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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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Zhang J, Wang M, Alam M, Zheng YP, Ye F, Hu X. Effects of non-invasive cervical spinal cord neuromodulation by trans-spinal electrical stimulation on cortico-muscular descending patterns in upper extremity of chronic stroke. Front Bioeng Biotechnol 2024; 12:1372158. [PMID: 38576448 PMCID: PMC10991759 DOI: 10.3389/fbioe.2024.1372158] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/17/2024] [Accepted: 03/11/2024] [Indexed: 04/06/2024] Open
Abstract
Background: Trans-spinal electrical stimulation (tsES) to the intact spinal cord poststroke may modulate the cortico-muscular control in stroke survivors with diverse lesions in the brain. This work aimed to investigate the immediate effects of tsES on the cortico-muscular descending patterns during voluntary upper extremity (UE) muscle contractions by analyzing cortico-muscular coherence (CMCoh) and electromyography (EMG) in people with chronic stroke. Methods: Twelve chronic stroke participants were recruited to perform wrist-hand extension and flexion tasks at submaximal levels of voluntary contraction for the corresponding agonist flexors and extensors. During the tasks, the tsES was delivered to the cervical spinal cord with rectangular biphasic pulses. Electroencephalography (EEG) data were collected from the sensorimotor cortex, and the EMG data were recorded from both distal and proximal UE muscles. The CMCoh, laterality index (LI) of the peak CMCoh, and EMG activation level parameters under both non-tsES and tsES conditions were compared to evaluate the immediate effects of tsES on the cortico-muscular descending pathway. Results: The CMCoh and LI of peak CMCoh in the agonist distal muscles showed significant increases (p < 0.05) during the wrist-hand extension and flexion tasks with the application of tsES. The EMG activation levels of the antagonist distal muscle during wrist-hand extension were significantly decreased (p < 0.05) with tsES. Additionally, the proximal UE muscles exhibited significant decreases (p < 0.05) in peak CMCoh and EMG activation levels by applying tsES. There was a significant increase (p < 0.05) in LI of peak CMCoh of proximal UE muscles during tsES. Conclusion: The cervical spinal cord neuromodulation via tsES enhanced the residual descending excitatory control, activated the local inhibitory circuits within the spinal cord, and reduced the cortical and proximal muscular compensatory effects. These results suggested the potential of tsES as a supplementary input for improving UE motor functions in stroke rehabilitation.
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Affiliation(s)
- Jianing Zhang
- Department of Biomedical Engineering, The Hong Kong Polytechnic University, Kowloon, China
| | - Maner Wang
- Department of Biomedical Engineering, The Hong Kong Polytechnic University, Kowloon, China
| | - Monzurul Alam
- Department of Biomedical Engineering, The Hong Kong Polytechnic University, Kowloon, China
| | - Yong-Ping Zheng
- Department of Biomedical Engineering, The Hong Kong Polytechnic University, Kowloon, China
| | - Fuqiang Ye
- Department of Biomedical Engineering, The Hong Kong Polytechnic University, Kowloon, China
| | - Xiaoling Hu
- Department of Biomedical Engineering, The Hong Kong Polytechnic University, Kowloon, China
- Research Institute for Smart Ageing (RISA), Hong Kong SAR, China
- Research Centre of Data Science and Artificial Intelligence (RC-DSAI), Hong Kong SAR, China
- Joint Research Centre for Biosensing and Precision Theranostics, Hong Kong SAR, China
- University Research Facility in Behavioral and Systems Neuroscience (UBSN), The Hong Kong Polytechnic University, Hong Kong SAR, China
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3
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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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Lin L, Qing W, Huang Y, Ye F, Rong W, Li W, Jiao J, Hu X. Comparison of Immediate Neuromodulatory Effects between Focal Vibratory and Electrical Sensory Stimulations after Stroke. Bioengineering (Basel) 2024; 11:286. [PMID: 38534560 DOI: 10.3390/bioengineering11030286] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/21/2024] [Revised: 03/14/2024] [Accepted: 03/15/2024] [Indexed: 03/28/2024] Open
Abstract
Focal vibratory stimulation (FVS) and neuromuscular electrical stimulation (NMES) are promising technologies for sensory rehabilitation after stroke. However, the differences between these techniques in immediate neuromodulatory effects on the poststroke cortex are not yet fully understood. In this research, cortical responses in persons with chronic stroke (n = 15) and unimpaired controls (n = 15) were measured by whole-brain electroencephalography (EEG) when FVS and NMES at different intensities were applied transcutaneously to the forearm muscles. Both FVS and sensory-level NMES induced alpha and beta oscillations in the sensorimotor cortex after stroke, significantly exceeding baseline levels (p < 0.05). These oscillations exhibited bilateral sensory deficiency, early adaptation, and contralesional compensation compared to the control group. FVS resulted in a significantly faster P300 response (p < 0.05) and higher theta oscillation (p < 0.05) compared to NMES. The beta desynchronization over the contralesional frontal-parietal area remained during NMES (p > 0.05), but it was significantly weakened during FVS (p < 0.05) after stroke. The results indicated that both FVS and NMES effectively activated the sensorimotor cortex after stroke. However, FVS was particularly effective in eliciting transient involuntary attention, while NMES primarily fostered the cortical responses of the targeted muscles in the contralesional motor cortex.
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Affiliation(s)
- Legeng Lin
- Department of Biomedical Engineering, The Hong Kong Polytechnic University, Hong Kong, China
- Research Institute for Smart Ageing (RISA), The Hong Kong Polytechnic University, Hong Kong, China
| | - Wanyi Qing
- Department of Biomedical Engineering, The Hong Kong Polytechnic University, Hong Kong, China
- Research Institute for Smart Ageing (RISA), The Hong Kong Polytechnic University, Hong Kong, China
| | - Yanhuan Huang
- Department of Biomedical Engineering, The Hong Kong Polytechnic University, Hong Kong, China
- Research Institute for Smart Ageing (RISA), The Hong Kong Polytechnic University, Hong Kong, China
| | - Fuqiang Ye
- Department of Biomedical Engineering, The Hong Kong Polytechnic University, Hong Kong, China
- Research Institute for Smart Ageing (RISA), The Hong Kong Polytechnic University, Hong Kong, China
| | - Wei Rong
- Department of Biomedical Engineering, The Hong Kong Polytechnic University, Hong Kong, China
| | - Waiming Li
- Department of Biomedical Engineering, The Hong Kong Polytechnic University, Hong Kong, China
| | - Jiao Jiao
- Department of Sport, Physical Education and Health, Hong Kong Baptist University, Hong Kong, China
| | - Xiaoling Hu
- Department of Biomedical Engineering, The Hong Kong Polytechnic University, Hong Kong, China
- Research Institute for Smart Ageing (RISA), The Hong Kong Polytechnic University, Hong Kong, China
- University Research Facility in Behavioral and Systems Neuroscience (UBSN), The Hong Kong Polytechnic University, Hong Kong, China
- Joint Research Centre for Biosensing and Precision Theranostics, The Hong Kong Polytechnic University, Hong Kong, China
- Research Centre on Data Science and Artificial Intelligence, The Hong Kong Polytechnic University, Hong Kong, China
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5
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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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Sarhan SM, Al-Faiz MZ, Takhakh AM. A review on EMG/EEG based control scheme of upper limb rehabilitation robots for stroke patients. Heliyon 2023; 9:e18308. [PMID: 37533980 PMCID: PMC10391943 DOI: 10.1016/j.heliyon.2023.e18308] [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] [Revised: 07/03/2023] [Accepted: 07/13/2023] [Indexed: 08/04/2023] Open
Abstract
Stroke is a common worldwide health problem and a crucial contributor to gained disability. The abilities of people, who are subjected to stroke, to live independently are significantly affected since affected upper limbs' functions are essential for our daily life. This review article focuses on emerging trends in BCI-controlled rehabilitation techniques based on EMG, EEG, or EGM + EEG signals in the last few years. Working on developing rehabilitation robotics, is considered a wealthy scientific area for researchers in the last period. There is a significant advantage that the human acquires from the interaction between the machine and his body, rehabilitation for a patient's limb is very important to get the body limb recovery, and this is what is provided mostly by applying robotic devices.
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Affiliation(s)
- Saad M. Sarhan
- Department of Biomedical Engineering, College of Engineering, Al-Nahrain University, Baghdad, Iraq
| | - Mohammed Z. Al-Faiz
- Department of Control and Computer, College of Information Engineering, Al-Nahrain University, Baghdad, Iraq
| | - Ayad M. Takhakh
- Department of Biomechanics, College of Engineering, Al-Nahrain University, Baghdad, Iraq
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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] [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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Kukkar KK, Rao N, Huynh D, Shah S, Contreras-Vidal JL, Parikh PJ. Task-dependent Alteration in Delta Band Corticomuscular Coherence during Standing in Chronic Stroke Survivors. MEDRXIV : THE PREPRINT SERVER FOR HEALTH SCIENCES 2023:2023.07.17.23292472. [PMID: 37503096 PMCID: PMC10371181 DOI: 10.1101/2023.07.17.23292472] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 07/29/2023]
Abstract
Balance control is an important indicator of mobility and independence in activities of daily living. How the changes in functional integrity of corticospinal tract due to stroke affects the maintenance of upright stance remains to be known. We investigated the changes in functional coupling between the cortex and lower limb muscles during a challenging balance task over multiple frequency bands in chronic stroke survivors. Eleven stroke patients and nine healthy controls performed a challenging balance task. They stood on a computerized platform with/without somatosensory input distortion created by sway-referencing the support surface, thereby varying the difficulty levels of the task. We computed corticomuscular coherence between Cz (electroencephalography) and leg muscles and assessed balance performance using Berg Balance scale (BBS), Timed-up and go (TUG) and center of pressure (COP) measures. We found lower delta frequency band coherence in stroke patients when compared with healthy controls under medium difficulty condition for distal but not proximal leg muscles. For both groups, we found similar coherence at other frequency bands. On BBS and TUG, stroke patients showed poor balance. However, similar group differences were not consistently observed across COP measures. The presence of distal versus proximal effect suggests differences in the (re)organization of the corticospinal connections across the two muscles groups for balance control. We argue that the observed group difference in the delta coherence might be due to altered mechanisms for the detection of somatosensory modulation resulting from sway-referencing of the support platform for balance control.
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Affiliation(s)
- Komal K Kukkar
- Center for Neuromotor and Biomechanics Research, Department of Health and Human Performance, University of Houston, Houston, Texas
| | - Nishant Rao
- Haskins Laboratories, Yale University, New Haven, Connecticut
| | - Diana Huynh
- Center for Neuromotor and Biomechanics Research, Department of Health and Human Performance, University of Houston, Houston, Texas
| | - Sheel Shah
- Center for Neuromotor and Biomechanics Research, Department of Health and Human Performance, University of Houston, Houston, Texas
| | - Jose L Contreras-Vidal
- Laboratory for Noninvasive Brain-Machine Interface Systems, Department of Electrical and Computer Engineering, University of Houston, Houston, Texas
| | - Pranav J Parikh
- Center for Neuromotor and Biomechanics Research, Department of Health and Human Performance, University of Houston, Houston, Texas
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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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11
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Parr JVV, Hodson-Tole E, Wood G. Short report presenting preliminary evidence of impaired corticomuscular coherence in an individual with Developmental Coordination Disorder. RESEARCH IN DEVELOPMENTAL DISABILITIES 2022; 131:104355. [PMID: 36191396 DOI: 10.1016/j.ridd.2022.104355] [Citation(s) in RCA: 5] [Impact Index Per Article: 2.5] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 01/12/2022] [Revised: 09/21/2022] [Accepted: 09/26/2022] [Indexed: 06/16/2023]
Abstract
BACKGROUND It has been suggested that developmental coordination disorder (DCD) could be caused by a 'dysconnection' in brain and skeletal muscle communication. To date no previous work has examined the integrity of this neuromuscular process in individuals with DCD. AIMS To conduct a feasibility study for measuring functional connectivity of the brain and muscle in an individual with DCD using corticomuscular coherence (CMC). METHODS AND PROCEDURES An individual with DCD and a typically developing (TD) participant completed a series of sustained 5-second voluntary isometric hand contractions (15 ± 5 % MVC) on a handheld dynamometer under both single and dual task (i.e., counting backwards) conditions. EEG, EMG and force data were collected. OUTCOMES AND RESULTS The participant with DCD displayed poorer force steadiness and higher mental demand compared to the TD participant and in dual task conditions. The TD participant displayed a commonly observed pattern of CMC that was highly localised over the contralateral hand area, the DCD participant displayed a less localised CMC across cortical regions. CONCLUSIONS AND IMPLICATIONS These findings support the feasibility of measuring CMC in DCD populations and offer some, albeit preliminary, evidence of impaired communication between the brain and muscles in these individuals.
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Affiliation(s)
- J V V Parr
- Research Centre for Musculoskeletal Science and Sports Medicine, Department of Sport and Exercise Science, Manchester Metropolitan University, Manchester, UK
| | - E Hodson-Tole
- Research Centre for Musculoskeletal Science and Sports Medicine, Department of Life Sciences, Manchester Metropolitan University, Manchester, UK
| | - G Wood
- Research Centre for Musculoskeletal Science and Sports Medicine, Department of Sport and Exercise Science, Manchester Metropolitan University, Manchester, UK.
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12
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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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13
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Milani G, Antonioni A, Baroni A, Malerba P, Straudi S. Relation Between EEG Measures and Upper Limb Motor Recovery in Stroke Patients: A Scoping Review. Brain Topogr 2022; 35:651-666. [PMID: 36136166 DOI: 10.1007/s10548-022-00915-y] [Citation(s) in RCA: 9] [Impact Index Per Article: 4.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/13/2022] [Accepted: 09/04/2022] [Indexed: 11/25/2022]
Abstract
Current clinical practice does not leverage electroencephalography (EEG) measurements in stroke patients, despite its potential to contribute to post-stroke recovery predictions. We review the literature on the effectiveness of various quantitative and qualitative EEG-based measures after stroke as a tool to predict upper limb motor outcome, in relation to stroke timeframe and applied experimental tasks. Moreover, we aim to provide guidance on the use of EEG in the assessment of upper limb motor recovery after stroke, suggesting a high potential for some metrics in the appropriate context. We identified relevant papers (N = 16) from databases ScienceDirect, Web of Science and MEDLINE, and assessed their methodological quality with the Joanna Briggs Institute (JBI) Critical Appraisal. We applied the Preferred Reporting Systems for Systematic Reviews and Meta-Analyses Extension for Scoping Reviews (PRISMA-ScR) Framework. Identified works used EEG to identify properties including event-related activation, spectral power in physiologically relevant bands, symmetry in brain dynamics, functional connectivity, cortico-muscular coherence and rhythmic coordination. EEG was acquired in resting state or in relation to behavioural conditions. Motor outcome was mainly evaluated with the Upper Limb Fugl-Meyer Assessment. Despite great variability in the literature, data suggests that the most promising EEG quantifiers for predicting post-stroke motor outcome are event-related measures. Measures of spectral power in physiologically relevant bands and measures of brain symmetry also show promise. We suggest that EEG measures may improve our understanding of stroke brain dynamics during recovery, and contribute to establishing a functional prognosis and choosing the rehabilitation approach.
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Affiliation(s)
- Giada Milani
- IIT@Unife Center for Translational Neurophysiology, Istituto Italiano di Tecnologia, Ferrara, Italy.,Department of Neuroscience and Rehabilitation, Ferrara University Hospital, Ferrara, Italy
| | - Annibale Antonioni
- Unit of Clinical Neurology, Department of Neuroscience and Rehabilitation, University of Ferrara, Ferrara, Italy
| | - Andrea Baroni
- Department of Neuroscience and Rehabilitation, Ferrara University Hospital, Ferrara, Italy
| | - Paola Malerba
- Battelle Center for Mathematical Medicine and Center for Biobehavioral Health, The Ohio State University, Columbus, OH, USA
| | - Sofia Straudi
- Department of Neuroscience and Rehabilitation, Ferrara University Hospital, Ferrara, Italy. .,Department of Neuroscience and Rehabilitation, University of Ferrara, Via Luigi Borsari 46, 44121, Ferrara, Italy.
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14
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Guo Z, Zhou S, Ji K, Zhuang Y, Song J, Nam C, Hu X, Zheng Y. Corticomuscular integrated representation of voluntary motor effort in robotic control for wrist-hand rehabilitation after stroke. J Neural Eng 2022; 19. [PMID: 35193124 DOI: 10.1088/1741-2552/ac5757] [Citation(s) in RCA: 7] [Impact Index Per Article: 3.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/27/2021] [Accepted: 02/22/2022] [Indexed: 11/12/2022]
Abstract
OBJECTIVE The central-to-peripheral voluntary motor effort (VME) in physical practice of the paretic limb is a dominant force for driving functional neuroplasticity on motor restoration post-stroke. However, current rehabilitation robots isolated the central and peripheral involvements in the control design, resulting in limited rehabilitation effectiveness. The purpose of this study was to design a corticomuscular coherence (CMC) and electromyography (EMG)-driven (CMC-EMG-driven) system with central-and-peripheral integrated representation of VME for wrist-hand rehabilitation after stroke. APPROACH The CMC-EMG-driven control was developed in a neuromuscular electrical stimulation (NMES)-robot system, i.e., CMC-EMG-driven NMES-robot system, to instruct and assist the wrist-hand extension and flexion in persons after stroke. A pilot single-group trial of 20 training sessions was conducted with the developed system to assess the feasibility for wrist-hand practice on the chronic strokes (n=16). The rehabilitation effectiveness was evaluated through clinical assessments, CMC, and EMG activation levels. MAIN RESULTS The trigger success rate and laterality index (LI) of CMC were significantly increased in wrist-hand extension across training sessions (p<0.05). After the training, significant improvements in the target wrist-hand joints and suppressed compensation from the proximal shoulder-elbow joints were observed through the clinical scores and EMG activation levels (p<0.05). The central-to-peripheral VME distribution across upper extremity (UE) muscles was also significantly improved, as revealed by the CMC values (p<0.05). SIGNIFICANCE Precise wrist-hand rehabilitation was achieved by the developed system, presenting suppressed cortical and muscular compensation from the contralesional hemisphere and the proximal UE, and improved distribution of the central-and-peripheral VME on UE muscles.
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Affiliation(s)
- Ziqi Guo
- The Hong Kong Polytechnic University, Rm S107a, Dept. of BME, PolyU, Hung H, Hung Hom, Kowloon, Kowloon, Nil, HONG KONG
| | - Sa Zhou
- The Hong Kong Polytechnic University, Rm S107a, Dept. of BME, PolyU, Hung H, Hung Hom, Kowloon, Hong Kong, Kowloon, HONG KONG
| | - Kailai Ji
- The Hong Kong Polytechnic University, Dept. of BME, PolyU, Hung H, Hung Hom, Kowloon, Kowloon, Hong Kong, HONG KONG
| | - Yongqi Zhuang
- Biomedical Engineering, Hong Kong Polytechnic University, BME PolyU, Kowloon, HONG KONG
| | - Jie Song
- The Hong Kong Polytechnic University, Rm S107a, Dept. of BME, PolyU, Hung H, Hung Hom, Kowloon, Hong Kong, Kowloon, Nil, HONG KONG
| | - Chingyi Nam
- The Hong Kong Polytechnic University, Rm S107a, Dept. of BME, PolyU, Hung H, Hung Hom, Kowloon, Hong Kong, Kowloon, Nil, HONG KONG
| | - Xiaoling Hu
- Biomedical Engineering, Hong Kong Polytechnic University, Rm ST420, Dept. of BME, PolyU, Hung H, Hung Hom, Kowloon, Hong Kong, Kowloon, HONG KONG
| | - Yongping Zheng
- Biomedical Engineering, The Hong Kong Polytechnic University, BME PolyU, Hong Kong, Nil, CHINA
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15
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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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16
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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: 12] [Impact Index Per Article: 4.0] [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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17
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Zhou S, Guo Z, Wong K, Zhu H, Huang Y, Hu X, Zheng YP. Pathway-specific cortico-muscular coherence in proximal-to-distal compensation during fine motor control of finger extension after stroke. J Neural Eng 2021; 18. [PMID: 34428752 DOI: 10.1088/1741-2552/ac20bc] [Citation(s) in RCA: 8] [Impact Index Per Article: 2.7] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/15/2021] [Accepted: 08/24/2021] [Indexed: 11/12/2022]
Abstract
Objective.Proximal-to-distal compensation is commonly observed in the upper extremity (UE) after a stroke, mainly due to the impaired fine motor control in hand joints. However, little is known about its related neural reorganization. This study investigated the pathway-specific corticomuscular interaction in proximal-to-distal UE compensation during fine motor control of finger extension post-stroke by directed corticomuscular coherence (dCMC).Approach.We recruited 14 chronic stroke participants and 11 unimpaired controls. Electroencephalogram (EEG) from the sensorimotor area was concurrently recorded with electromyography (EMG) from extensor digitorum (ED), flexor digitorum (FD), triceps brachii (TRI) and biceps brachii (BIC) muscles in both sides of the stroke participants and in the dominant (right) side of the controls during the unilateral isometric finger extension at 20% maximal voluntary contractions. The dCMC was analyzed in descending (EEG → EMG) and ascending pathways (EMG → EEG) via the directed coherence. It was also analyzed in stable (segments with higher EMG stability) and less-stable periods (segments with lower EMG stability) subdivided from the whole movement period to investigate the fine motor control. Finally, the corticomuscular conduction time was estimated by dCMC phase delay.Main results.The affected limb had significantly lower descending dCMC in distal UE (ED and FD) than BIC (P< 0.05). It showed the descending dominance (significantly higher descending dCMC than the ascending,P< 0.05) in proximal UE (BIC and TRI) rather than the distal UE as in the controls. In the less-stable period, the affected limb had significantly lower EMG stability but higher ascending dCMC (P< 0.05) in distal UE than the controls. Furthermore, significantly prolonged descending conduction time (∼38.8 ms) was found in ED in the affected limb than the unaffected (∼26.94 ms) and control limbs (∼25.74 ms) (P< 0.05).Significance.The proximal-to-distal UE compensation in fine motor control post-stroke exhibited altered descending dominance from the distal to proximal UE, increased ascending feedbacks from the distal UE for fine motor control, and prolonged descending conduction time in the agonist muscle.
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Affiliation(s)
- Sa Zhou
- Department of Biomedical Engineering, The Hong Kong Polytechnic University, Hong Kong, People's Republic of China.,University Research Facility in Behavioural and Systems Neuroscience (UBSN), The Hong Kong Polytechnic University, Hong Kong, People's Republic of China
| | - Ziqi Guo
- Department of Biomedical Engineering, The Hong Kong Polytechnic University, Hong Kong, People's Republic of China.,University Research Facility in Behavioural and Systems Neuroscience (UBSN), The Hong Kong Polytechnic University, Hong Kong, People's Republic of China
| | - Kiufung Wong
- Department of Biomedical Engineering, The Hong Kong Polytechnic University, Hong Kong, People's Republic of China.,University Research Facility in Behavioural and Systems Neuroscience (UBSN), The Hong Kong Polytechnic University, Hong Kong, People's Republic of China
| | - Hanlin Zhu
- Department of Biomedical Engineering, The Hong Kong Polytechnic University, Hong Kong, People's Republic of China.,University Research Facility in Behavioural and Systems Neuroscience (UBSN), The Hong Kong Polytechnic University, Hong Kong, People's Republic of China
| | - Yanhuan Huang
- Department of Biomedical Engineering, The Hong Kong Polytechnic University, Hong Kong, People's Republic of China.,University Research Facility in Behavioural and Systems Neuroscience (UBSN), The Hong Kong Polytechnic University, Hong Kong, People's Republic of China
| | - Xiaoling Hu
- Department of Biomedical Engineering, The Hong Kong Polytechnic University, Hong Kong, People's Republic of China.,University Research Facility in Behavioural and Systems Neuroscience (UBSN), The Hong Kong Polytechnic University, Hong Kong, People's Republic of China.,The Hong Kong Polytechnic University Shenzhen Research Institute, Shenzhen, People's Republic of China
| | - Yong-Ping Zheng
- Department of Biomedical Engineering, The Hong Kong Polytechnic University, Hong Kong, People's Republic of China.,University Research Facility in Behavioural and Systems Neuroscience (UBSN), The Hong Kong Polytechnic University, Hong Kong, People's Republic of China
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18
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Liu J, Wang J, Tan G, Sheng Y, Chang H, Xie Q, Liu H. Correlation Evaluation of Functional Corticomuscular Coupling With Abnormal Muscle Synergy After Stroke. IEEE Trans Biomed Eng 2021; 68:3261-3272. [PMID: 33764872 DOI: 10.1109/tbme.2021.3068997] [Citation(s) in RCA: 8] [Impact Index Per Article: 2.7] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/09/2022]
Abstract
OBJECTIVE While neuroplasticity and functional reorganization during motor recovery can be indirectly reflected and evaluated by functional corticomuscular coupling (fCMC), little work has been published regarding the cortical origin of abnormal muscle synergy and compensatory mechanism in the separation movement of stroke patients. METHODS In this study, we proposed to use extended partial directed coherence (ePDC) combined with an optimal spatial filtering approach to estimate fCMC in stroke patients and healthy controls, and further established muscle synergy model (MSM) to jointly explore the modulation mechanism between cortex and muscles. RESULTS Compared to healthy controls, stroke patients had significantly reduced coupling strength in both descending and ascending pathway. Moreover, the MSM were abnormal with high variability and low similarity in the separation stage of stroke patients. Further exploration of the positive relationship between fCMC characteristics and MSM parameters proved the possibility of using fCMC-MSM-based correlation indicator to evaluate abnormality of the cortical related synergy movement as well as the rehabilitation level of stroke patients. CONCLUSION We developed a computational procedure to evaluate the correlation between fCMC and MSM in stroke patients. SIGNIFICANCE This article provides a quantitative evaluation metrics based on fCMC to reveal the deficits during poststroke motor restoration and a promising approach to help patients correct abnormal movement habits, paving the way for neurophysiological assessment of neuromuscular control in conjunction with clinical scores.
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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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