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Birbaumer N. "Your Thoughts are (were) Free!": Brain-Computer-Interfaces, Neurofeedback, Detection of Deception, and the Future of Mind-Reading. Appl Psychophysiol Biofeedback 2024:10.1007/s10484-024-09648-z. [PMID: 38874845 DOI: 10.1007/s10484-024-09648-z] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Accepted: 05/20/2024] [Indexed: 06/15/2024]
Abstract
This review describes the historical developement and rationale of clinically relevant research on neurophysiological "mind reading" paradims: Brain- Computer-Interfaces, detection of deception, brain stimulation and neurofeedback and the clinical applications in drug resistant epilepsy, chronic stroke, and communication with paralyzed locked-in persons. The emphasis lies on completely locked-in patients with amyotrophic lateral sclerosis using non-invasive and invasive brain computer interfaces and neurofeedback to restore verbal communication with the social environment. In the second part of the article we argue that success and failure of neurophysiological "mind reading" paradigms may be explained with a motor theory of thinking and emotion in combination with learning theory. The ethical implications of brain computer interface and neurofeedback approaches, particularly for severe chronic paralysis and loss of communication diseases and decisions on hastened death and euthanasia are discussed.
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Affiliation(s)
- Niels Birbaumer
- Department of Medical Psychology and Behavioral Neurobiology, University of Tübingen, Silcherstrasse 5, 74072, Tübingen, Germany.
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2
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Kantawala B, Emir Hamitoglu A, Nohra L, Abdullahi Yusuf H, Jonathan Isaac K, Shariff S, Nazir A, Soju K, Yenkoyan K, Wojtara M, Uwishema O. Microengineered neuronal networks: enhancing brain-machine interfaces. Ann Med Surg (Lond) 2024; 86:3535-3542. [PMID: 38846893 PMCID: PMC11152794 DOI: 10.1097/ms9.0000000000002130] [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: 11/23/2023] [Accepted: 04/05/2024] [Indexed: 06/09/2024] Open
Abstract
The brain-machine interface (BMI), a crucial conduit between the human brain and computers, holds transformative potential for various applications in neuroscience. This manuscript explores the role of micro-engineered neuronal networks (MNNs) in advancing BMI technologies and their therapeutic applications. As the interdisciplinary collaboration intensifies, the need for innovative and user-friendly BMI technologies becomes paramount. A comprehensive literature review sourced from reputable databases (PubMed Central, Medline, EBSCOhost, and Google Scholar) aided in the foundation of the manuscript, emphasizing the pivotal role of MNNs. This study aims to synthesize and analyze the diverse facets of MNNs in the context of BMI technologies, contributing insights into neural processes, technological advancements, therapeutic potentials, and ethical considerations surrounding BMIs. MNNs, exemplified by dual-mode neural microelectrodes, offer a controlled platform for understanding complex neural processes. Through case studies, we showcase the pivotal role of MNNs in BMI innovation, addressing challenges, and paving the way for therapeutic applications. The integration of MNNs with BMI technologies marks a revolutionary stride in neuroscience, refining brain-computer interactions and offering therapeutic avenues for neurological disorders. Challenges, ethical considerations, and future trends in BMI research necessitate a balanced approach, leveraging interdisciplinary collaboration to ensure responsible and ethical advancements. Embracing the potential of MNNs is paramount for the betterment of individuals with neurological conditions and the broader community.
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Affiliation(s)
- Burhan Kantawala
- Oli Health Magazine Organization, Research and Education, Kigali, Rwanda
- Neuroscience Laboratory, Cobrain Centre, Yerevan State Medical University named after Mkhitar Heratsi, Yerevan, Armenia
| | - Ali Emir Hamitoglu
- Oli Health Magazine Organization, Research and Education, Kigali, Rwanda
- Faculty of Medicine, Namik Kemal University, Tekirdag, Turkey
| | - Lea Nohra
- Oli Health Magazine Organization, Research and Education, Kigali, Rwanda
- Faculty of Medical Science, Lebanese University, Beirut, Lebanon
| | - Hassan Abdullahi Yusuf
- Oli Health Magazine Organization, Research and Education, Kigali, Rwanda
- College of Health science, Faculty of Clinical Sciences Bayero University Kano, Nigeria
| | - Kirumira Jonathan Isaac
- Oli Health Magazine Organization, Research and Education, Kigali, Rwanda
- Faculty of Clinical Medicine and Dentistry, Kampala International University, Uganda
| | - Sanobar Shariff
- Oli Health Magazine Organization, Research and Education, Kigali, Rwanda
- Neuroscience Laboratory, Cobrain Centre, Yerevan State Medical University named after Mkhitar Heratsi, Yerevan, Armenia
| | - Abubakar Nazir
- Oli Health Magazine Organization, Research and Education, Kigali, Rwanda
- Department of Medicine, King Edward Medical University, Pakistan
| | - Kevin Soju
- Oli Health Magazine Organization, Research and Education, Kigali, Rwanda
- Faculty of Medicine, Christian Medical College, Ludhiana, India
| | - Konstantin Yenkoyan
- Neuroscience Laboratory, Cobrain Centre, Yerevan State Medical University named after Mkhitar Heratsi, Yerevan, Armenia
- Department of Biochemistry, Yerevan State Medical University named after Mkhitar Heratsi, Yerevan, Armenia
| | - Magda Wojtara
- Oli Health Magazine Organization, Research and Education, Kigali, Rwanda
| | - Olivier Uwishema
- Oli Health Magazine Organization, Research and Education, Kigali, Rwanda
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3
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Gangadharan SK, Ramakrishnan S, Paek A, Ravindran A, Prasad VA, Vidal JLC. Characterization of Event Related Desynchronization in Chronic Stroke Using Motor Imagery Based Brain Computer Interface for Upper Limb Rehabilitation. Ann Indian Acad Neurol 2024; 27:297-306. [PMID: 38835164 PMCID: PMC11232817 DOI: 10.4103/aian.aian_1056_23] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/30/2023] [Accepted: 04/02/2024] [Indexed: 06/06/2024] Open
Abstract
OBJECTIVE Motor imagery-based brain-computer interface (MI-BCI) is a promising novel mode of stroke rehabilitation. The current study aims to investigate the feasibility of MI-BCI in upper limb rehabilitation of chronic stroke survivors and also to study the early event-related desynchronization after MI-BCI intervention. METHODS Changes in the characteristics of sensorimotor rhythm modulations in response to a short brain-computer interface (BCI) intervention for upper limb rehabilitation of stroke-disabled hand and normal hand were examined. The participants were trained to modulate their brain rhythms through motor imagery or execution during calibration, and they played a virtual marble game during the feedback session, where the movement of the marble was controlled by their sensorimotor rhythm. RESULTS Ipsilesional and contralesional activities were observed in the brain during the upper limb rehabilitation using BCI intervention. All the participants were able to successfully control the position of the virtual marble using their sensorimotor rhythm. CONCLUSIONS The preliminary results support the feasibility of BCI in upper limb rehabilitation and unveil the capability of MI-BCI as a promising medical intervention. This study provides a strong platform for clinicians to build upon new strategies for stroke rehabilitation by integrating MI-BCI with various therapeutic options to induce neural plasticity and recovery.
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Affiliation(s)
- Sagila K Gangadharan
- Department of Electrical Engineering, Indian Institute of Technology Palakkad, Palakkad, Kerala, India
| | - Subasree Ramakrishnan
- Department of Neurology, National Institute of Mental Health and Neuroscience, Bengaluru, Karnataka, India
| | - Andrew Paek
- Department of Electrical and Computer Engineering, Noninvasive Brain Machine Interface Systems Lab, University of Houston, Houston, USA
| | - Akshay Ravindran
- Department of Electrical and Computer Engineering, Noninvasive Brain Machine Interface Systems Lab, University of Houston, Houston, USA
| | - Vinod A Prasad
- Infocomm Technology Cluster, Singapore Institute of Technology, Singapore
| | - Jose L Contreras Vidal
- Department of Electrical and Computer Engineering, Noninvasive Brain Machine Interface Systems Lab, University of Houston, Houston, USA
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Berger DJ, d’Avella A. Myoelectric control and virtual reality to enhance motor rehabilitation after stroke. Front Bioeng Biotechnol 2024; 12:1376000. [PMID: 38665814 PMCID: PMC11043476 DOI: 10.3389/fbioe.2024.1376000] [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: 01/24/2024] [Accepted: 03/28/2024] [Indexed: 04/28/2024] Open
Abstract
Effective upper-limb rehabilitation for severely impaired stroke survivors is still missing. Recent studies endorse novel motor rehabilitation approaches such as robotic exoskeletons and virtual reality systems to restore the function of the paretic limb of stroke survivors. However, the optimal way to promote the functional reorganization of the central nervous system after a stroke has yet to be uncovered. Electromyographic (EMG) signals have been employed for prosthetic control, but their application to rehabilitation has been limited. Here we propose a novel approach to promote the reorganization of pathological muscle activation patterns and enhance upper-limb motor recovery in stroke survivors by using an EMG-controlled interface to provide personalized assistance while performing movements in virtual reality (VR). We suggest that altering the visual feedback to improve motor performance in VR, thereby reducing the effect of deviations of the actual, dysfunctional muscle patterns from the functional ones, will actively engage patients in motor learning and facilitate the restoration of functional muscle patterns. An EMG-controlled VR interface may facilitate effective rehabilitation by targeting specific changes in the structure of muscle synergies and in their activations that emerged after a stroke-offering the possibility to provide rehabilitation therapies addressing specific individual impairments.
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Affiliation(s)
- Denise Jennifer Berger
- Laboratory of Neuromotor Physiology, IRCCS Fondazione Santa Lucia, Rome, Italy
- Department of Systems Medicine, Centre of Space Bio-medicine, University of Rome Tor Vergata, Rome, Italy
| | - Andrea d’Avella
- Laboratory of Neuromotor Physiology, IRCCS Fondazione Santa Lucia, Rome, Italy
- Department of Biology, University of Rome Tor Vergata, Rome, Italy
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Behboodi A, Kline J, Gravunder A, Phillips C, Parker SM, Damiano DL. Development and evaluation of a BCI-neurofeedback system with real-time EEG detection and electrical stimulation assistance during motor attempt for neurorehabilitation of children with cerebral palsy. Front Hum Neurosci 2024; 18:1346050. [PMID: 38633751 PMCID: PMC11021665 DOI: 10.3389/fnhum.2024.1346050] [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: 11/28/2023] [Accepted: 03/22/2024] [Indexed: 04/19/2024] Open
Abstract
In the realm of motor rehabilitation, Brain-Computer Interface Neurofeedback Training (BCI-NFT) emerges as a promising strategy. This aims to utilize an individual's brain activity to stimulate or assist movement, thereby strengthening sensorimotor pathways and promoting motor recovery. Employing various methodologies, BCI-NFT has been shown to be effective for enhancing motor function primarily of the upper limb in stroke, with very few studies reported in cerebral palsy (CP). Our main objective was to develop an electroencephalography (EEG)-based BCI-NFT system, employing an associative learning paradigm, to improve selective control of ankle dorsiflexion in CP and potentially other neurological populations. First, in a cohort of eight healthy volunteers, we successfully implemented a BCI-NFT system based on detection of slow movement-related cortical potentials (MRCP) from EEG generated by attempted dorsiflexion to simultaneously activate Neuromuscular Electrical Stimulation which assisted movement and served to enhance sensory feedback to the sensorimotor cortex. Participants also viewed a computer display that provided real-time visual feedback of ankle range of motion with an individualized target region displayed to encourage maximal effort. After evaluating several potential strategies, we employed a Long short-term memory (LSTM) neural network, a deep learning algorithm, to detect the motor intent prior to movement onset. We then evaluated the system in a 10-session ankle dorsiflexion training protocol on a child with CP. By employing transfer learning across sessions, we could significantly reduce the number of calibration trials from 50 to 20 without compromising detection accuracy, which was 80.8% on average. The participant was able to complete the required calibration trials and the 100 training trials per session for all 10 sessions and post-training demonstrated increased ankle dorsiflexion velocity, walking speed and step length. Based on exceptional system performance, feasibility and preliminary effectiveness in a child with CP, we are now pursuing a clinical trial in a larger cohort of children with CP.
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Affiliation(s)
- Ahad Behboodi
- Department of Biomechanics, University of Nebraska Omaha, Omaha, NE, United States
- Neurorehabilitation and Biomechanics Research Section, Rehabilitation Medicine Department, Clinical Center, National Institutes of Health, Bethesda, MD, United States
| | - Julia Kline
- Neurorehabilitation and Biomechanics Research Section, Rehabilitation Medicine Department, Clinical Center, National Institutes of Health, Bethesda, MD, United States
| | - Andrew Gravunder
- Neurorehabilitation and Biomechanics Research Section, Rehabilitation Medicine Department, Clinical Center, National Institutes of Health, Bethesda, MD, United States
| | - Connor Phillips
- Neurorehabilitation and Biomechanics Research Section, Rehabilitation Medicine Department, Clinical Center, National Institutes of Health, Bethesda, MD, United States
| | - Sheridan M. Parker
- Neurorehabilitation and Biomechanics Research Section, Rehabilitation Medicine Department, Clinical Center, National Institutes of Health, Bethesda, MD, United States
| | - Diane L. Damiano
- Neurorehabilitation and Biomechanics Research Section, Rehabilitation Medicine Department, Clinical Center, National Institutes of Health, Bethesda, MD, United States
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Chen D, Zhao Z, Zhang S, Chen S, Wu X, Shi J, Liu N, Pan C, Tang Y, Meng C, Zhao X, Tao B, Liu W, Chen D, Ding H, Zhang P, Tang Z. Evolving Therapeutic Landscape of Intracerebral Hemorrhage: Emerging Cutting-Edge Advancements in Surgical Robots, Regenerative Medicine, and Neurorehabilitation Techniques. Transl Stroke Res 2024:10.1007/s12975-024-01244-x. [PMID: 38558011 DOI: 10.1007/s12975-024-01244-x] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/31/2023] [Revised: 03/06/2024] [Accepted: 03/19/2024] [Indexed: 04/04/2024]
Abstract
Intracerebral hemorrhage (ICH) is the most serious form of stroke and has limited available therapeutic options. As knowledge on ICH rapidly develops, cutting-edge techniques in the fields of surgical robots, regenerative medicine, and neurorehabilitation may revolutionize ICH treatment. However, these new advances still must be translated into clinical practice. In this review, we examined several emerging therapeutic strategies and their major challenges in managing ICH, with a particular focus on innovative therapies involving robot-assisted minimally invasive surgery, stem cell transplantation, in situ neuronal reprogramming, and brain-computer interfaces. Despite the limited expansion of the drug armamentarium for ICH over the past few decades, the judicious selection of more efficacious therapeutic modalities and the exploration of multimodal combination therapies represent opportunities to improve patient prognoses after ICH.
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Affiliation(s)
- Danyang Chen
- Department of Neurology, Tongji Hospital, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, Hubei, China
| | - Zhixian Zhao
- Department of Neurology, Tongji Hospital, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, Hubei, China
| | - Shenglun Zhang
- School of Mechanical Science and Engineering, Huazhong University of Science and Technology, Wuhan, Hubei, China
| | - Shiling Chen
- Department of Neurology, Tongji Hospital, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, Hubei, China
| | - Xuan Wu
- Department of Neurology, Tongji Hospital, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, Hubei, China
| | - Jian Shi
- School of Mechanical Science and Engineering, Huazhong University of Science and Technology, Wuhan, Hubei, China
| | - Na Liu
- Department of Neurology, Tongji Hospital, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, Hubei, China
| | - Chao Pan
- Department of Neurology, Tongji Hospital, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, Hubei, China
| | - Yingxin Tang
- Department of Neurology, Tongji Hospital, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, Hubei, China
| | - Cai Meng
- School of Astronautics, Beihang University, Beijing, China
| | - Xingwei Zhao
- School of Mechanical Science and Engineering, Huazhong University of Science and Technology, Wuhan, Hubei, China
| | - Bo Tao
- School of Mechanical Science and Engineering, Huazhong University of Science and Technology, Wuhan, Hubei, China
| | - Wenjie Liu
- Beijing WanTeFu Medical Instrument Co., Ltd., Beijing, China
| | - Diansheng Chen
- Institute of Robotics, School of Mechanical Engineering and Automation, Beihang University, Beijing, China
| | - Han Ding
- School of Mechanical Science and Engineering, Huazhong University of Science and Technology, Wuhan, Hubei, China
| | - Ping Zhang
- Department of Neurology, Tongji Hospital, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, Hubei, China.
| | - Zhouping Tang
- Department of Neurology, Tongji Hospital, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, Hubei, China.
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Sánchez Cuesta FJ, González-Zamorano Y, Moreno-Verdú M, Vourvopoulos A, Serrano IJ, Del Castillo-Sobrino MD, Figueiredo P, Romero JP. Effects of motor imagery-based neurofeedback training after bilateral repetitive transcranial magnetic stimulation on post-stroke upper limb motor function: an exploratory crossover clinical trial. J Rehabil Med 2024; 56:jrm18253. [PMID: 38450442 PMCID: PMC10938141 DOI: 10.2340/jrm.v56.18253] [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: 07/17/2023] [Accepted: 01/23/2024] [Indexed: 03/08/2024] Open
Abstract
OBJECTIVE To examine the clinical effects of combining motor imagery-based neurofeedback training with bilateral repetitive transcranial magnetic stimulation for upper limb motor function in subacute and chronic stroke. DESIGN Clinical trial following an AB/BA crossover design with counterbalanced assignment. SUBJECTS Twenty individuals with subacute (n = 4) or chronic stroke (n = 16). METHODS Ten consecutive sessions of bilateral repetitive transcranial magnetic stimulation alone (therapy A) were compared vs a combination of10 consecutive sessions of bilateral repetitive transcranial magnetic stimulation with 12 non-consecutive sessions of motor imagery-based neurofeedback training (therapy B). Patients received both therapies (1-month washout period), in sequence AB or BA. Participants were assessed before and after each therapy and at 15-days follow-up, using the Fugl-Meyer Assessment-upper limb, hand-grip strength, and the Nottingham Sensory Assessment as primary outcome measures. RESULTS Both therapies resulted in improved functionality and sensory function. Therapy B consistently exhibited superior effects compared with therapy A, according to Fugl-Meyer Assessment and tactile and kinaesthetic sensory function across multiple time-points, irrespective of treatment sequence. No statistically significant differences between therapies were found for hand-grip strength. CONCLUSION Following subacute and chronic stroke, integrating bilateral repetitive transcranial magnetic stimulation and motor imagery-based neurofeedback training has the potential to enhance functional performance compared with using bilateral repetitive transcranial magnetic stimulation alone in upper limb recovery.
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Affiliation(s)
- Francisco José Sánchez Cuesta
- Faculty of Experimental Sciences, Francisco de Vitoria University, Pozuelo de Alarcón, Spain; Brain Injury and Movement Disorders Neurorehabilitation Group (GINDAT), Institute of Life Sciences, Francisco de Vitoria University, Pozuelo de Alarcón, Spain
| | - Yeray González-Zamorano
- Brain Injury and Movement Disorders Neurorehabilitation Group (GINDAT), Institute of Life Sciences, Francisco de Vitoria University, Pozuelo de Alarcón, Spain; Department of Physiotherapy, Occupational Therapy, Rehabilitation and Physical Medicine, King Juan Carlos University, Alcorcón, Spain; Cognitive Neuroscience, Pain, and Rehabilitation Research Group (NECODOR), Faculty of Health Sciences, Rey Juan Carlos University, Madrid, Spain
| | - Marcos Moreno-Verdú
- Faculty of Experimental Sciences, Francisco de Vitoria University, Pozuelo de Alarcón, Spain; Brain Injury and Movement Disorders Neurorehabilitation Group (GINDAT), Institute of Life Sciences, Francisco de Vitoria University, Pozuelo de Alarcón, Spain.
| | - Athanasios Vourvopoulos
- Institute for Systems and Robotics-Lisboa, Department of Bioengineering, Instituto Superior Técnico, Universidade de Lisboa, Lisbon, Portugal
| | - Ignacio J Serrano
- Neural and Cognitive Engineering group, Centre for Automation and Robotics (CAR) CSIC-UPM, Arganda del Rey, Madrid, Spain
| | | | - Patrícia Figueiredo
- Institute for Systems and Robotics-Lisboa, Department of Bioengineering, Instituto Superior Técnico, Universidade de Lisboa, Lisbon, Portugal
| | - Juan Pablo Romero
- Faculty of Experimental Sciences, Francisco de Vitoria University, Pozuelo de Alarcón, Spain; Brain Injury and Movement Disorders Neurorehabilitation Group (GINDAT), Institute of Life Sciences, Francisco de Vitoria University, Pozuelo de Alarcón, Spain; Brain Damage Unit, Beata María Ana Hospital, Madrid, Spain.
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Brunner I, Lundquist CB, Pedersen AR, Spaich EG, Dosen S, Savic A. Brain computer interface training with motor imagery and functional electrical stimulation for patients with severe upper limb paresis after stroke: a randomized controlled pilot trial. J Neuroeng Rehabil 2024; 21:10. [PMID: 38245782 PMCID: PMC10799379 DOI: 10.1186/s12984-024-01304-1] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/18/2023] [Accepted: 01/09/2024] [Indexed: 01/22/2024] Open
Abstract
BACKGROUND Restorative Brain-Computer Interfaces (BCI) that combine motor imagery with visual feedback and functional electrical stimulation (FES) may offer much-needed treatment alternatives for patients with severely impaired upper limb (UL) function after a stroke. OBJECTIVES This study aimed to examine if BCI-based training, combining motor imagery with FES targeting finger/wrist extensors, is more effective in improving severely impaired UL motor function than conventional therapy in the subacute phase after stroke, and if patients with preserved cortical-spinal tract (CST) integrity benefit more from BCI training. METHODS Forty patients with severe UL paresis (< 13 on Action Research Arm Test (ARAT) were randomized to either a 12-session BCI training as part of their rehabilitation or conventional UL rehabilitation. BCI sessions were conducted 3-4 times weekly for 3-4 weeks. At baseline, Transcranial Magnetic Stimulation (TMS) was performed to examine CST integrity. The main endpoint was the ARAT at 3 months post-stroke. A binominal logistic regression was conducted to examine the effect of treatment group and CST integrity on achieving meaningful improvement. In the BCI group, electroencephalographic (EEG) data were analyzed to investigate changes in event-related desynchronization (ERD) during the course of therapy. RESULTS Data from 35 patients (15 in the BCI group and 20 in the control group) were analyzed at 3-month follow-up. Few patients (10/35) improved above the minimally clinically important difference of 6 points on ARAT, 5/15 in the BCI group, 5/20 in control. An independent-samples Mann-Whitney U test revealed no differences between the two groups, p = 0.382. In the logistic regression only CST integrity was a significant predictor for improving UL motor function, p = 0.007. The EEG analysis showed significant changes in ERD of the affected hemisphere and its lateralization only during unaffected UL motor imagery at the end of the therapy. CONCLUSION This is the first RCT examining BCI training in the subacute phase where only patients with severe UL paresis were included. Though more patients in the BCI group improved relative to the group size, the difference between the groups was not significant. In the present study, preserved CTS integrity was much more vital for UL improvement than which type of intervention the patients received. Larger studies including only patients with some preserved CST integrity should be attempted.
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Affiliation(s)
- Iris Brunner
- Department of Clinical Medicine, Hammel Neurocenter and University Hospital, Aarhus University, Voldbyvej 12, 8450, Hammel, Denmark.
| | | | - Asger Roer Pedersen
- University Research Clinic for Innovative Patient Pathways, Diagnostic Centre, Silkeborg Regional Hospital, 8600, Silkeborg, Denmark
| | - Erika G Spaich
- Department of Health Science and Technology, Aalborg University, 9220, Aalborg, Denmark
| | - Strahinja Dosen
- Department of Health Science and Technology, Aalborg University, 9220, Aalborg, Denmark
| | - Andrej Savic
- Science and Research Centre, University of Belgrade-School of Electrical Engineering, Belgrade, 11000, Serbia
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Zhang M, Zhu F, Jia F, Wu Y, Wang B, Gao L, Chu F, Tang W. Efficacy of brain-computer interfaces on upper extremity motor function rehabilitation after stroke: A systematic review and meta-analysis. NeuroRehabilitation 2024; 54:199-212. [PMID: 38143387 DOI: 10.3233/nre-230215] [Citation(s) in RCA: 1] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/26/2023]
Abstract
BACKGROUND The recovery of upper limb function is crucial to the daily life activities of stroke patients. Brain-computer interface technology may have potential benefits in treating upper limb dysfunction. OBJECTIVE To systematically evaluate the efficacy of brain-computer interfaces (BCI) in the rehabilitation of upper limb motor function in stroke patients. METHODS Six databases up to July 2023 were reviewed according to the PRSIMA guidelines. Randomized controlled trials of BCI-based upper limb functional rehabilitation for stroke patients were selected for meta-analysis by pooling standardized mean difference (SMD) to summarize the evidence. The Cochrane risk of bias tool was used to assess the methodological quality of the included studies. RESULTS Twenty-five studies were included. The studies showed that BCI had a small effect on the improvement of upper limb function after the intervention. In terms of total duration of training, < 12 hours of training may result in better rehabilitation, but training duration greater than 12 hours suggests a non significant therapeutic effect of BCI training. CONCLUSION This meta-analysis suggests that BCI has a slight efficacy in improving upper limb function and has favorable long-term outcomes. In terms of total duration of training, < 12 hours of training may lead to better rehabilitation.
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Affiliation(s)
- Ming Zhang
- Department of Mechatronic Engineering, China University of Mining and Technology, Jiangsu, China
- The Affiliated Xuzhou Rehabilitation Hospital of Xuzhou Medical University, Xuzhou Medical University, Jiangsu, China
| | - Feilong Zhu
- College of Physical Education and Sports, Beijing Normal University, Beijing, China
| | - Fan Jia
- The Affiliated Xuzhou Rehabilitation Hospital of Xuzhou Medical University, Xuzhou Medical University, Jiangsu, China
| | - Yu Wu
- Department of Sports and Exercise Science, Zhejiang University, Hangzhou, China
| | - Bin Wang
- Departments of Rehabilitation Medicine, the Second Affiliated Hospital of Xi'an Jiaotong University, Xi'an, China
| | - Ling Gao
- The Affiliated Xuzhou Rehabilitation Hospital of Xuzhou Medical University, Xuzhou Medical University, Jiangsu, China
| | - Fengming Chu
- The Affiliated Xuzhou Rehabilitation Hospital of Xuzhou Medical University, Xuzhou Medical University, Jiangsu, China
| | - Wei Tang
- Department of Mechatronic Engineering, China University of Mining and Technology, Jiangsu, China
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Qu H, Zeng F, Tang Y, Shi B, Wang Z, Chen X, Wang J. The clinical effects of brain-computer interface with robot on upper-limb function for post-stroke rehabilitation: a meta-analysis and systematic review. Disabil Rehabil Assist Technol 2024; 19:30-41. [PMID: 35450498 DOI: 10.1080/17483107.2022.2060354] [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: 11/19/2021] [Accepted: 03/26/2022] [Indexed: 10/18/2022]
Abstract
PURPOSE Many recent clinical studies have suggested that the combination of brain-computer interfaces (BCIs) can induce neurological recovery and improvement in motor function. In this review, we performed a systematic review and meta-analysis to evaluate the clinical effects of BCI-robot systems. METHODS The articles published from January 2010 to December 2020 have been searched by using the databases (EMBASE, PubMed, CINAHL, EBSCO, Web of Science and manual search). The single-group studies were qualitatively described, and only the controlled-trial studies were included for the meta-analysis. The mean difference (MD) of Fugl-Meyer Assessment (FMA) scores were pooled and the random-effects model method was used to perform the meta-analysis. The PRISMA criteria were followed in current review. RESULTS A total of 897 records were identified, eight single-group studies and 11 controlled-trial studies were included in our review. The systematic analysis indicated that the BCI-robot systems had a significant improvement on motor function recovery. The meta-analysis showed there were no statistic differences between BCI-robot groups and robot groups, neither in the immediate effects nor long-term effects (p > 0.05). CONCLUSION The use of BCI-robot systems has significant improvement on the motor function recovery of hemiparetic upper-limb, and there is a sustaining effect. The meta-analysis showed no statistical difference between the experimental group (BCI-robot) and the control group (robot). However, there are a few shortcomings in the experimental design of existing studies, more clinical trials need to be conducted, and the experimental design needs to be more rigorous.Implications for RehabilitationIn this review, we evaluated the clinical effects of brain-computer interface with robot on upper-limb function for post-stroke rehabilitation. After we screened the databases, 19 articles were included in this review. These articles all clinical trial research, they all used non-invasive brain-computer interfaces and upper-limb robot.We conducted the systematic review with nine articles, the result indicated that the BCI-robot system had a significant improvement on motor function recovery. Eleven articles were included for the meta-analysis, the result showed there were no statistic differences between BCI-robot groups and robot groups, neither in the immediate effects nor long-term effects.We thought the result of meta-analysis which showed no statistic difference was probably caused by the heterogenicity of clinical trial designs of these articles.We thought the BCI-robot systems are promising strategies for post-stroke rehabilitation. And we gave several suggestions for further research: (1) The experimental design should be more rigorous, and describe the experimental designs in detail, especially the control group intervention, to make the experiment replicability. (2) New evaluation criteria need to be established, more objective assessment such as biomechanical assessment, fMRI should be utilised as the primary outcome. (3) More clinical studies with larger sample size, novel external devices, and BCI systems need to be conducted to investigate the differences between BCI-robot system and other interventions. (4) Further research could shift the focus to the patients who are in subacute stage, to explore if the early BCI training can make a positive impact on cerebral cortical recovery.
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Affiliation(s)
- Hao Qu
- Institute of Robotics and Intelligent Systems, School of Mechanical Engineering, Xi'an Jiaotong University, Xi'an, China
| | - Feixiang Zeng
- Department of Rehabilitation Medicine, HuiZhou Third People's Hospital, Huizhou, China
| | - Yongbin Tang
- Institute of Robotics and Intelligent Systems, School of Mechanical Engineering, Xi'an Jiaotong University, Xi'an, China
| | - Bin Shi
- Institute of Robotics and Intelligent Systems, School of Mechanical Engineering, Xi'an Jiaotong University, Xi'an, China
| | - Zhijun Wang
- Department of Rehabilitation Medicine, FoShan Fifth People's Hospital, Guangdong, China
| | - Xiaokai Chen
- Department of Rehabilitation Medicine, HuiZhou Third People's Hospital, Huizhou, China
| | - Jing Wang
- Institute of Robotics and Intelligent Systems, School of Mechanical Engineering, Xi'an Jiaotong University, Xi'an, China
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Hao M, Fang Q, Wu B, Liu L, Tang H, Tian F, Chen L, Kong D, Li J. Rehabilitation effect of intelligent rehabilitation training system on hemiplegic limb spasms after stroke. Open Life Sci 2023; 18:20220724. [PMID: 37791058 PMCID: PMC10543700 DOI: 10.1515/biol-2022-0724] [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: 05/29/2023] [Revised: 08/14/2023] [Accepted: 08/18/2023] [Indexed: 10/05/2023] Open
Abstract
This article aimed to explore the rehabilitation efficacy of intelligent rehabilitation training systems in hemiplegic limb spasms after stroke and provided more theoretical basis for the application of intelligent rehabilitation systems in the rehabilitation of hemiplegic limb spasms after stroke. To explore the rehabilitation efficacy of intelligent rehabilitation training system (RTS for short here) in post-stroke hemiplegic limb spasms, this study selected 99 patients with post-stroke hemiplegic limb spasms admitted to a local tertiary hospital from March 2021 to March 2023 as the research subjects. This article used blind selection to randomly divide them into three groups: control group 1, control group 2, and study group, with 33 patients in each group. Control group 1 used a conventional RTS, group 2 used the brain-computer interface RTS from reference 9, and research group used the intelligent RTS from this article. This article compared the degree of spasticity, balance ability score, motor function score, and daily living activity score of three groups of patients after 10 weeks of treatment. After 10 weeks of treatment, the number of patients in the study group with no spasms at level 0 (24) was significantly higher than the number of patients in group 1 (7) and group 2 (10), with a statistically significant difference (P < 0.05); In the comparison of Barthel index scores, after ten weeks of treatment, the total number of people in the study group with scores starting at 71-80 and 81-100 was 23. The total number of people in the score range of 71-80 and 81-100 in group 1 was 5, while in group 2, the total number of people in this score range was 8. The study group scored considerably higher than the control group and the difference was found to be statistically relevant (P < 0.05). In the Berg balance assessment scale and motor function assessment scale, after 10 weeks of treatment, the scores of the study group patients on both scales were significantly higher than those of group 1 and group 2 (P < 0.05). The intelligent RTS is beneficial for promoting the improvement of spasticity in stroke patients with hemiplegic limb spasms, as well as improving their balance ability, motor ability, and daily life activities. Its rehabilitation effect is good.
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Affiliation(s)
- Mingqing Hao
- Nursing Department, Guizhou Provincial People’s Hospital, Guiyang550000, Guizhou, China
- College of Nursing, Guizhou University of Traditional Chinese Medicine, Guiyang550000, Guizhou, China
| | - Qian Fang
- Nursing Department, Guizhou Provincial People’s Hospital, Guiyang550000, Guizhou, China
| | - Bei Wu
- Rory Meyers School of Nursing, New York University, New York10012, New York, USA
| | - Lin Liu
- Nursing Department, Guizhou Provincial People’s Hospital, Guiyang550000, Guizhou, China
| | - Huan Tang
- College of Nursing, Zunyi Medical University, Zunyi563000, Guizhou, China
| | - Fang Tian
- Nursing Department, Guizhou Provincial People’s Hospital, Guiyang550000, Guizhou, China
| | - Lihua Chen
- Nursing Department, Guizhou Provincial People’s Hospital, Guiyang550000, Guizhou, China
- College of Nursing, Guizhou University of Traditional Chinese Medicine, Guiyang550000, Guizhou, China
| | - Demiao Kong
- Nursing Department, Guizhou Provincial People’s Hospital, Guiyang550000, Guizhou, China
| | - Juan Li
- Nursing Department, Guizhou Provincial People’s Hospital, Guiyang550000, Guizhou, 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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13
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Bates M, Sunderam S. Hand-worn devices for assessment and rehabilitation of motor function and their potential use in BCI protocols: a review. Front Hum Neurosci 2023; 17:1121481. [PMID: 37484920 PMCID: PMC10357516 DOI: 10.3389/fnhum.2023.1121481] [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: 12/11/2022] [Accepted: 06/01/2023] [Indexed: 07/25/2023] Open
Abstract
Introduction Various neurological conditions can impair hand function. Affected individuals cannot fully participate in activities of daily living due to the lack of fine motor control. Neurorehabilitation emphasizes repetitive movement and subjective clinical assessments that require clinical experience to administer. Methods Here, we perform a review of literature focused on the use of hand-worn devices for rehabilitation and assessment of hand function. We paid particular attention to protocols that involve brain-computer interfaces (BCIs) since BCIs are gaining ground as a means for detecting volitional signals as the basis for interactive motor training protocols to augment recovery. All devices reviewed either monitor, assist, stimulate, or support hand and finger movement. Results A majority of studies reviewed here test or validate devices through clinical trials, especially for stroke. Even though sensor gloves are the most commonly employed type of device in this domain, they have certain limitations. Many such gloves use bend or inertial sensors to monitor the movement of individual digits, but few monitor both movement and applied pressure. The use of such devices in BCI protocols is also uncommon. Discussion We conclude that hand-worn devices that monitor both flexion and grip will benefit both clinical diagnostic assessment of function during treatment and closed-loop BCI protocols aimed at rehabilitation.
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14
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Shou YZ, Wang XH, Yang GF. Verum versus Sham brain-computer interface on upper limb function recovery after stroke: A systematic review and meta-analysis of randomized controlled trials. Medicine (Baltimore) 2023; 102:e34148. [PMID: 37390271 PMCID: PMC10313240 DOI: 10.1097/md.0000000000034148] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 05/06/2023] [Accepted: 06/08/2023] [Indexed: 07/02/2023] Open
Abstract
BACKGROUND Previous clinical trials have reported that the brain-computer interface (BCI) is a useful management tool for upper limb function recovery (ULFR) in stroke. However, there is insufficient evidence regarding this topic. Thus, this study aimed to investigate the effectiveness of verum versus sham BCI on the ULFR in stroke patients. METHODS We comprehensively searched the Cochrane Library, PUBMED, EMBASE, Web of Science, and China National Knowledge Infrastructure databases from their inception to January 1, 2023. Randomized clinical trials (RCTs) assessing the effectiveness and safety of BCI for ULFR after stroke were included. The outcomes were the Fugl-Meyer Assessment for Upper Extremity, Wolf Motor Function Test, Modified Barthel Index, motor activity log, and Action Research Arm Test. The methodological quality of all the included randomized controlled trials was evaluated using the Cochrane risk-of-bias tool. Statistical analysis was performed using RevMan 5.4 software. RESULTS Eleven eligible studies involving 334 patients were included. The results of the meta-analysis showed significant differences in the Fugl-Meyer Assessment for Upper Extremity (mean difference [MD] = 4.78, 95% confidence interval [CI] [1.90, 7.65], I2 = 0%, P = .001) and Modified Barthel Index (MD = 7.37, 95% CI [1.89, 12.84], I2 = 19%, P = .008). However, no significant differences were found on motor activity log (MD = -0.70, 95% CI [-3.17, 1.77]), Action Research Arm Test (MD = 3.05, 95% CI [-8.33, 14.44], I2 = 0%, P = .60), and Wolf Motor Function Test (MD = 4.23, 95% CI [-0.55, 9.01], P = .08). CONCLUSION BCI may be an effective management strategy for ULFR in stroke patients. Future studies with larger sample size and strict design are still needed to warrant the current findings.
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Affiliation(s)
- Yi-zhou Shou
- Department of Rehabilitation, Tongde Hospital of Zhejiang Province, Hangzhou, China
| | - Xin-hua Wang
- Department of Tuina, The Second Affiliated Hospital of Zhejiang Chinese Medical University, Hangzhou, China
| | - Gui-fen Yang
- Department of Rehabilitation, Tongde Hospital of Zhejiang Province, Hangzhou, China
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Fu J, Chen S, Shu X, Lin Y, Jiang Z, Wei D, Gao J, Jia J. Functional-oriented, portable brain-computer interface training for hand motor recovery after stroke: a randomized controlled study. Front Neurosci 2023; 17:1146146. [PMID: 37250399 PMCID: PMC10213744 DOI: 10.3389/fnins.2023.1146146] [Citation(s) in RCA: 1] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/17/2023] [Accepted: 04/07/2023] [Indexed: 05/31/2023] Open
Abstract
Background Brain-computer interfaces (BCIs) have been proven to be effective for hand motor recovery after stroke. Facing kinds of dysfunction of the paretic hand, the motor task of BCIs for hand rehabilitation is relatively single, and the operation of many BCI devices is complex for clinical use. Therefore, we proposed a functional-oriented, portable BCI equipment and explored the efficiency of hand motor recovery after a stroke. Materials and methods Stroke patients were randomly assigned to the BCI group and the control group. The BCI group received BCI-based grasp/open motor training, while the control group received task-oriented guidance training. Both groups received 20 sessions of motor training in 4 weeks, and each session lasted for 30 min. The Fugl-Meyer assessment of the upper limb (FMA-UE) was applied for the assessment of rehabilitation outcomes, and the EEG signals were obtained for processing. Results The progress of FMA-UE between the BCI group [10.50 (5.75, 16.50)] and the control group [5.00 (4.00, 8.00)] was significantly different (Z = -2.834, P = 0.005). Meanwhile, the FMA-UE of both groups improved significantly (P < 0.001). A total of 24 patients in the BCI group achieved the minimal clinically important difference (MCID) of FMA-UE with an effective rate of 80%, and 16 in the control group achieved the MCID, with an effective rate of 51.6%. The lateral index of the open task in the BCI group was significantly decreased (Z = -2.704, P = 0.007). The average BCI accuracy for 24 stroke patients in 20 sessions was 70.7%, which was improved by 5.0% in the final session compared with the first session. Conclusion Targeted hand movement and two motor task modes, namely grasp and open, to be applied in a BCI design may be suitable in stroke patients with hand dysfunction. The functional-oriented, portable BCI training can promote hand recovery after a stroke, and it is expected to be widely used in clinical practice. The lateral index change of inter-hemispheric balance may be the mechanism of motor recovery. Trial registration number ChiCTR2100044492.
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Affiliation(s)
- Jianghong Fu
- Department of Rehabilitation Medicine, Huashan Hospital, Fudan University, Shanghai, China
| | - Shugeng Chen
- Department of Rehabilitation Medicine, Huashan Hospital, Fudan University, Shanghai, China
| | - Xiaokang Shu
- School of Mechanical Engineering, Shanghai Jiao Tong University, Shanghai, China
| | - Yifang Lin
- Department of Rehabilitation Medicine, Huashan Hospital, Fudan University, Shanghai, China
| | - Zewu Jiang
- Department of Rehabilitation Medicine, Huashan Hospital, Fudan University, Shanghai, China
| | - Dongshuai Wei
- Department of Rehabilitation Medicine, Huashan Hospital, Fudan University, Shanghai, China
| | - Jiajia Gao
- Department of Rehabilitation Medicine, Shanghai No. 3 Rehabilitation Hospital, Shanghai, China
| | - Jie Jia
- Department of Rehabilitation Medicine, Huashan Hospital, Fudan University, Shanghai, China
- National Clinical Research Center for Aging and Medicine, Huashan Hospital, Fudan University, Shanghai, China
- National Center for Neurological Disorders, Huashan Hospital, Fudan University, Shanghai, China
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A Review of Online Classification Performance in Motor Imagery-Based Brain–Computer Interfaces for Stroke Neurorehabilitation. SIGNALS 2023. [DOI: 10.3390/signals4010004] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 01/22/2023] Open
Abstract
Motor imagery (MI)-based brain–computer interfaces (BCI) have shown increased potential for the rehabilitation of stroke patients; nonetheless, their implementation in clinical practice has been restricted due to their low accuracy performance. To date, although a lot of research has been carried out in benchmarking and highlighting the most valuable classification algorithms in BCI configurations, most of them use offline data and are not from real BCI performance during the closed-loop (or online) sessions. Since rehabilitation training relies on the availability of an accurate feedback system, we surveyed articles of current and past EEG-based BCI frameworks who report the online classification of the movement of two upper limbs in both healthy volunteers and stroke patients. We found that the recently developed deep-learning methods do not outperform the traditional machine-learning algorithms. In addition, patients and healthy subjects exhibit similar classification accuracy in current BCI configurations. Lastly, in terms of neurofeedback modality, functional electrical stimulation (FES) yielded the best performance compared to non-FES systems.
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Zanona ADF, Piscitelli D, Seixas VM, Scipioni KRDDS, Bastos MSC, de Sá LCK, Monte-Silva K, Bolivar M, Solnik S, De Souza RF. Brain-computer interface combined with mental practice and occupational therapy enhances upper limb motor recovery, activities of daily living, and participation in subacute stroke. Front Neurol 2023; 13:1041978. [PMID: 36698872 PMCID: PMC9869053 DOI: 10.3389/fneur.2022.1041978] [Citation(s) in RCA: 3] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/12/2022] [Accepted: 11/28/2022] [Indexed: 01/11/2023] Open
Abstract
Background We investigated the effects of brain-computer interface (BCI) combined with mental practice (MP) and occupational therapy (OT) on performance in activities of daily living (ADL) in stroke survivors. Methods Participants were randomized into two groups: experimental (n = 23, BCI controlling a hand exoskeleton combined with MP and OT) and control (n = 21, OT). Subjects were assessed with the functional independence measure (FIM), motor activity log (MAL), amount of use (MAL-AOM), and quality of movement (MAL-QOM). The box and blocks test (BBT) and the Jebsen hand functional test (JHFT) were used for the primary outcome of performance in ADL, while the Fugl-Meyer Assessment was used for the secondary outcome. Exoskeleton activation and the degree of motor imagery (measured as event-related desynchronization) were assessed in the experimental group. For the BCI, the EEG electrodes were placed on the regions of FC3, C3, CP3, FC4, C4, and CP4, according to the international 10-20 EEG system. The exoskeleton was placed on the affected hand. MP was based on functional tasks. OT consisted of ADL training, muscle mobilization, reaching tasks, manipulation and prehension, mirror therapy, and high-frequency therapeutic vibration. The protocol lasted 1 h, five times a week, for 2 weeks. Results There was a difference between baseline and post-intervention analysis for the experimental group in all evaluations: FIM (p = 0.001, d = 0.56), MAL-AOM (p = 0.001, d = 0.83), MAL-QOM (p = 0.006, d = 0.84), BBT (p = 0.004, d = 0.40), and JHFT (p = 0.001, d = 0.45). Within the experimental group, post-intervention improvements were detected in the degree of motor imagery (p < 0.001) and the amount of exoskeleton activations (p < 0.001). For the control group, differences were detected for MAL-AOM (p = 0.001, d = 0.72), MAL-QOM (p = 0.013, d = 0.50), and BBT (p = 0.005, d = 0.23). Notably, the effect sizes were larger for the experimental group. No differences were detected between groups at post-intervention. Conclusion BCI combined with MP and OT is a promising tool for promoting sensorimotor recovery of the upper limb and functional independence in subacute post-stroke survivors.
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Affiliation(s)
- Aristela de Freitas Zanona
- Department of Occupational Therapy and Graduate Program in Applied Health Sciences, Federal University of Sergipe, São Cristóvão, Sergipe, Brazil,*Correspondence: Aristela de Freitas Zanona ✉
| | - Daniele Piscitelli
- School of Medicine and Surgery, University of Milano-Bicocca, Milan, Italy,Department of Kinesiology, University of Connecticut, Storrs, CT, United States
| | - Valquiria Martins Seixas
- Department of Occupational Therapy and Graduate Program in Applied Health Sciences, Federal University of Sergipe, São Cristóvão, Sergipe, Brazil
| | | | | | | | - Kátia Monte-Silva
- Department of Physical Therapy, Federal University of Pernambuco, Recife, Pernambuco, Brazil
| | - Miburge Bolivar
- Department of Occupational Therapy and Graduate Program in Applied Health Sciences, Federal University of Sergipe, São Cristóvão, Sergipe, Brazil
| | - Stanislaw Solnik
- Department of Physical Therapy, University of North Georgia, Dahlonega, GA, United States,Department of Physical Education, Wroclaw University of Health and Sport Sciences, Wroclaw, Poland
| | - Raphael Fabricio De Souza
- Department of Occupational Therapy and Graduate Program in Applied Health Sciences, Federal University of Sergipe, São Cristóvão, Sergipe, Brazil
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Penev YP, Beneke A, Root KT, Meisel E, Kwak S, Diaz MJ, Root JL, Hosseini MR, Lucke-Wold B. Therapeutic Effectiveness of Brain Computer Interfaces in Stroke Patients: A Systematic Review. JOURNAL OF EXPERIMENTAL NEUROLOGY 2023; 4:87-93. [PMID: 37799298 PMCID: PMC10552326 DOI: 10.33696/neurol.4.077] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Figures] [Subscribe] [Scholar Register] [Indexed: 10/07/2023]
Abstract
Background Brain-computer interfaces (BCIs) are a rapidly advancing field which utilizes brain activity to control external devices for a myriad of functions, including the restoration of motor function. Clinically, BCIs have been especially impactful in patients who suffer from stroke-mediated damage. However, due to the rapid advancement in the field, there is a lack of accepted standards of practice. Therefore, the aim of this systematic review is to summarize the current literature published regarding the efficacy of BCI-based rehabilitation of motor dysfunction in stroke patients. Methodology This systematic review was performed in accordance with the guidelines set forth by the Preferred Reporting Items for Systematic Reviews and Meta-analysis (PRISMA) 2020 statement. PubMed, Embase, and Cochrane Library were queried for relevant articles and screened for inclusion criteria by two authors. All discrepancies were resolved by discussion among both reviewers and subsequent consensus. Results 11/12 (91.6%) of studies focused on upper extremity outcomes and reported larger initial improvements for participants in the treatment arm (using BCI) as compared to those in the control arm (no BCI). 2/2 studies focused on lower extremity outcomes reported improvements for the treatment arm compared to the control arm. Discussion/Conclusion This systematic review illustrates the utility BCI has for the restoration of upper extremity and lower extremity motor function in stroke patients and supports further investigation of BCI for other clinical indications.
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Affiliation(s)
- Yordan P. Penev
- ICollege of Medicine, University of Florida, Gainesville, Florida, USA
| | - Alice Beneke
- ICollege of Medicine, University of Florida, Gainesville, Florida, USA
| | - Kevin T. Root
- ICollege of Medicine, University of Florida, Gainesville, Florida, USA
| | - Emily Meisel
- ICollege of Medicine, University of Florida, Gainesville, Florida, USA
| | - Sean Kwak
- ICollege of Medicine, University of Florida, Gainesville, Florida, USA
| | - Michael J. Diaz
- ICollege of Medicine, University of Florida, Gainesville, Florida, USA
| | | | | | - Brandon Lucke-Wold
- Department of Neurosurgery, University of Florida, Gainesville, Florida, USA
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Fu J, Chen S, Jia J. Sensorimotor Rhythm-Based Brain-Computer Interfaces for Motor Tasks Used in Hand Upper Extremity Rehabilitation after Stroke: A Systematic Review. Brain Sci 2022; 13:brainsci13010056. [PMID: 36672038 PMCID: PMC9856697 DOI: 10.3390/brainsci13010056] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/16/2022] [Revised: 12/05/2022] [Accepted: 12/25/2022] [Indexed: 12/29/2022] Open
Abstract
Brain-computer interfaces (BCIs) are becoming more popular in the neurological rehabilitation field, and sensorimotor rhythm (SMR) is a type of brain oscillation rhythm that can be captured and analyzed in BCIs. Previous reviews have testified to the efficacy of the BCIs, but seldom have they discussed the motor task adopted in BCIs experiments in detail, as well as whether the feedback is suitable for them. We focused on the motor tasks adopted in SMR-based BCIs, as well as the corresponding feedback, and searched articles in PubMed, Embase, Cochrane library, Web of Science, and Scopus and found 442 articles. After a series of screenings, 15 randomized controlled studies were eligible for analysis. We found motor imagery (MI) or motor attempt (MA) are common experimental paradigms in EEG-based BCIs trials. Imagining/attempting to grasp and extend the fingers is the most common, and there were multi-joint movements, including wrist, elbow, and shoulder. There were various types of feedback in MI or MA tasks for hand grasping and extension. Proprioception was used more frequently in a variety of forms. Orthosis, robot, exoskeleton, and functional electrical stimulation can assist the paretic limb movement, and visual feedback can be used as primary feedback or combined forms. However, during the recovery process, there are many bottleneck problems for hand recovery, such as flaccid paralysis or opening the fingers. In practice, we should mainly focus on patients' difficulties, and design one or more motor tasks for patients, with the assistance of the robot, FES, or other combined feedback, to help them to complete a grasp, finger extension, thumb opposition, or other motion. Future research should focus on neurophysiological changes and functional improvements and further elaboration on the changes in neurophysiology during the recovery of motor function.
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Affiliation(s)
- Jianghong Fu
- Department of Rehabilitation Medicine, Huashan Hospital, Fudan University, Shanghai 200040, China
| | - Shugeng Chen
- Department of Rehabilitation Medicine, Huashan Hospital, Fudan University, Shanghai 200040, China
| | - Jie Jia
- Department of Rehabilitation Medicine, Huashan Hospital, Fudan University, Shanghai 200040, China
- National Clinical Research Center for Aging and Medicine, Huashan Hospital, Fudan University, Shanghai 200040, China
- National Center for Neurological Disorders, Shanghai 200040, China
- Correspondence: ; Tel./Fax: +86-021-5288-7820
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Brain-machine Interface (BMI)-based Neurorehabilitation for Post-stroke Upper Limb Paralysis. Keio J Med 2022; 71:82-92. [PMID: 35718470 DOI: 10.2302/kjm.2022-0002-oa] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/27/2022]
Abstract
Because recovery from upper limb paralysis after stroke is challenging, compensatory approaches have been the main focus of upper limb rehabilitation. However, based on fundamental and clinical research indicating that the brain has a far greater potential for plastic change than previously thought, functional restorative approaches have become increasingly common. Among such interventions, constraint-induced movement therapy, task-specific training, robotic therapy, neuromuscular electrical stimulation (NMES), mental practice, mirror therapy, and bilateral arm training are recommended in recently published stroke guidelines. For severe upper limb paralysis, however, no effective therapy has yet been established. Against this background, there is growing interest in applying brain-machine interface (BMI) technologies to upper limb rehabilitation. Increasing numbers of randomized controlled trials have demonstrated the effectiveness of BMI neurorehabilitation, and several meta-analyses have shown medium to large effect sizes with BMI therapy. Subgroup analyses indicate higher intervention effects in the subacute group than the chronic group, when using movement attempts as the BMI-training trigger task rather than using motor imagery, and using NMES as the external device compared with using other devices. The Keio BMI team has developed an electroencephalography-based neurorehabilitation system and has published clinical and basic studies demonstrating its effectiveness and neurophysiological mechanisms. For its wider clinical application, the positioning of BMI therapy in upper limb rehabilitation needs to be clarified, BMI needs to be commercialized as an easy-to-use and cost-effective medical device, and training systems for rehabilitation professionals need to be developed. A technological breakthrough enabling selective modulation of neural circuits is also needed.
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Bibliometric analysis on Brain-computer interfaces in a 30-year period. APPL INTELL 2022. [DOI: 10.1007/s10489-022-04226-4] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/03/2022]
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Behboodi A, Lee WA, Hinchberger VS, Damiano DL. Determining optimal mobile neurofeedback methods for motor neurorehabilitation in children and adults with non-progressive neurological disorders: a scoping review. J Neuroeng Rehabil 2022; 19:104. [PMID: 36171602 PMCID: PMC9516814 DOI: 10.1186/s12984-022-01081-9] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/25/2022] [Accepted: 09/08/2022] [Indexed: 11/22/2022] Open
Abstract
Background Brain–computer interfaces (BCI), initially designed to bypass the peripheral motor system to externally control movement using brain signals, are additionally being utilized for motor rehabilitation in stroke and other neurological disorders. Also called neurofeedback training, multiple approaches have been developed to link motor-related cortical signals to assistive robotic or electrical stimulation devices during active motor training with variable, but mostly positive, functional outcomes reported. Our specific research question for this scoping review was: for persons with non-progressive neurological injuries who have the potential to improve voluntary motor control, which mobile BCI-based neurofeedback methods demonstrate or are associated with improved motor outcomes for Neurorehabilitation applications? Methods We searched PubMed, Web of Science, and Scopus databases with all steps from study selection to data extraction performed independently by at least 2 individuals. Search terms included: brain machine or computer interfaces, neurofeedback and motor; however, only studies requiring a motor attempt, versus motor imagery, were retained. Data extraction included participant characteristics, study design details and motor outcomes. Results From 5109 papers, 139 full texts were reviewed with 23 unique studies identified. All utilized EEG and, except for one, were on the stroke population. The most commonly reported functional outcomes were the Fugl-Meyer Assessment (FMA; n = 13) and the Action Research Arm Test (ARAT; n = 6) which were then utilized to assess effectiveness, evaluate design features, and correlate with training doses. Statistically and functionally significant pre-to post training changes were seen in FMA, but not ARAT. Results did not differ between robotic and electrical stimulation feedback paradigms. Notably, FMA outcomes were positively correlated with training dose. Conclusion This review on BCI-based neurofeedback training confirms previous findings of effectiveness in improving motor outcomes with some evidence of enhanced neuroplasticity in adults with stroke. Associative learning paradigms have emerged more recently which may be particularly feasible and effective methods for Neurorehabilitation. More clinical trials in pediatric and adult neurorehabilitation to refine methods and doses and to compare to other evidence-based training strategies are warranted.
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Affiliation(s)
- Ahad Behboodi
- Rehabilitation Medicine Department, National Institutes of Health, Bethesda, MD, USA
| | - Walker A Lee
- Rehabilitation Medicine Department, National Institutes of Health, Bethesda, MD, USA
| | | | - Diane L Damiano
- Rehabilitation Medicine Department, National Institutes of Health, Bethesda, MD, USA.
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Kuwahara W, Miyawaki Y, Kaneko F. Impact of the Upper Limb Physiotherapy on Behavioral and Brain Adaptations in Post-Stroke Patients. JOURNAL OF ROBOTICS AND MECHATRONICS 2022. [DOI: 10.20965/jrm.2022.p0718] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 11/09/2022]
Abstract
Many stroke patients suffer from motor impairments due to paralysis, and consequently, motor paralysis of upper limbs seems to be particularly prone to residual impairment compared to that of lower limbs. Although ‘learned non-use’ that by managing reasonably well using only the unaffected upper limb in their actions, the patients can achieve their desired behavior, and these success experiences strengthen this pattern of behavior can be interpreted as a post-stroke adaptation, physiotherapy may lead to poor recovery of motor impairment. This review article discusses the impact of upper limb physiotherapy after stroke on behavioral/brain adaptations. Our previous studies demonstrated that patients with severe post-stroke sensorimotor impairments in a chronic phase might have abnormal functional connectivity. To prevent such adaptation after stroke, upper limb physiotherapy is important. In rehabilitation practices, hyper-adaptation has been often observed in not only behavioral but also brain changes. Although several studies are reporting clinical efficacy in patients with moderate to mild paralysis, there might be no effective treatment for patients with severe motor paralysis. To overcome these serious problems, we have developed a novel approach, kinesthetic illusion induced by visual stimulation (KINVIS) therapy. We showed that the effects of KINVIS therapy with therapeutic exercise on upper limb motor functions were mediated by spasticity, and functional connectivity in the brain was also changed with the improvement of motor function after KINVIS therapy. Brain changes underlying behavioral changes need to be more examined, and the adaptation of stroke patients needs to be clarified in detail.
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Bigoni C, Zandvliet SB, Beanato E, Crema A, Coscia M, Espinosa A, Henneken T, Hervé J, Oflar M, Evangelista GG, Morishita T, Wessel MJ, Bonvin C, Turlan JL, Birbaumer N, Hummel FC. A Novel Patient-Tailored, Cumulative Neurotechnology-Based Therapy for Upper-Limb Rehabilitation in Severely Impaired Chronic Stroke Patients: The AVANCER Study Protocol. Front Neurol 2022; 13:919511. [PMID: 35873764 PMCID: PMC9301337 DOI: 10.3389/fneur.2022.919511] [Citation(s) in RCA: 5] [Impact Index Per Article: 2.5] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/13/2022] [Accepted: 06/10/2022] [Indexed: 11/17/2022] Open
Abstract
Effective, patient-tailored rehabilitation to restore upper-limb motor function in severely impaired stroke patients is still missing. If suitably combined and administered in a personalized fashion, neurotechnologies offer a large potential to assist rehabilitative therapies to enhance individual treatment effects. AVANCER (clinicaltrials.gov NCT04448483) is a two-center proof-of-concept trial with an individual based cumulative longitudinal intervention design aiming at reducing upper-limb motor impairment in severely affected stroke patients with the help of multiple neurotechnologies. AVANCER will determine feasibility, safety, and effectivity of this innovative intervention. Thirty chronic stroke patients with a Fugl-Meyer assessment of the upper limb (FM-UE) <20 will be recruited at two centers. All patients will undergo the cumulative personalized intervention within two phases: the first uses an EEG-based brain-computer interface to trigger a variety of patient-tailored movements supported by multi-channel functional electrical stimulation in combination with a hand exoskeleton. This phase will be continued until patients do not improve anymore according to a quantitative threshold based on the FM-UE. The second interventional phase will add non-invasive brain stimulation by means of anodal transcranial direct current stimulation to the motor cortex to the initial approach. Each phase will last for a minimum of 11 sessions. Clinical and multimodal assessments are longitudinally acquired, before the first interventional phase, at the switch to the second interventional phase and at the end of the second interventional phase. The primary outcome measure is the 66-point FM-UE, a significant improvement of at least four points is hypothesized and considered clinically relevant. Several clinical and system neuroscience secondary outcome measures are additionally evaluated. AVANCER aims to provide evidence for a safe, effective, personalized, adjuvant treatment for patients with severe upper-extremity impairment for whom to date there is no efficient treatment available.
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Affiliation(s)
- Claudia Bigoni
- Defitech Chair of Clinical Neuroengineering, Center for Neuroprosthetics (CNP) and Brain Mind Institute (BMI), École Polytechnique Fédérale de Lausanne (EPFL), Geneva, Switzerland
- Defitech Chair of Clinical Neuroengineering, Center for Neuroprosthetics (CNP) and Brain Mind Institute (BMI), École Polytechnique Fédérale de Lausanne (EPFL), Clinique Romande de Réadaptation, Sion, Switzerland
| | - Sarah B. Zandvliet
- Defitech Chair of Clinical Neuroengineering, Center for Neuroprosthetics (CNP) and Brain Mind Institute (BMI), École Polytechnique Fédérale de Lausanne (EPFL), Geneva, Switzerland
- Defitech Chair of Clinical Neuroengineering, Center for Neuroprosthetics (CNP) and Brain Mind Institute (BMI), École Polytechnique Fédérale de Lausanne (EPFL), Clinique Romande de Réadaptation, Sion, Switzerland
- Department of Rehabilitation, Donders Institute for Brain, Cognition and Behaviour, Radboud University Medical Centre, Nijmegen, Netherlands
| | - Elena Beanato
- Defitech Chair of Clinical Neuroengineering, Center for Neuroprosthetics (CNP) and Brain Mind Institute (BMI), École Polytechnique Fédérale de Lausanne (EPFL), Geneva, Switzerland
- Defitech Chair of Clinical Neuroengineering, Center for Neuroprosthetics (CNP) and Brain Mind Institute (BMI), École Polytechnique Fédérale de Lausanne (EPFL), Clinique Romande de Réadaptation, Sion, Switzerland
| | - Andrea Crema
- Clinical Neuroscience, University of Geneva Medical School, Geneva, Switzerland
- Bertarelli Foundation Chair in Translational Neuroengineering, Centre for Neuroprosthetics and Institute of Bioengineering, School of Engineering, École Polytechnique Fédérale de Lausanne (EPFL), Lausanne, Switzerland
| | - Martina Coscia
- Wyss Center for Bio and Neuroengineering, Geneva, Switzerland
- confinis AG, Sursee, Switzerland
| | - Arnau Espinosa
- Wyss Center for Bio and Neuroengineering, Geneva, Switzerland
| | - Tina Henneken
- Defitech Chair of Clinical Neuroengineering, Center for Neuroprosthetics (CNP) and Brain Mind Institute (BMI), École Polytechnique Fédérale de Lausanne (EPFL), Geneva, Switzerland
- Defitech Chair of Clinical Neuroengineering, Center for Neuroprosthetics (CNP) and Brain Mind Institute (BMI), École Polytechnique Fédérale de Lausanne (EPFL), Clinique Romande de Réadaptation, Sion, Switzerland
| | - Julie Hervé
- Defitech Chair of Clinical Neuroengineering, Center for Neuroprosthetics (CNP) and Brain Mind Institute (BMI), École Polytechnique Fédérale de Lausanne (EPFL), Geneva, Switzerland
- Defitech Chair of Clinical Neuroengineering, Center for Neuroprosthetics (CNP) and Brain Mind Institute (BMI), École Polytechnique Fédérale de Lausanne (EPFL), Clinique Romande de Réadaptation, Sion, Switzerland
| | - Meltem Oflar
- Defitech Chair of Clinical Neuroengineering, Center for Neuroprosthetics (CNP) and Brain Mind Institute (BMI), École Polytechnique Fédérale de Lausanne (EPFL), Geneva, Switzerland
- Defitech Chair of Clinical Neuroengineering, Center for Neuroprosthetics (CNP) and Brain Mind Institute (BMI), École Polytechnique Fédérale de Lausanne (EPFL), Clinique Romande de Réadaptation, Sion, Switzerland
| | - Giorgia G. Evangelista
- Defitech Chair of Clinical Neuroengineering, Center for Neuroprosthetics (CNP) and Brain Mind Institute (BMI), École Polytechnique Fédérale de Lausanne (EPFL), Geneva, Switzerland
- Defitech Chair of Clinical Neuroengineering, Center for Neuroprosthetics (CNP) and Brain Mind Institute (BMI), École Polytechnique Fédérale de Lausanne (EPFL), Clinique Romande de Réadaptation, Sion, Switzerland
| | - Takuya Morishita
- Defitech Chair of Clinical Neuroengineering, Center for Neuroprosthetics (CNP) and Brain Mind Institute (BMI), École Polytechnique Fédérale de Lausanne (EPFL), Geneva, Switzerland
- Defitech Chair of Clinical Neuroengineering, Center for Neuroprosthetics (CNP) and Brain Mind Institute (BMI), École Polytechnique Fédérale de Lausanne (EPFL), Clinique Romande de Réadaptation, Sion, Switzerland
| | - Maximilian J. Wessel
- Defitech Chair of Clinical Neuroengineering, Center for Neuroprosthetics (CNP) and Brain Mind Institute (BMI), École Polytechnique Fédérale de Lausanne (EPFL), Geneva, Switzerland
- Defitech Chair of Clinical Neuroengineering, Center for Neuroprosthetics (CNP) and Brain Mind Institute (BMI), École Polytechnique Fédérale de Lausanne (EPFL), Clinique Romande de Réadaptation, Sion, Switzerland
| | | | - Jean-Luc Turlan
- Department of Neurological Rehabilitation, Clinique Romande de Réadaptation Suva, Sion, Switzerland
| | - Niels Birbaumer
- Department of Medical Psychology and Behavioral Neurobiology, University of Tübingen, Tübingen, Germany
| | - Friedhelm C. Hummel
- Defitech Chair of Clinical Neuroengineering, Center for Neuroprosthetics (CNP) and Brain Mind Institute (BMI), École Polytechnique Fédérale de Lausanne (EPFL), Geneva, Switzerland
- Defitech Chair of Clinical Neuroengineering, Center for Neuroprosthetics (CNP) and Brain Mind Institute (BMI), École Polytechnique Fédérale de Lausanne (EPFL), Clinique Romande de Réadaptation, Sion, Switzerland
- Clinical Neuroscience, University of Geneva Medical School, Geneva, Switzerland
- *Correspondence: Friedhelm C. Hummel
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Wang Z, Cao C, Chen L, Gu B, Liu S, Xu M, He F, Ming D. Multimodal Neural Response and Effect Assessment During a BCI-Based Neurofeedback Training After Stroke. Front Neurosci 2022; 16:884420. [PMID: 35784834 PMCID: PMC9247245 DOI: 10.3389/fnins.2022.884420] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/26/2022] [Accepted: 05/17/2022] [Indexed: 11/20/2022] Open
Abstract
Stroke caused by cerebral infarction or hemorrhage can lead to motor dysfunction. The recovery of motor function is vital for patients with stroke in daily activities. Traditional rehabilitation of stroke generally depends on physical practice under passive affected limbs movement. Motor imagery-based brain computer interface (MI-BCI) combined with functional electrical stimulation (FES) is a potential active neural rehabilitation technology for patients with stroke recently, which complements traditional passive rehabilitation methods. As the predecessor of BCI technology, neurofeedback training (NFT) is a psychological process that feeds back neural activities online to users for self-regulation. In this work, BCI-based NFT were proposed to promote the active repair and reconstruction of the whole nerve conduction pathway and motor function. We designed and implemented a multimodal, training type motor NFT system (BCI-NFT-FES) by integrating the visual, auditory, and tactile multisensory pathway feedback mode and using the joint detection of electroencephalography (EEG) and functional near-infrared spectroscopy (fNIRS). The results indicated that after 4 weeks of training, the clinical scale score, event-related desynchronization (ERD) of EEG patterns, and cerebral oxygen response of patients with stroke were enhanced obviously. This study preliminarily verified the clinical effectiveness of the long-term NFT system and the prospect of motor function rehabilitation.
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Affiliation(s)
- Zhongpeng Wang
- Academy of Medical Engineering and Translational Medicine, Tianjin University, Tianjin, China
- Department of Biomedical Engineering, College of Precision Instruments and Optoelectronics Engineering, Tianjin University, Tianjin, China
| | - Cong Cao
- Academy of Medical Engineering and Translational Medicine, Tianjin University, Tianjin, China
| | - Long Chen
- Academy of Medical Engineering and Translational Medicine, Tianjin University, Tianjin, China
- *Correspondence: Long Chen
| | - Bin Gu
- Department of Biomedical Engineering, College of Precision Instruments and Optoelectronics Engineering, Tianjin University, Tianjin, China
| | - Shuang Liu
- Academy of Medical Engineering and Translational Medicine, Tianjin University, Tianjin, China
| | - Minpeng Xu
- Academy of Medical Engineering and Translational Medicine, Tianjin University, Tianjin, China
- Department of Biomedical Engineering, College of Precision Instruments and Optoelectronics Engineering, Tianjin University, Tianjin, China
- Tianjin International Joint Research Center for Neural Engineering, Tianjin, China
| | - Feng He
- Academy of Medical Engineering and Translational Medicine, Tianjin University, Tianjin, China
- Department of Biomedical Engineering, College of Precision Instruments and Optoelectronics Engineering, Tianjin University, Tianjin, China
- Tianjin International Joint Research Center for Neural Engineering, Tianjin, China
| | - Dong Ming
- Academy of Medical Engineering and Translational Medicine, Tianjin University, Tianjin, China
- Department of Biomedical Engineering, College of Precision Instruments and Optoelectronics Engineering, Tianjin University, Tianjin, China
- Tianjin International Joint Research Center for Neural Engineering, Tianjin, China
- Dong Ming
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Peng Y, Wang J, Liu Z, Zhong L, Wen X, Wang P, Gong X, Liu H. The Application of Brain-Computer Interface in Upper Limb Dysfunction After Stroke: A Systematic Review and Meta-Analysis of Randomized Controlled Trials. Front Hum Neurosci 2022; 16:798883. [PMID: 35422693 PMCID: PMC9001895 DOI: 10.3389/fnhum.2022.798883] [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: 10/20/2021] [Accepted: 02/17/2022] [Indexed: 11/13/2022] Open
Abstract
Objective This study aimed to examine the effectiveness and safety of the Brain-computer interface (BCI) in treatment of upper limb dysfunction after stroke. Methods English and Chinese electronic databases were searched up to July 2021. Randomized controlled trials (RCTs) were eligible. The methodological quality was assessed using Cochrane’s risk-of-bias tool. Meta-analysis was performed using RevMan 5.4. Results A total of 488 patients from 16 RCTs were included. The results showed that (1) the meta-analysis of BCI-combined treatment on the improvement of the upper limb function showed statistical significance [standardized mean difference (SMD): 0.53, 95% CI: 0.26–0.80, P < 0.05]; (2) BCI treatment can improve the abilities of daily living of patients after stroke, and the analysis results are statistically significant (SMD: 1.67, 95% CI: 0.61–2.74, P < 0.05); and (3) the BCI-combined therapy was not statistically significant for the analysis of the Modified Ashworth Scale (MAS) (SMD: −0.10, 95% CI: −0.50 to 0.30, P = 0.61). Conclusion The meta-analysis indicates that the BCI therapy or BCI combined with other therapies such as conventional rehabilitation training and motor imagery training can improve upper limb dysfunction after stroke and enhance the quality of daily life.
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Affiliation(s)
- Yang Peng
- Department of Rehabilitation Medicine, Yue Bei People’s Hospital, Shaoguan, China
| | - Jing Wang
- Department of Rehabilitation Medicine, Yue Bei People’s Hospital, Shaoguan, China
| | - Zicai Liu
- School of Rehabilitation, Gannan Medical University, Ganzhou, China
| | - Lida Zhong
- Department of Rehabilitation Medicine, Yue Bei People’s Hospital, Shaoguan, China
| | - Xin Wen
- School of Rehabilitation, Gannan Medical University, Ganzhou, China
| | - Pu Wang
- Department of Rehabilitation Medicine, The Seventh Affiliated Hospital, Sun Yat-sen University, Shenzhen, China
- *Correspondence: Pu Wang,
| | - Xiaoqian Gong
- Yue Bei People’s Hospital, Shaoguan, China
- Xiaoqian Gong,
| | - Huiyu Liu
- Department of Rehabilitation Medicine, Yue Bei People’s Hospital, Shaoguan, China
- Huiyu Liu,
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Tavazzi E, Bergsland N, Pirastru A, Cazzoli M, Blasi V, Baglio F. MRI markers of functional connectivity and tissue microstructure in stroke-related motor rehabilitation: A systematic review. Neuroimage Clin 2021; 33:102931. [PMID: 34995869 PMCID: PMC8741615 DOI: 10.1016/j.nicl.2021.102931] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/08/2021] [Revised: 12/27/2021] [Accepted: 12/28/2021] [Indexed: 12/18/2022]
Abstract
BACKGROUND Stroke-related disability is a major problem at individual and socio-economic levels. Neuromotor rehabilitation has a key role for its dual action on affected body segment and brain reorganization. Despite its known efficacy in clinical practice, the extent and type of effect at a brain level, mediated by neuroplasticity, are still under question. OBJECTIVE To analyze studies applying MRI markers of functional and structural connectivity in patients affected with stroke undergoing motor rehabilitation, and to evaluate the effect of rehabilitation on brain reorganization. METHODS Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) criteria were applied to select studies applying quantitative non-conventional MRI techniques on patients undergoing motor rehabilitation, both physical and virtual (virtual reality, mental imagery). Literature search was conducted using MEDLINE (via PubMed), Cochrane Central Register of Controlled Trials (CENTRAL), and EMBASE from inception to 30th June 2020. RESULTS Forty-one out of 6983 papers were included in the current review. Selected studies are heterogeneous in terms of patient characteristics as well as type, duration and frequency of rehabilitative approach. Neuromotor rehabilitation promotes neuroplasticity, favoring functional recovery of the ipsilesional hemisphere and activation of anatomically and functionally related brain areas in both hemispheres, to compensate for damaged tissue. CONCLUSIONS The evidence derived from the analyzed studies supports the positive impact of rehabilitation on brain reorganization, despite the high data heterogeneity. Advanced MRI techniques provide reliable markers of structural and functional connectivity that may potentially aid in helping to implement the most appropriate rehabilitation intervention.
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Affiliation(s)
- E Tavazzi
- IRCCS, Fondazione Don Carlo Gnocchi ONLUS, Milan, Italy; Department of Neurology, Buffalo Neuroimaging Analysis Center, School of Medicine and Biomedical Sciences, University at Buffalo, State University of New York, Buffalo, NY, United States
| | - N Bergsland
- IRCCS, Fondazione Don Carlo Gnocchi ONLUS, Milan, Italy; Department of Neurology, Buffalo Neuroimaging Analysis Center, School of Medicine and Biomedical Sciences, University at Buffalo, State University of New York, Buffalo, NY, United States.
| | - A Pirastru
- IRCCS, Fondazione Don Carlo Gnocchi ONLUS, Milan, Italy
| | - M Cazzoli
- IRCCS, Fondazione Don Carlo Gnocchi ONLUS, Milan, Italy
| | - V Blasi
- IRCCS, Fondazione Don Carlo Gnocchi ONLUS, Milan, Italy
| | - F Baglio
- IRCCS, Fondazione Don Carlo Gnocchi ONLUS, Milan, Italy
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Nojima I, Sugata H, Takeuchi H, Mima T. Brain-Computer Interface Training Based on Brain Activity Can Induce Motor Recovery in Patients With Stroke: A Meta-Analysis. Neurorehabil Neural Repair 2021; 36:83-96. [PMID: 34958261 DOI: 10.1177/15459683211062895] [Citation(s) in RCA: 11] [Impact Index Per Article: 3.7] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/15/2022]
Abstract
BACKGROUND Brain-computer interface (BCI) is a procedure involving brain activity in which neural status is provided to the participants for self-regulation. The current review aims to evaluate the effect sizes of clinical studies investigating the use of BCI-based rehabilitation interventions in restoring upper extremity function and effective methods to detect brain activity for motor recovery. METHODS A computerized search of MEDLINE, CENTRAL, Web of Science, and PEDro was performed to identify relevant articles. We selected clinical trials that used BCI-based training for post-stroke patients and provided motor assessment scores before and after the intervention. The pooled standardized mean differences of BCI-based training were calculated using the random-effects model. RESULTS We initially identified 655 potentially relevant articles; finally, 16 articles fulfilled the inclusion criteria, involving 382 participants. A significant effect of neurofeedback intervention for the paretic upper limb was observed (standardized mean difference = .48, [.16-.80], P = .006). However, the effect estimates were moderately heterogeneous among the studies (I2 = 45%, P = .03). Subgroup analysis of the method of measurement of brain activity indicated the effectiveness of the algorithm focusing on sensorimotor rhythm. CONCLUSION This meta-analysis suggested that BCI-based training was superior to conventional interventions for motor recovery of the upper limbs in patients with stroke. However, the results are not conclusive because of a high risk of bias and a large degree of heterogeneity due to the differences in the BCI interventions and the participants; therefore, further studies involving larger cohorts are required to confirm these results.
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Affiliation(s)
- Ippei Nojima
- Department of Physical Therapy, 84161Shinshu University School of Health Sciences, Matsumoto, Japan
| | - Hisato Sugata
- Faculty of Welfare and Health Science, 6339Oita University, Oita, Japan
| | - Hiroki Takeuchi
- National Hospital Organization, 73721Higashinagoya National Hospital, Nagoya, Japan
| | - Tatsuya Mima
- Graduate School of Core Ethics and Frontier Sciences, 316844Ritsumeikan University, Kyoto, Japan
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Emerging trends in BCI-robotics for motor control and rehabilitation. CURRENT OPINION IN BIOMEDICAL ENGINEERING 2021. [DOI: 10.1016/j.cobme.2021.100354] [Citation(s) in RCA: 3] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/19/2022]
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Chen S, Shu X, Wang H, Ding L, Fu J, Jia J. The Differences Between Motor Attempt and Motor Imagery in Brain-Computer Interface Accuracy and Event-Related Desynchronization of Patients With Hemiplegia. Front Neurorobot 2021; 15:706630. [PMID: 34803647 PMCID: PMC8602190 DOI: 10.3389/fnbot.2021.706630] [Citation(s) in RCA: 16] [Impact Index Per Article: 5.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/07/2021] [Accepted: 10/07/2021] [Indexed: 11/13/2022] Open
Abstract
Background: Motor attempt and motor imagery (MI) are two common motor tasks used in brain-computer interface (BCI). They are widely researched for motor rehabilitation in patients with hemiplegia. The differences between the motor attempt (MA) and MI tasks of patients with hemiplegia can be used to promote BCI application. This study aimed to explore the accuracy of BCI and event-related desynchronization (ERD) between the two tasks. Materials and Methods: We recruited 13 patients with stroke and 3 patients with traumatic brain injury, to perform MA and MI tasks in a self-control design. The BCI accuracies from the bilateral, ipsilesional, and contralesional hemispheres were analyzed and compared between different tasks. The cortical activation patterns were evaluated with ERD and laterality index (LI). Results: The study showed that the BCI accuracies of MA were significantly (p < 0.05) higher than MI in the bilateral, ipsilesional, and contralesional hemispheres in the alpha-beta (8–30 Hz) frequency bands. There was no significant difference in ERD and LI between the MA and MI tasks in the 8–30 Hz frequency bands. However, in the MA task, there was a negative correlation between the ERD values in the channel CP1 and ipsilesional hemispheric BCI accuracies (r = −0.552, p = 0.041, n = 14) and a negative correlation between the ERD values in channel CP2 and bilateral hemispheric BCI accuracies (r = −0.543, p = 0.045, n = 14). While in the MI task, there were negative correlations between the ERD values in channel C4 and bilateral hemispheric BCI accuracies (r = −0.582, p = 0.029, n = 14) as well as the contralesional hemispheric BCI accuracies (r = −0.657, p = 0.011, n = 14). As for motor dysfunction, there was a significant positive correlation between the ipsilesional BCI accuracies and FMA scores of the hand part in 8–13 Hz (r = 0.565, p = 0.035, n = 14) in the MA task and a significant positive correlation between the ipsilesional BCI accuracies and FMA scores of the hand part in 13–30 Hz (r = 0.558, p = 0.038, n = 14) in the MI task. Conclusion: The MA task may achieve better BCI accuracy but have similar cortical activations with the MI task. Cortical activation (ERD) may influence the BCI accuracy, which should be carefully considered in the BCI motor rehabilitation of patients with hemiplegia.
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Affiliation(s)
- Shugeng Chen
- Department of Rehabilitation Medicine, Huashan Hospital, Fudan University, Shanghai, China
| | - Xiaokang Shu
- School of Mechanical Engineering, Shanghai Jiao Tong University, Shanghai, China
| | - Hewei Wang
- Department of Rehabilitation Medicine, Huashan Hospital, Fudan University, Shanghai, China
| | - Li Ding
- Department of Rehabilitation Medicine, Huashan Hospital, Fudan University, Shanghai, China
| | - Jianghong Fu
- Department of Rehabilitation Medicine, Huashan Hospital, Fudan University, Shanghai, China
| | - Jie Jia
- Department of Rehabilitation Medicine, Huashan Hospital, Fudan University, Shanghai, China.,National Clinical Research Center for Aging and Medicine, Huashan Hospital, Fudan University, Shanghai, China.,National Center for Neurological Disorders, Shanghai, China
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Motor Imagery-Based Brain-Computer Interface Combined with Multimodal Feedback to Promote Upper Limb Motor Function after Stroke: A Preliminary Study. EVIDENCE-BASED COMPLEMENTARY AND ALTERNATIVE MEDICINE 2021; 2021:1116126. [PMID: 34777531 PMCID: PMC8580676 DOI: 10.1155/2021/1116126] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Received: 09/06/2021] [Accepted: 10/11/2021] [Indexed: 01/21/2023]
Abstract
Background Recently, the brain-computer interface (BCI) has seen rapid development, which may promote the recovery of motor function in chronic stroke patients. Methods Twelve stroke patients with severe upper limb and hand motor impairment were enrolled and randomly assigned into two groups: motor imagery (MI)-based BCI training with multimodal feedback (BCI group, n = 7) and classical motor imagery training (control group, n = 5). Motor function and electrophysiology were evaluated before and after the intervention. The Fugl-Meyer assessment-upper extremity (FMA-UE) is the primary outcome measure. Secondary outcome measures include an increase in wrist active extension or surface electromyography (the amplitude and cocontraction of extensor carpi radialis during movement), the action research arm test (ARAT), the motor status scale (MSS), and Barthel index (BI). Time-frequency analysis and power spectral analysis were used to reflect the electroencephalogram (EEG) change before and after the intervention. Results Compared with the baseline, the FMA-UE score increased significantly in the BCI group (p = 0.006). MSS scores improved significantly in both groups, while ARAT did not improve significantly. In addition, before the intervention, all patients could not actively extend their wrists or just had muscle contractions. After the intervention, four patients regained the ability to extend their paretic wrists (two in each group). The amplitude and area under the curve of extensor carpi radialis improved to some extent, but there was no statistical significance between the groups. Conclusion MI-based BCI combined with sensory and visual feedback might improve severe upper limb and hand impairment in chronic stroke patients, showing the potential for application in rehabilitation medicine.
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Sinha AM, Nair VA, Prabhakaran V. Brain-Computer Interface Training With Functional Electrical Stimulation: Facilitating Changes in Interhemispheric Functional Connectivity and Motor Outcomes Post-stroke. Front Neurosci 2021; 15:670953. [PMID: 34646112 PMCID: PMC8503522 DOI: 10.3389/fnins.2021.670953] [Citation(s) in RCA: 7] [Impact Index Per Article: 2.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/22/2021] [Accepted: 08/30/2021] [Indexed: 11/13/2022] Open
Abstract
While most survivors of stroke experience some spontaneous recovery and receive treatment in the subacute setting, they are often left with persistent impairments in upper limb sensorimotor function which impact autonomy in daily life. Brain-Computer Interface (BCI) technology has shown promise as a form of rehabilitation that can facilitate motor recovery after stroke, however, we have a limited understanding of the changes in functional connectivity and behavioral outcomes associated with its use. Here, we investigate the effects of EEG-based BCI intervention with functional electrical stimulation (FES) on resting-state functional connectivity (rsFC) and motor outcomes in stroke recovery. 23 patients post-stroke with upper limb motor impairment completed BCI intervention with FES. Resting-state functional magnetic resonance imaging (rs-fMRI) scans and behavioral data were collected prior to intervention, post- and 1-month post-intervention. Changes in rsFC within the motor network and behavioral measures were investigated to identify brain-behavior correlations. At the group-level, there were significant increases in interhemispheric and network rsFC in the motor network after BCI intervention, and patients significantly improved on the Action Research Arm Test (ARAT) and SIS domains. Notably, changes in interhemispheric rsFC from pre- to both post- and 1 month post-intervention correlated with behavioral improvements across several motor-related domains. These findings suggest that BCI intervention with FES can facilitate interhemispheric connectivity changes and upper limb motor recovery in patients after stroke.
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Affiliation(s)
- Anita M Sinha
- Department of Biomedical Engineering, University of Wisconsin-Madison, Madison, WI, United States.,Department of Radiology, University of Wisconsin-Madison, Madison, WI, United States
| | - Veena A Nair
- Department of Radiology, University of Wisconsin-Madison, Madison, WI, United States
| | - Vivek Prabhakaran
- Department of Radiology, University of Wisconsin-Madison, Madison, WI, United States
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Intracortical Microelectrode Array Unit Yield under Chronic Conditions: A Comparative Evaluation. MICROMACHINES 2021; 12:mi12080972. [PMID: 34442594 PMCID: PMC8400387 DOI: 10.3390/mi12080972] [Citation(s) in RCA: 14] [Impact Index Per Article: 4.7] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Received: 05/21/2021] [Revised: 08/10/2021] [Accepted: 08/12/2021] [Indexed: 01/01/2023]
Abstract
While microelectrode arrays (MEAs) offer the promise of elucidating functional neural circuitry and serve as the basis for a cortical neuroprosthesis, the challenge of designing and demonstrating chronically reliable technology remains. Numerous studies report “chronic” data but the actual time spans and performance measures corresponding to the experimental work vary. In this study, we reviewed the experimental durations that constitute chronic studies across a range of MEA types and animal species to gain an understanding of the widespread variability in reported study duration. For rodents, which are the most commonly used animal model in chronic studies, we examined active electrode yield (AEY) for different array types as a means to contextualize the study duration variance, as well as investigate and interpret the performance of custom devices in comparison to conventional MEAs. We observed wide-spread variance within species for the chronic implantation period and an AEY that decayed linearly in rodent models that implanted commercially-available devices. These observations provide a benchmark for comparing the performance of new technologies and highlight the need for consistency in chronic MEA studies. Additionally, to fully derive performance under chronic conditions, the duration of abiotic failure modes, biological processes induced by indwelling probes, and intended application of the device are key determinants.
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34
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Hu M, Cheng HJ, Ji F, Chong JSX, Lu Z, Huang W, Ang KK, Phua KS, Chuang KH, Jiang X, Chew E, Guan C, Zhou JH. Brain Functional Changes in Stroke Following Rehabilitation Using Brain-Computer Interface-Assisted Motor Imagery With and Without tDCS: A Pilot Study. Front Hum Neurosci 2021; 15:692304. [PMID: 34335210 PMCID: PMC8322606 DOI: 10.3389/fnhum.2021.692304] [Citation(s) in RCA: 11] [Impact Index Per Article: 3.7] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/08/2021] [Accepted: 06/24/2021] [Indexed: 11/13/2022] Open
Abstract
Brain-computer interface-assisted motor imagery (MI-BCI) or transcranial direct current stimulation (tDCS) has been proven effective in post-stroke motor function enhancement, yet whether the combination of MI-BCI and tDCS may further benefit the rehabilitation of motor functions remains unknown. This study investigated brain functional activity and connectivity changes after a 2 week MI-BCI and tDCS combined intervention in 19 chronic subcortical stroke patients. Patients were randomized into MI-BCI with tDCS group and MI-BCI only group who underwent 10 sessions of 20 min real or sham tDCS followed by 1 h MI-BCI training with robotic feedback. We derived amplitude of low-frequency fluctuation (ALFF), regional homogeneity (ReHo), and functional connectivity (FC) from resting-state functional magnetic resonance imaging (fMRI) data pre- and post-intervention. At baseline, stroke patients had lower ALFF in the ipsilesional somatomotor network (SMN), lower ReHo in the contralesional insula, and higher ALFF/Reho in the bilateral posterior default mode network (DMN) compared to age-matched healthy controls. After the intervention, the MI-BCI only group showed increased ALFF in contralesional SMN and decreased ALFF/Reho in the posterior DMN. In contrast, no post-intervention changes were detected in the MI-BCI + tDCS group. Furthermore, higher increases in ALFF/ReHo/FC measures were related to better motor function recovery (measured by the Fugl-Meyer Assessment scores) in the MI-BCI group while the opposite association was detected in the MI-BCI + tDCS group. Taken together, our findings suggest that brain functional re-normalization and network-specific compensation were found in the MI-BCI only group but not in the MI-BCI + tDCS group although both groups gained significant motor function improvement post-intervention with no group difference. MI-BCI and tDCS may exert differential or even opposing impact on brain functional reorganization during post-stroke motor rehabilitation; therefore, the integration of the two strategies requires further refinement to improve efficacy and effectiveness.
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Affiliation(s)
- Mengjiao Hu
- NTU Institute for Health Technologies, Interdisciplinary Graduate Programme, Nanyang Technological University, Singapore, Singapore.,Center for Sleep and Cognition, Center for Translational MR Research, Yong Loo Lin School of Medicine, National University of Singapore, Singapore, Singapore
| | - Hsiao-Ju Cheng
- Center for Sleep and Cognition, Center for Translational MR Research, Yong Loo Lin School of Medicine, National University of Singapore, Singapore, Singapore.,Department of Biomedical Engineering, Faculty of Engineering, National University of Singapore, Singapore, Singapore
| | - Fang Ji
- Center for Sleep and Cognition, Center for Translational MR Research, Yong Loo Lin School of Medicine, National University of Singapore, Singapore, Singapore
| | - Joanna Su Xian Chong
- Center for Sleep and Cognition, Center for Translational MR Research, Yong Loo Lin School of Medicine, National University of Singapore, Singapore, Singapore
| | - Zhongkang Lu
- Institute for Infocomm Research, Agency for Science Technology and Research, Singapore, Singapore
| | - Weimin Huang
- Institute for Infocomm Research, Agency for Science Technology and Research, Singapore, Singapore
| | - Kai Keng Ang
- Institute for Infocomm Research, Agency for Science Technology and Research, Singapore, Singapore.,School of Computer Science and Engineering, Nanyang Technological University, Singapore, Singapore
| | - Kok Soon Phua
- Institute for Infocomm Research, Agency for Science Technology and Research, Singapore, Singapore
| | - Kai-Hsiang Chuang
- Singapore Bioimaging Consortium, Agency for Science Technology and Research, Singapore, Singapore.,Queensland Brain Institute and Centre for Advanced Imaging, The University of Queensland, Brisbane, QLD, Australia
| | - Xudong Jiang
- School of Electrical and Electronic Engineering, Nanyang Technological University, Singapore, Singapore
| | - Effie Chew
- Division of Neurology, University Medicine Cluster, National University Health System, Singapore, Singapore
| | - Cuntai Guan
- School of Computer Science and Engineering, Nanyang Technological University, Singapore, Singapore
| | - Juan Helen Zhou
- Center for Sleep and Cognition, Center for Translational MR Research, Yong Loo Lin School of Medicine, National University of Singapore, Singapore, Singapore.,Department of Electrical and Computer Engineering, National University of Singapore, Singapore, Singapore.,Integrative Sciences and Engineering Programme (ISEP), National University of Singapore, Singapore, Singapore
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35
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Araujo RS, Silva CR, Netto SPN, Morya E, Brasil FL. Development of a Low-Cost EEG-Controlled Hand Exoskeleton 3D Printed on Textiles. Front Neurosci 2021; 15:661569. [PMID: 34248478 PMCID: PMC8267155 DOI: 10.3389/fnins.2021.661569] [Citation(s) in RCA: 14] [Impact Index Per Article: 4.7] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/31/2021] [Accepted: 05/03/2021] [Indexed: 12/20/2022] Open
Abstract
Stroke survivors can be affected by motor deficits in the hand. Robotic equipment associated with brain–machine interfaces (BMI) may aid the motor rehabilitation of these patients. BMIs involving orthotic control by motor imagery practices have been successful in restoring stroke patients' movements. However, there is still little acceptance of the robotic devices available, either by patients and clinicians, mainly because of the high costs involved. Motivated by this context, this work aims to design and construct the Hand Exoskeleton for Rehabilitation Objectives (HERO) to recover extension and flexion movements of the fingers. A three-dimensional (3D) printing technique in association with textiles was used to produce a lightweight and wearable device. 3D-printed actuators have also been designed to reduce equipment costs. The actuator transforms the torque of DC motors into linear force transmitted by Bowden cables to move the fingers passively. The exoskeleton was controlled by neuroelectric signal—electroencephalography (EEG). Concept tests were performed to evaluate control performance. A healthy volunteer was submitted to a training session with the exoskeleton, according to the Graz-BCI protocol. Ergonomy was evaluated with a two-dimensional (2D) tracking software and correlation analysis. HERO can be compared to ordinary clothing. The weight over the hand was around 102 g. The participant was able to control the exoskeleton with a classification accuracy of 91.5%. HERO project resulted in a lightweight, simple, portable, ergonomic, and low-cost device. Its use is not restricted to a clinical setting. Thus, users will be able to execute motor training with the HERO at hospitals, rehabilitation clinics, and at home, increasing the rehabilitation intervention time. This may support motor rehabilitation and improve stroke survivors life quality.
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Affiliation(s)
- Rommel S Araujo
- Edmond and Lily Safra International Institute of Neuroscience, Santos Dumont Institute, Macaíba, Brazil
| | - Camille R Silva
- Federal Institute of Education, Science and Technology of Rio Grande Do Norte, Ceara-Mirim Campus, Ceará-Mirim, Brazil
| | - Severino P N Netto
- Edmond and Lily Safra International Institute of Neuroscience, Santos Dumont Institute, Macaíba, Brazil
| | - Edgard Morya
- Edmond and Lily Safra International Institute of Neuroscience, Santos Dumont Institute, Macaíba, Brazil
| | - Fabricio L Brasil
- Edmond and Lily Safra International Institute of Neuroscience, Santos Dumont Institute, Macaíba, Brazil
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36
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Silva EMGS, Holanda LJ, Coutinho GKB, Andrade FS, Nascimento GIS, Nagem DAP, Valentim RADM, Lindquist AR. Effects of Active Upper Limb Orthoses Using Brain-Machine Interfaces for Rehabilitation of Patients With Neurological Disorders: Protocol for a Systematic Review and Meta-Analysis. Front Neurosci 2021; 15:661494. [PMID: 34248477 PMCID: PMC8264786 DOI: 10.3389/fnins.2021.661494] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/30/2021] [Accepted: 05/04/2021] [Indexed: 12/01/2022] Open
Abstract
Introduction: The field of brain–machine interfaces (BMI) for upper limb (UL) orthoses is growing exponentially due to improvements in motor performance, quality of life, and functionality of people with neurological diseases. Considering this, we planned a systematic review to investigate the effects of BMI-controlled UL orthoses for rehabilitation of patients with neurological disorders. Methods: This systematic review and meta-analysis protocol was elaborated according to the Preferred Reporting Items for Systematic Reviews and Meta-Analyses Protocols (PRISMA-P 2015) and Cochrane Handbook for Systematic Reviews of Interventions. A search will be conducted on Pubmed, IEEE Xplore Digital Library, Medline, and Web of Science databases without language and year restrictions, and Patents Scope, Patentlens, and Google Patents websites in English, Spanish, French, German, and Portuguese between 2011 and 2021. Two independent reviewers will include randomized controlled trials and quasi-experimental studies using BMI-controlled active UL orthoses to improve human movement. Studies must contain participants aged >18 years, diagnosed with neurological disorders, and with impaired UL movement. Three independent reviewers will conduct the same procedure for patents. Evidence quality and risk of bias will be evaluated following the Cochrane collaboration by two review authors. Meta-analysis will be conducted in case of homogeneity between groups. Otherwise, a narrative synthesis will be performed. Data will be inserted into a table containing physical description, UL orthoses control system, and effect of BMI-controlled orthoses. Discussion: BMI-controlled orthoses can assist individuals in several routine activities and provide functional independence and sense of overcoming limitations imposed by the underlying disease. These benefits will also be associated with orthoses descriptions, safety, portability, adverse events, and tools used to assess UL motor performance in patients with neurological disorders. PROSPERO Registration Number: CRD42020182195.
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Affiliation(s)
- Emília M G S Silva
- Laboratory of Intervention and Analysis of Movement, Department of Physical Therapy, Federal University of Rio Grande do Norte, Natal, Brazil.,Laboratory of Technological Innovation in Health, Federal University of Rio Grande do Norte, Natal, Brazil
| | - Ledycnarf J Holanda
- Laboratory of Intervention and Analysis of Movement, Department of Physical Therapy, Federal University of Rio Grande do Norte, Natal, Brazil.,Laboratory of Technological Innovation in Health, Federal University of Rio Grande do Norte, Natal, Brazil
| | - Gustavo K B Coutinho
- Laboratory of Technological Innovation in Health, Federal University of Rio Grande do Norte, Natal, Brazil
| | - Fernanda S Andrade
- Laboratory of Technological Innovation in Health, Federal University of Rio Grande do Norte, Natal, Brazil.,Department of Biomedical Engineering, Federal University of Rio Grande do Norte, Natal, Brazil
| | - Gabriel I S Nascimento
- Laboratory of Technological Innovation in Health, Federal University of Rio Grande do Norte, Natal, Brazil
| | - Danilo A P Nagem
- Laboratory of Technological Innovation in Health, Federal University of Rio Grande do Norte, Natal, Brazil.,Department of Biomedical Engineering, Federal University of Rio Grande do Norte, Natal, Brazil
| | - Ricardo A de M Valentim
- Laboratory of Technological Innovation in Health, Federal University of Rio Grande do Norte, Natal, Brazil.,Department of Biomedical Engineering, Federal University of Rio Grande do Norte, Natal, Brazil
| | - Ana Raquel Lindquist
- Laboratory of Intervention and Analysis of Movement, Department of Physical Therapy, Federal University of Rio Grande do Norte, Natal, Brazil.,Laboratory of Technological Innovation in Health, Federal University of Rio Grande do Norte, Natal, Brazil
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37
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Exploring the Use of Brain-Computer Interfaces in Stroke Neurorehabilitation. BIOMED RESEARCH INTERNATIONAL 2021; 2021:9967348. [PMID: 34239936 PMCID: PMC8235968 DOI: 10.1155/2021/9967348] [Citation(s) in RCA: 18] [Impact Index Per Article: 6.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Received: 03/20/2021] [Accepted: 06/04/2021] [Indexed: 11/17/2022]
Abstract
With the continuous development of artificial intelligence technology, "brain-computer interfaces" are gradually entering the field of medical rehabilitation. As a result, brain-computer interfaces (BCIs) have been included in many countries' strategic plans for innovating this field, and subsequently, major funding and talent have been invested in this technology. In neurological rehabilitation for stroke patients, the use of BCIs opens up a new chapter in "top-down" rehabilitation. In our study, we first reviewed the latest BCI technologies, then presented recent research advances and landmark findings in BCI-based neurorehabilitation for stroke patients. Neurorehabilitation was focused on the areas of motor, sensory, speech, cognitive, and environmental interactions. Finally, we summarized the shortcomings of BCI use in the field of stroke neurorehabilitation and the prospects for BCI technology development for rehabilitation.
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38
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Irastorza-Landa N, García-Cossio E, Sarasola-Sanz A, Brötz D, Birbaumer N, Ramos-Murguialday A. Functional synergy recruitment index as a reliable biomarker of motor function and recovery in chronic stroke patients. J Neural Eng 2021; 18. [PMID: 33530072 DOI: 10.1088/1741-2552/abe244] [Citation(s) in RCA: 9] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/03/2020] [Accepted: 02/02/2021] [Indexed: 12/14/2022]
Abstract
Objective. Stroke affects the expression of muscle synergies underlying motor control, most notably in patients with poorer motor function. The majority of studies on muscle synergies have conventionally approached this analysis by assuming alterations in the inner structures of synergies after stroke. Although different synergy-based features based on this assumption have to some extent described pathological mechanisms in post-stroke neuromuscular control, a biomarker that reliably reflects motor function and recovery is still missing.Approach. Based on the theory of muscle synergies, we alternatively hypothesize that functional synergy structures are physically preserved and measure the temporal correlation between the recruitment profiles of healthy modules by paretic and healthy muscles, a feature hereafter reported as the FSRI. We measured clinical scores and extracted the muscle synergies of both ULs of 18 chronic stroke survivors from the electromyographic activity of 8 muscles during bilateral movements before and after 4 weeks of non-invasive BMI controlled robot therapy and physiotherapy. We computed the FSRI as well as features quantifying inter-limb structural differences and evaluated the correlation of these synergy-based measures with clinical scores.Main results. Correlation analysis revealed weak relationships between conventional features describing inter-limb synergy structural differences and motor function. In contrast, FSRI values during specific or combined movement data significantly correlated with UL motor function and recovery scores. Additionally, we observed that BMI-based training with contingent positive proprioceptive feedback led to improved FSRI values during the specific trained finger extension movement.Significance. We demonstrated that FSRI can be used as a reliable physiological biomarker of motor function and recovery in stroke, which can be targeted via BMI-based proprioceptive therapies and adjuvant physiotherapy to boost effective rehabilitation.
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Affiliation(s)
- Nerea Irastorza-Landa
- Neuroprosthetics Group, Institute of Medical Psychology and Behavioral Neurobiology, University of Tübingen, Tübingen, Germany.,International Max Planck Research School for Cognitive and Systems Neuroscience, Tübingen, Germany.,IKERBASQUE, Basque Foundation for Science, Bilbao, Spain.,Neurotechnology Laboratory, TECNALIA, Basque Research and Technology Alliance (BRTA), Donostia-San Sebastián, Spain
| | | | - Andrea Sarasola-Sanz
- Neuroprosthetics Group, Institute of Medical Psychology and Behavioral Neurobiology, University of Tübingen, Tübingen, Germany.,Neurotechnology Laboratory, TECNALIA, Basque Research and Technology Alliance (BRTA), Donostia-San Sebastián, Spain
| | - Doris Brötz
- Neuroprosthetics Group, Institute of Medical Psychology and Behavioral Neurobiology, University of Tübingen, Tübingen, Germany
| | - Niels Birbaumer
- Neuroprosthetics Group, Institute of Medical Psychology and Behavioral Neurobiology, University of Tübingen, Tübingen, Germany.,Wyss Center for Bio and Neuroengineering, Geneva, Switzerland
| | - Ander Ramos-Murguialday
- Neuroprosthetics Group, Institute of Medical Psychology and Behavioral Neurobiology, University of Tübingen, Tübingen, Germany.,Neurotechnology Laboratory, TECNALIA, Basque Research and Technology Alliance (BRTA), Donostia-San Sebastián, Spain
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39
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Discussion on the Rehabilitation of Stroke Hemiplegia Based on Interdisciplinary Combination of Medicine and Engineering. EVIDENCE-BASED COMPLEMENTARY AND ALTERNATIVE MEDICINE 2021; 2021:6631835. [PMID: 33815554 PMCID: PMC7990546 DOI: 10.1155/2021/6631835] [Citation(s) in RCA: 4] [Impact Index Per Article: 1.3] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Received: 12/18/2020] [Revised: 01/21/2021] [Accepted: 02/20/2021] [Indexed: 11/25/2022]
Abstract
Interdisciplinary combinations of medicine and engineering are part of the strategic plan of many universities aiming to be world-class institutions. One area in which these interactions have been prominent is rehabilitation of stroke hemiplegia. This article reviews advances in the last five years of stroke hemiplegia rehabilitation via interdisciplinary combination of medicine and engineering. Examples of these technologies include VR, RT, mHealth, BCI, tDCS, rTMS, and TCM rehabilitation. In this article, we will summarize the latest research in these areas and discuss the advantages and disadvantages of each to examine the frontiers of interdisciplinary medicine and engineering advances.
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40
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Lau CCY, Yuan K, Wong PCM, Chu WCW, Leung TW, Wong WW, Tong RKY. Modulation of Functional Connectivity and Low-Frequency Fluctuations After Brain-Computer Interface-Guided Robot Hand Training in Chronic Stroke: A 6-Month Follow-Up Study. Front Hum Neurosci 2021; 14:611064. [PMID: 33551777 PMCID: PMC7855586 DOI: 10.3389/fnhum.2020.611064] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.7] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/28/2020] [Accepted: 12/18/2020] [Indexed: 12/12/2022] Open
Abstract
Hand function improvement in stroke survivors in the chronic stage usually plateaus by 6 months. Brain-computer interface (BCI)-guided robot-assisted training has been shown to be effective for facilitating upper-limb motor function recovery in chronic stroke. However, the underlying neuroplasticity change is not well understood. This study aimed to investigate the whole-brain neuroplasticity changes after 20-session BCI-guided robot hand training, and whether the changes could be maintained at the 6-month follow-up. Therefore, the clinical improvement and the neurological changes before, immediately after, and 6 months after training were explored in 14 chronic stroke subjects. The upper-limb motor function was assessed by Action Research Arm Test (ARAT) and Fugl-Meyer Assessment for Upper-Limb (FMA), and the neurological changes were assessed using resting-state functional magnetic resonance imaging. Repeated-measure ANOVAs indicated that long-term motor improvement was found by both FMA (F[2,26] = 6.367, p = 0.006) and ARAT (F[2,26] = 7.230, p = 0.003). Seed-based functional connectivity analysis exhibited that significantly modulated FC was observed between ipsilesional motor regions (primary motor cortex and supplementary motor area) and contralesional areas (supplementary motor area, premotor cortex, and superior parietal lobule), and the effects were sustained after 6 months. The fALFF analysis showed that local neuronal activities significantly increased in central, frontal and parietal regions, and the effects were also sustained after 6 months. Consistent results in FC and fALFF analyses demonstrated the increase of neural activities in sensorimotor and fronto-parietal regions, which were highly involved in the BCI-guided training. Clinical Trial Registration: This study has been registered at ClinicalTrials.gov with clinical trial registration number NCT02323061.
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Affiliation(s)
- Cathy C Y Lau
- Department of Biomedical Engineering, The Chinese University of Hong Kong, Hong Kong, China
| | - Kai Yuan
- Department of Biomedical Engineering, The Chinese University of Hong Kong, Hong Kong, China
| | - Patrick C M Wong
- Brain and Mind Institute, The Chinese University of Hong Kong, Hong Kong, China
| | - Winnie C W Chu
- Department of Imaging and Interventional Radiology, Prince of Wales Hospital, The Chinese University of Hong Kong, Hong Kong, China
| | - Thomas W Leung
- Department of Medicine and Therapeutics, Prince of Wales Hospital, The Chinese University of Hong Kong, Hong Kong, China
| | - Wan-Wa Wong
- Department of Psychiatry and Biobehavioural Sciences, University of California, Los Angeles, Los Angeles, CA, United States
| | - Raymond K Y Tong
- Department of Biomedical Engineering, The Chinese University of Hong Kong, Hong Kong, China
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41
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Su F, Xu W. Enhancing Brain Plasticity to Promote Stroke Recovery. Front Neurol 2020; 11:554089. [PMID: 33192987 PMCID: PMC7661553 DOI: 10.3389/fneur.2020.554089] [Citation(s) in RCA: 29] [Impact Index Per Article: 7.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/24/2020] [Accepted: 10/08/2020] [Indexed: 12/11/2022] Open
Abstract
Stroke disturbs both the structural and functional integrity of the brain. The understanding of stroke pathophysiology has improved greatly in the past several decades. However, effective therapy is still limited, especially for patients who are in the subacute or chronic phase. Multiple novel therapies have been developed to improve clinical outcomes by improving brain plasticity. These approaches either focus on improving brain remodeling and restoration or on constructing a neural bypass to avoid brain injury. This review describes emerging therapies, including modern rehabilitation, brain stimulation, cell therapy, brain-computer interfaces, and peripheral nervous transfer, and highlights treatment-induced plasticity. Key evidence from basic studies on the underlying mechanisms is also briefly discussed. These insights should lead to a deeper understanding of the overall neural circuit changes, the clinical relevance of these changes in stroke, and stroke treatment progress, which will assist in the development of future approaches to enhance brain function after stroke.
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Affiliation(s)
| | - Wendong Xu
- Department of Hand Surgery, Huashan Hospital, Shanghai Medical College, Fudan University, Shanghai, China
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42
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Sebastián-Romagosa M, Cho W, Ortner R, Murovec N, Von Oertzen T, Kamada K, Allison BZ, Guger C. Brain Computer Interface Treatment for Motor Rehabilitation of Upper Extremity of Stroke Patients-A Feasibility Study. Front Neurosci 2020; 14:591435. [PMID: 33192277 PMCID: PMC7640937 DOI: 10.3389/fnins.2020.591435] [Citation(s) in RCA: 36] [Impact Index Per Article: 9.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/04/2020] [Accepted: 09/10/2020] [Indexed: 12/21/2022] Open
Abstract
Introduction Numerous recent publications have explored Brain Computer Interfaces (BCI) systems as rehabilitation tools to help subacute and chronic stroke patients recover upper extremity movement. Recent work has shown that BCI therapy can lead to better outcomes than conventional therapy. BCI combined with other techniques such as Functional Electrical Stimulation (FES) and Virtual Reality (VR) allows to the user restore the neurological function by inducing the neural plasticity through improved real-time detection of motor imagery (MI) as patients perform therapy tasks. Methods Fifty-one stroke patients with upper extremity hemiparesis were recruited for this study. All participants performed 25 sessions with the MI BCI and assessment visits to track the functional changes before and after the therapy. Results The results of this study demonstrated a significant increase in the motor function of the paretic arm assessed by Fugl-Meyer Assessment (FMA-UE), ΔFMA-UE = 4.68 points, P < 0.001, reduction of the spasticity in the wrist and fingers assessed by Modified Ashworth Scale (MAS), ΔMAS-wrist = -0.72 points (SD = 0.83), P < 0.001, ΔMAS-fingers = -0.63 points (SD = 0.82), P < 0.001. Other significant improvements in the grasp ability were detected in the healthy hand. All these functional improvements achieved during the BCI therapy persisted 6 months after the therapy ended. Results also showed that patients with Motor Imagery accuracy (MI) above 80% increase 3.16 points more in the FMA than patients below this threshold (95% CI; [1.47–6.62], P = 0.003). The functional improvement was not related with the stroke severity or with the stroke stage. Conclusion The BCI treatment used here was effective in promoting long lasting functional improvements in the upper extremity in stroke survivors with severe, moderate and mild impairment. This functional improvement can be explained by improved neuroplasticity in the central nervous system.
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Affiliation(s)
| | - Woosang Cho
- g.tec Medical Engineering GmbH, Schiedlberg, Austria.,Institute of Medical Psychology and Behavioral Neurobiology, University of Tübingen, Tübingen, Germany.,International Max Planck Research School for Neural & Behavioral Sciences, Tübingen, Germany
| | - Rupert Ortner
- g.tec Medical Engineering Spain SL, Barcelona, Spain
| | - Nensi Murovec
- g.tec Medical Engineering GmbH, Schiedlberg, Austria
| | - Tim Von Oertzen
- Department of Neurology 1, Kepler Universitätsklinik, Linz, Austria
| | | | - Brendan Z Allison
- Department of Cognitive Science, University of California, San Diego, San Diego, CA, United States
| | - Christoph Guger
- g.tec Medical Engineering Spain SL, Barcelona, Spain.,g.tec Medical Engineering GmbH, Schiedlberg, Austria
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Temporal frequency joint sparse optimization and fuzzy fusion for motor imagery-based brain-computer interfaces. J Neurosci Methods 2020; 340:108725. [DOI: 10.1016/j.jneumeth.2020.108725] [Citation(s) in RCA: 10] [Impact Index Per Article: 2.5] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/26/2020] [Revised: 04/02/2020] [Accepted: 04/03/2020] [Indexed: 11/20/2022]
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The Promotoer, a brain-computer interface-assisted intervention to promote upper limb functional motor recovery after stroke: a study protocol for a randomized controlled trial to test early and long-term efficacy and to identify determinants of response. BMC Neurol 2020; 20:254. [PMID: 32593293 PMCID: PMC7320550 DOI: 10.1186/s12883-020-01826-w] [Citation(s) in RCA: 14] [Impact Index Per Article: 3.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/21/2020] [Accepted: 06/10/2020] [Indexed: 01/21/2023] Open
Abstract
BACKGROUND Stroke is a leading cause of long-term disability. Cost-effective post-stroke rehabilitation programs for upper limb are critically needed. Brain-Computer Interfaces (BCIs) which enable the modulation of Electroencephalography (EEG) sensorimotor rhythms are promising tools to promote post-stroke recovery of upper limb motor function. The "Promotoer" study intends to boost the application of the EEG-based BCIs in clinical practice providing evidence for a short/long-term efficacy in enhancing post-stroke hand functional motor recovery and quantifiable indices of the participants response to a BCI-based intervention. To these aims, a longitudinal study will be performed in which subacute stroke participants will undergo a hand motor imagery (MI) training assisted by the Promotoer system, an EEG-based BCI system fully compliant with rehabilitation requirements. METHODS This longitudinal 2-arm randomized controlled superiority trial will include 48 first ever, unilateral, subacute stroke participants, randomly assigned to 2 intervention groups: the BCI-assisted hand MI training and a hand MI training not supported by BCI. Both interventions are delivered (3 weekly session; 6 weeks) as add-on regimen to standard intensive rehabilitation. A multidimensional assessment will be performed at: randomization/pre-intervention, 48 h post-intervention, and at 1, 3 and 6 month/s after end of intervention. Primary outcome measure is the Fugl-Meyer Assessment (FMA, upper extremity) at 48 h post-intervention. Secondary outcome measures include: the upper extremity FMA at follow-up, the Modified Ashworth Scale, the Numeric Rating Scale for pain, the Action Research Arm Test, the National Institute of Health Stroke Scale, the Manual Muscle Test, all collected at the different timepoints as well as neurophysiological and neuroimaging measures. DISCUSSION We expect the BCI-based rewarding of hand MI practice to promote long-lasting retention of the early induced improvement in hand motor outcome and also, this clinical improvement to be sustained by a long-lasting neuroplasticity changes harnessed by the BCI-based intervention. Furthermore, the longitudinal multidimensional assessment will address the selection of those stroke participants who best benefit of a BCI-assisted therapy, consistently advancing the transfer of BCIs to a best clinical practice. TRIAL REGISTRATION Name of registry: BCI-assisted MI Intervention in Subacute Stroke (Promotoer). TRIAL REGISTRATION NUMBER NCT04353297 ; registration date on the ClinicalTrial.gov platform: April, 15/2020.
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Rieke JD, Matarasso AK, Yusufali MM, Ravindran A, Alcantara J, White KD, Daly JJ. Development of a combined, sequential real-time fMRI and fNIRS neurofeedback system to enhance motor learning after stroke. J Neurosci Methods 2020; 341:108719. [PMID: 32439425 DOI: 10.1016/j.jneumeth.2020.108719] [Citation(s) in RCA: 9] [Impact Index Per Article: 2.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/24/2019] [Revised: 03/30/2020] [Accepted: 03/30/2020] [Indexed: 10/24/2022]
Abstract
BACKGROUND After stroke, wrist extension dyscoordination precludes functional arm/hand. We developed a more spatially precise brain signal for use in brain computer interface (BCI's) for stroke survivors. NEW METHOD Combination BCI protocol of real-time functional magnetic resonance imaging (rt-fMRI) sequentially followed by functional near infrared spectroscopy (rt-fNIRS) neurofeedback, interleaved with motor learning sessions without neural feedback. Custom Matlab and Python code was developed to provide rt-fNIRS-based feedback to the chronic stroke survivor, system user. RESULTS The user achieved a maximum of 71 % brain signal accuracy during rt-fNIRS neural training; progressive focus of brain activation across rt-fMRI neural training; increasing trend of brain signal amplitude during wrist extension across rt-fNIRS training; and clinically significant recovery of arm coordination and active wrist extension. COMPARISON WITH EXISTING METHODS Neurorehabilitation, peripherally directed, shows limited efficacy, as do EEG-based BCIs, for motor recovery of moderate/severely impaired stroke survivors. EEG-based BCIs are based on electrophysiological signal; whereas, rt-fMRI and rt-fNIRS are based on neurovascular signal. CONCLUSION The system functioned well during user testing. Methods are detailed for others' use. The system user successfully engaged rt-fMRI and rt-fNIRS neurofeedback systems, modulated brain signal during rt-fMRI and rt-fNIRS training, according to volume of brain activation and intensity of signal, respectively, and clinically significantly improved limb coordination and active wrist extension. fNIRS use in this case demonstrates a feasible/practical BCI system for further study with regard to use in chronic stroke rehab, and fMRI worked in concept, but cost and some patient-use issues make it less feasible for clinical practice.
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Affiliation(s)
- Jake D Rieke
- Brain Rehabilitation Research Center (BRRC), Malcom Randall VA Medical Center (VA), 1600 SW Archer Rd, Gainesville, FL, 32608, USA; Department of Biomedical Engineering (BME), NEB Building, University of Florida, Gainesville, FL, 32608, USA
| | - Avi K Matarasso
- Brain Rehabilitation Research Center (BRRC), Malcom Randall VA Medical Center (VA), 1600 SW Archer Rd, Gainesville, FL, 32608, USA; Dept of Chemical Engineering, NEB Building, UF, Gainesville, FL, 32608, USA
| | - M Minhal Yusufali
- Brain Rehabilitation Research Center (BRRC), Malcom Randall VA Medical Center (VA), 1600 SW Archer Rd, Gainesville, FL, 32608, USA; Department of Biomedical Engineering (BME), NEB Building, University of Florida, Gainesville, FL, 32608, USA
| | - Aniruddh Ravindran
- Brain Rehabilitation Research Center (BRRC), Malcom Randall VA Medical Center (VA), 1600 SW Archer Rd, Gainesville, FL, 32608, USA; Department of Biomedical Engineering (BME), NEB Building, University of Florida, Gainesville, FL, 32608, USA
| | - Jose Alcantara
- Brain Rehabilitation Research Center (BRRC), Malcom Randall VA Medical Center (VA), 1600 SW Archer Rd, Gainesville, FL, 32608, USA; Department of Biomedical Engineering (BME), NEB Building, University of Florida, Gainesville, FL, 32608, USA
| | - Keith D White
- Brain Rehabilitation Research Center (BRRC), Malcom Randall VA Medical Center (VA), 1600 SW Archer Rd, Gainesville, FL, 32608, USA
| | - Janis J Daly
- Brain Rehabilitation Research Center (BRRC), Malcom Randall VA Medical Center (VA), 1600 SW Archer Rd, Gainesville, FL, 32608, USA; Dept of Neurology, College of Medicine, UF, Gainesville, FL, 32608, USA.
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Bai Z, Fong KNK, Zhang JJ, Chan J, Ting KH. Immediate and long-term effects of BCI-based rehabilitation of the upper extremity after stroke: a systematic review and meta-analysis. J Neuroeng Rehabil 2020; 17:57. [PMID: 32334608 PMCID: PMC7183617 DOI: 10.1186/s12984-020-00686-2] [Citation(s) in RCA: 76] [Impact Index Per Article: 19.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/25/2019] [Accepted: 04/07/2020] [Indexed: 11/10/2022] Open
Abstract
BACKGROUND A substantial number of clinical studies have demonstrated the functional recovery induced by the use of brain-computer interface (BCI) technology in patients after stroke. The objective of this review is to evaluate the effect sizes of clinical studies investigating the use of BCIs in restoring upper extremity function after stroke and the potentiating effect of transcranial direct current stimulation (tDCS) on BCI training for motor recovery. METHODS The databases (PubMed, Medline, EMBASE, CINAHL, CENTRAL, PsycINFO, and PEDro) were systematically searched for eligible single-group or clinical controlled studies regarding the effects of BCIs in hemiparetic upper extremity recovery after stroke. Single-group studies were qualitatively described, but only controlled-trial studies were included in the meta-analysis. The PEDro scale was used to assess the methodological quality of the controlled studies. A meta-analysis of upper extremity function was performed by pooling the standardized mean difference (SMD). Subgroup meta-analyses regarding the use of external devices in combination with the application of BCIs were also carried out. We summarized the neural mechanism of the use of BCIs on stroke. RESULTS A total of 1015 records were screened. Eighteen single-group studies and 15 controlled studies were included. The studies showed that BCIs seem to be safe for patients with stroke. The single-group studies consistently showed a trend that suggested BCIs were effective in improving upper extremity function. The meta-analysis (of 12 studies) showed a medium effect size favoring BCIs for improving upper extremity function after intervention (SMD = 0.42; 95% CI = 0.18-0.66; I2 = 48%; P < 0.001; fixed-effects model), while the long-term effect (five studies) was not significant (SMD = 0.12; 95% CI = - 0.28 - 0.52; I2 = 0%; P = 0.540; fixed-effects model). A subgroup meta-analysis indicated that using functional electrical stimulation as the external device in BCI training was more effective than using other devices (P = 0.010). Using movement attempts as the trigger task in BCI training appears to be more effective than using motor imagery (P = 0.070). The use of tDCS (two studies) could not further facilitate the effects of BCI training to restore upper extremity motor function (SMD = - 0.30; 95% CI = - 0.96 - 0.36; I2 = 0%; P = 0.370; fixed-effects model). CONCLUSION The use of BCIs has significant immediate effects on the improvement of hemiparetic upper extremity function in patients after stroke, but the limited number of studies does not support its long-term effects. BCIs combined with functional electrical stimulation may be a better combination for functional recovery than other kinds of neural feedback. The mechanism for functional recovery may be attributed to the activation of the ipsilesional premotor and sensorimotor cortical network.
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Affiliation(s)
- Zhongfei Bai
- Department of Rehabilitation Sciences, The Hong Kong Polytechnic University, Kowloon, Hong Kong SAR.,Department of Occupational Therapy, Shanghai YangZhi Rehabilitation Hospital (Shanghai Sunshine Rehabilitation Center), Shanghai, China.,Department of Rehabilitation Sciences, Tongji University School of Medicine, Shanghai, China
| | - Kenneth N K Fong
- Department of Rehabilitation Sciences, The Hong Kong Polytechnic University, Kowloon, Hong Kong SAR.
| | - Jack Jiaqi Zhang
- Department of Rehabilitation Sciences, The Hong Kong Polytechnic University, Kowloon, Hong Kong SAR
| | - Josephine Chan
- School of Occupational Therapy, Institute of Health Sciences, Texas Woman's University, Houston Center, USA
| | - K H Ting
- University Research Facility in Behavioral and Systems Neuroscience, The Hong Kong Polytechnic University, Kowloon, Hong Kong SAR
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Foldes ST, Boninger ML, Weber DJ, Collinger JL. Effects of MEG-based neurofeedback for hand rehabilitation after tetraplegia: preliminary findings in cortical modulations and grip strength. J Neural Eng 2020; 17:026019. [PMID: 32135525 DOI: 10.1088/1741-2552/ab7cfb] [Citation(s) in RCA: 4] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 01/17/2023]
Abstract
OBJECTIVE Neurofeedback (NF) trains people to volitionally modulate their cortical activity to affect a behavioral outcome. We evaluated the feasibility of using NF to improve hand function after chronic cervical-level spinal cord injury (SCI) using biologically-relevant visual feedback of motor-related brain activity and an intuitive control scheme. APPROACH The NF system acquired magnetoencephalography (MEG) data in real-time to provide feedback of event-related desynchronization (ERD) measured over the sensorimotor cortex during attempted hand grasping. During brain control, stronger ERD resulting from attempted grasping drove the virtual hand towards a more closed grasp, while less ERD drove the hand more open. MAIN RESULTS Eight individuals with partial or complete hand impairment due to chronic SCI controlled the NF to perform a grasping task that increased in difficulty as the participants achieved success. During their first NF session, participants achieved an average success rate of 63.7 ± 6.4% (chance level of 13.9%). After as few as one intervention session, four of the seven individuals evaluated for ERD changes had significantly strengthened ERD and three of the four participants with measurable grip strength prior to NF had increased grip strength. Interestingly, both individuals who participated in a longer-term study (i.e. >8 NF sessions) had improved grip strength and significantly strengthened ERD. SIGNIFICANCE This study demonstrates that MEG-based NF training can change brain activity in individuals with hand impairment due to SCI and has the potential to induce acute changes in grip strength. Future studies will evaluate whether neuroplasticity induced with long term NF can improve hand function for those with moderate impairment.
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Affiliation(s)
- Stephen T Foldes
- VA Pittsburgh Healthcare System, Pittsburgh, PA, United States of America. Rehab Neural Engineering Labs, Departments of Physical Medicine and Rehabilitation and Bioengineering, University of Pittsburgh, Pittsburgh, PA, United States of America. Center for the Neural Basis of Cognition, Pittsburgh, PA, United States of America. Barrow Neurological Institute, Phoenix Children's Hospital, Phoenix, AZ, United States of America
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Caria A, da Rocha JLD, Gallitto G, Birbaumer N, Sitaram R, Murguialday AR. Brain-Machine Interface Induced Morpho-Functional Remodeling of the Neural Motor System in Severe Chronic Stroke. Neurotherapeutics 2020; 17:635-650. [PMID: 31802435 PMCID: PMC7283440 DOI: 10.1007/s13311-019-00816-2] [Citation(s) in RCA: 4] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/16/2022] Open
Abstract
Brain-machine interfaces (BMI) permit bypass motor system disruption by coupling contingent neuroelectric signals related to motor activity with prosthetic devices that enhance afferent and proprioceptive feedback to the somatosensory cortex. In this study, we investigated neural plasticity in the motor network of severely impaired chronic stroke patients after an EEG-BMI-based treatment reinforcing sensorimotor contingency of ipsilesional motor commands. Our structural connectivity analysis revealed decreased fractional anisotropy in the splenium and body of the corpus callosum, and in the contralesional hemisphere in the posterior limb of the internal capsule, the posterior thalamic radiation, and the superior corona radiata. Functional connectivity analysis showed decreased negative interhemispheric coupling between contralesional and ipsilesional sensorimotor regions, and decreased positive intrahemispheric coupling among contralesional sensorimotor regions. These findings indicate that BMI reinforcing ipsilesional brain activity and enhancing proprioceptive function of the affected hand elicits reorganization of contralesional and ipsilesional somatosensory and motor-assemblies as well as afferent and efferent connection-related motor circuits that support the partial re-establishment of the original neurophysiology of the motor system even in severe chronic stroke.
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Affiliation(s)
- Andrea Caria
- Department of Psychology and Cognitive Sciences, University of Trento, Corso Bettini 33, 38068, Rovereto, Italy.
- Istituto di Ricovero e Cura a Carattere Scientifico, Fondazione Ospedale San Camillo, Venice, Italy.
- Institut für Medizinische Psychologie und Verhaltensneurobiologie, Universität Tübingen, Tübingen, Germany.
| | - Josué Luiz Dalboni da Rocha
- Brain and Language Laboratory, Department of Clinical Neuroscience, University of Geneva, Geneva, Switzerland
| | - Giuseppe Gallitto
- Department of Psychology and Cognitive Sciences, University of Trento, Corso Bettini 33, 38068, Rovereto, Italy
| | - Niels Birbaumer
- Institut für Medizinische Psychologie und Verhaltensneurobiologie, Universität Tübingen, Tübingen, Germany
| | - Ranganatha Sitaram
- Institute of Biological and Medical Engineering, Pontificia Universidad Católica de Chile, Santiago, Chile
- Department of Psychiatry, Section of Neuroscience, School of Medicine, Pontificia Universidad Católica de Chile, Santiago, Chile
- Laboratory for Brain-Machine Interfaces and Neuromodulation, School of Medicine, Pontificia Universidad Católica de Chile, Santiago, Chile
| | - Ander Ramos Murguialday
- Institut für Medizinische Psychologie und Verhaltensneurobiologie, Universität Tübingen, Tübingen, Germany
- Health Technologies Department, TECNALIA, San Sebastian, Spain
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Pichiorri F, Mattia D. Brain-computer interfaces in neurologic rehabilitation practice. HANDBOOK OF CLINICAL NEUROLOGY 2020; 168:101-116. [PMID: 32164846 DOI: 10.1016/b978-0-444-63934-9.00009-3] [Citation(s) in RCA: 25] [Impact Index Per Article: 6.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 12/11/2022]
Abstract
The brain-computer interfaces (BCIs) for neurologic rehabilitation are based on the assumption that by retraining the brain to specific activities, an ultimate improvement of function can be expected. In this chapter, we review the present status, key determinants, and future directions of the clinical use of BCI in neurorehabilitation. The recent advancements in noninvasive BCIs as a therapeutic tool to promote functional motor recovery by inducing neuroplasticity are described, focusing on stroke as it represents the major cause of long-term motor disability. The relevance of recent findings on BCI use in spinal cord injury beyond the control of neuroprosthetic devices to restore motor function is briefly discussed. In a dedicated section, we examine the potential role of BCI technology in the domain of cognitive function recovery by instantiating BCIs in the long history of neurofeedback and some emerging BCI paradigms to address cognitive rehabilitation are highlighted. Despite the knowledge acquired over the last decade and the growing number of studies providing evidence for clinical efficacy of BCI in motor rehabilitation, an exhaustive deployment of this technology in clinical practice is still on its way. The pipeline to translate BCI to clinical practice in neurorehabilitation is the subject of this chapter.
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Affiliation(s)
- Floriana Pichiorri
- Neuroelectrical Imaging and Brain Computer Interface Laboratory, Fondazione Santa Lucia IRCCS, Rome, Italy
| | - Donatella Mattia
- Neuroelectrical Imaging and Brain Computer Interface Laboratory, Fondazione Santa Lucia IRCCS, Rome, Italy.
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Lu RR, Zheng MX, Li J, Gao TH, Hua XY, Liu G, Huang SH, Xu JG, Wu Y. Motor imagery based brain-computer interface control of continuous passive motion for wrist extension recovery in chronic stroke patients. Neurosci Lett 2019; 718:134727. [PMID: 31887332 DOI: 10.1016/j.neulet.2019.134727] [Citation(s) in RCA: 14] [Impact Index Per Article: 2.8] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/22/2019] [Revised: 12/13/2019] [Accepted: 12/26/2019] [Indexed: 11/17/2022]
Abstract
Motor recovery of wrist and fingers is still a great challenge for chronic stroke survivors. The present study aimed to verify the efficiency of motor imagery based brain-computer interface (BCI) control of continuous passive motion (CPM) in the recovery of wrist extension due to stroke. An observational study was conducted in 26 chronic stroke patients, aged 49.0 ± 15.4 years, with upper extremity motor impairment. All patients showed no wrist extension recovery. A 24-channel highresolution electroencephalogram (EEG) system was used to acquire cortical signal while they were imagining extension of the affected wrist. Then, 20 sessions of BCI-driven CPM training were carried out for 6 weeks. Primary outcome was the increase of active range of motion (ROM) of the affected wrist from the baseline to final evaluation. Improvement of modified Barthel Index, EEG classification and motor imagery pattern of wrist extension were recorded as secondary outcomes. Twenty-one patients finally passed the EEG screening and completed all the BCI-driven CPM trainings. From baseline to the final evaluation, the increase of active ROM of the affected wrists was (24.05 ± 14.46)˚. The increase of modified Barthel Index was 3.10 ± 4.02 points. But no statistical difference was detected between the baseline and final evaluations (P > 0.05). Both EEG classification and motor imagery pattern improved. The present study demonstrated beneficial outcomes of MI-based BCI control of CPM training in motor recovery of wrist extension using motor imagery signal of brain in chronic stroke patients.
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Affiliation(s)
- Rong-Rong Lu
- Department of Rehabilitation, Huashan Hospital, Fudan University, No. 12 Middle Wulumuqi Road, Shanghai 200040, China
| | - Mou-Xiong Zheng
- Department of Traumatology and Orthopedics, Yueyang Hospital, Shanghai University of Traditional Chinese Medicine, Shanghai 200437, China
| | - Jie Li
- Department of Computer Science and Technology, Tongji University, No. 4800 Cao'an Highway, Shanghai 200092, China
| | - Tian-Hao Gao
- Department of Rehabilitation, Huashan Hospital, Fudan University, No. 12 Middle Wulumuqi Road, Shanghai 200040, China
| | - Xu-Yun Hua
- Department of Traumatology and Orthopedics, Yueyang Hospital, Shanghai University of Traditional Chinese Medicine, Shanghai 200437, China
| | - Gang Liu
- Department of Rehabilitation, Huashan Hospital, Fudan University, No. 12 Middle Wulumuqi Road, Shanghai 200040, China
| | - Song-Hua Huang
- Department of Rehabilitation, Huashan Hospital, Fudan University, No. 12 Middle Wulumuqi Road, Shanghai 200040, China
| | - Jian-Guang Xu
- School of Rehabilitation Science, Shanghai University of Traditional Chinese Medicine, Shanghai 201203, China.
| | - Yi Wu
- Department of Rehabilitation, Huashan Hospital, Fudan University, No. 12 Middle Wulumuqi Road, Shanghai 200040, China.
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