is lacking. The Centers for Disease Control and Prevention have recently recognized that sarcopenia detection requires improved diagnosis and screening measures. Mounting evidence hints towards changes in the corticospinal communication system where corticomuscular coherence (CMC) reflects an effective mechanism of corticospinal interaction. CMC can be assessed during locomotion by means of simultaneously measuring Electroencephalography (EEG) and Electromyography (EMG). The aim of this study was to perform sarcopenia screening in community-dwelling older adults and explore the possibility of using CMC assessed during gait to discriminate between sarcopenic and non-sarcopenic older adults. Receiver Operating Characteristic (ROC) curves showed high sensitivity, precision and accuracy of CMC assessed from EEG Cz sensor and EMG sensors located over Musculus Vastus Medialis [Cz-VM; AUC (95.0%CI): 0.98 (0.92-1.04), sensitivity: 1.00, 1-specificity: 0.89, p < 0.001] and with Musculus Biceps Femoris [Cz-BF; AUC (95.0%CI): 0.86 (0.68-1.03), sensitivity: 1.00, 1-specificity: 0.70, p < 0.001]. These muscles showed significant differences with large magnitude of effect between sarcopenic and non-sarcopenic older adults [Hedge's g (95.0%CI): 2.2 (1.3-3.1), p = 0.005 and Hedge's g (95.0%CI): 1.5 (0.7-2.2), p = 0.010; respectively]. The novelty of this exploratory investigation is the hint toward a novel possible determinant of age-related sarcopenia, derived from corticospinal control of locomotion and shown by the observed large differences in CMC when sarcopenic and non-sarcopenic older adults are compared. This, in turn, might represent in future a potential treatment target to counteract sarcopenia as well as a parameter to monitor the progression of the disease and/or the potential recovery following other treatment interventions.
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Affiliation(s)
- Federico Gennaro
- Department of Health Sciences and Technology, Institute of Human Movement Sciences and Sport, ETH Zurich, 8093 Zurich, Switzerland; (K.D.B.); (E.D.d.B.)
| | - Paolo Maino
- Pain Management Center, Neurocenter of Southern Switzerland, Regional Hospital of Lugano, 6962 Lugano, Switzerland;
| | - Alain Kaelin-Lang
- Neurocenter of Southern Switzerland, Regional Hospital of Lugano, 6900 Lugano, Switzerland;
- Faculty of Biomedical Sciences, Università della Svizzera Italiana, 6900 Lugano, Switzerland
- Medical faculty, University of Bern, 3008 Bern, Switzerland
| | - Katrien De Bock
- Department of Health Sciences and Technology, Institute of Human Movement Sciences and Sport, ETH Zurich, 8093 Zurich, Switzerland; (K.D.B.); (E.D.d.B.)
| | - Eling D. de Bruin
- Department of Health Sciences and Technology, Institute of Human Movement Sciences and Sport, ETH Zurich, 8093 Zurich, Switzerland; (K.D.B.); (E.D.d.B.)
- Department of Neurobiology, Division of Physiotherapy, Care Sciences and Society, Karolinska Institutet, 171 77 Stockholm, Sweden
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Huang H, Chen L, Mao G, Bach J, Xue Q, Han F, Guo X, Otom A, Chernykh E, Alvarez E, Bryukhovetskiy A, Sarnowaska A, He X, Dimitrijevic M, Shanti I, von Wild K, Ramón-Cueto A, Alzoubi Z, Moviglia G, Mobasheri H, Alzoubi A, Zhang W. The 2019 yearbook of Neurorestoratology. JOURNAL OF NEURORESTORATOLOGY 2020. [DOI: 10.26599/jnr.2020.9040004] [Citation(s) in RCA: 14] [Impact Index Per Article: 3.5] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/08/2022] Open
Abstract
Time is infinite movement in constant motion. We are glad to see that Neurorestoratology, a new discipline, has grown into a rich field involving many global researchers in recent years. In this 2019 yearbook of Neurorestoratology, we introduce the most recent advances and achievements in this field, including findings on the pathogenesis of neurological diseases, neurorestorative mechanisms, and clinical therapeutic achievements globally. Many patients have benefited from treatments involving cell therapies, neurostimulation/neuromodulation, brain–computer interface, neurorestorative surgery or pharmacy, and many others. Clinical physicians can refer to this yearbook with the latest knowledge and apply it to clinical practice.
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Farahat A, Reichert C, Sweeney-Reed CM, Hinrichs H. Convolutional neural networks for decoding of covert attention focus and saliency maps for EEG feature visualization. J Neural Eng 2019; 16:066010. [PMID: 31416059 DOI: 10.1088/1741-2552/ab3bb4] [Citation(s) in RCA: 32] [Impact Index Per Article: 6.4] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/12/2022]
Abstract
OBJECTIVE Convolutional neural networks (CNNs) have proven successful as function approximators and have therefore been used for classification problems including electroencephalography (EEG) signal decoding for brain-computer interfaces (BCI). Artificial neural networks, however, are considered black boxes, because they usually have thousands of parameters, making interpretation of their internal processes challenging. Here we systematically evaluate the use of CNNs for EEG signal decoding and investigate a method for visualizing the CNN model decision process. APPROACH We developed a CNN model to decode the covert focus of attention from EEG event-related potentials during object selection. We compared the CNN and the commonly used linear discriminant analysis (LDA) classifier performance, applied to datasets with different dimensionality, and analyzed transfer learning capacity. Moreover, we validated the impact of single model components by systematically altering the model. Furthermore, we investigated the use of saliency maps as a tool for visualizing the spatial and temporal features driving the model output. MAIN RESULTS The CNN model and the LDA classifier achieved comparable accuracy on the lower-dimensional dataset, but CNN exceeded LDA performance significantly on the higher-dimensional dataset (without hypothesis-driven preprocessing), achieving an average decoding accuracy of 90.7% (chance level = 8.3%). Parallel convolutions, tanh or ELU activation functions, and dropout regularization proved valuable for model performance, whereas the sequential convolutions, ReLU activation function, and batch normalization components reduced accuracy or yielded no significant difference. Saliency maps revealed meaningful features, displaying the typical spatial distribution and latency of the P300 component expected during this task. SIGNIFICANCE Following systematic evaluation, we provide recommendations for when and how to use CNN models in EEG decoding. Moreover, we propose a new approach for investigating the neural correlates of a cognitive task by training CNN models on raw high-dimensional EEG data and utilizing saliency maps for relevant feature extraction.
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Affiliation(s)
- Amr Farahat
- Neurocybernetics and Rehabiliation Research Group, Department of Neurology, Otto-von-Guericke University Hospital, Leipziger Str. 44, 39120 Magdeburg, Germany
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