Brain-actuated functional electrical stimulation elicits lasting arm motor recovery after stroke

Nature Communications, Journal Year: 2018, Volume and Issue: 9(1)

Published: June 14, 2018

Abstract Brain-computer interfaces (BCI) are used in stroke rehabilitation to translate brain signals into intended movements of the paralyzed limb. However, efficacy and mechanisms BCI-based therapies remain unclear. Here we show that BCI coupled functional electrical stimulation (FES) elicits significant, clinically relevant, lasting motor recovery chronic survivors more effectively than sham FES. Such is associated quantitative signatures neuroplasticity. patients exhibit a significant after intervention, which remains 6–12 months end therapy. Electroencephalography analysis pinpoints differences favor group, mainly consisting an increase connectivity between areas affected hemisphere. This significantly correlated with improvement. Results illustrate how BCI–FES therapy can drive purposeful plasticity thanks contingent activation body natural efferent afferent pathways.

Language: Английский

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BCI for stroke rehabilitation: motor and beyond

Journal of Neural Engineering, Journal Year: 2020, Volume and Issue: 17(4), P. 041001 - 041001

Published: July 2, 2020

Abstract Stroke is one of the leading causes long-term disability among adults and contributes to major socio-economic burden globally. frequently results in multifaceted impairments including motor, cognitive emotion deficits. In recent years, brain–computer interface (BCI)-based therapy has shown promising for post-stroke motor rehabilitation. spite success received by BCI-based interventions domain, non-motor are yet receive similar attention research clinical settings. Some preliminary encouraging rehabilitation using BCI seem suggest that it may also hold potential treating deficits such as impairments. Moreover, past studies have an intricate relationship between functions which might influence overall outcome. A number highlight inability current treatment protocols account implicit interplay functions. This indicates necessity explore all-inclusive plan targeting synergistic these standalone interventions. approach lead better recovery than individual isolation. this paper, we review advances use systems beyond particular, improving cognition stroke patients. Building on findings domains, next discuss possibility a holistic system affect synergistically promote restorative neuroplasticity. Such would provide all-encompassing platform, overarching outcomes transfer quality living. first works analyse cross-domain functional enabled

Language: Английский

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An exoskeleton controlled by an epidural wireless brain–machine interface in a tetraplegic patient: a proof-of-concept demonstration

The Lancet Neurology, Journal Year: 2019, Volume and Issue: 18(12), P. 1112 - 1122

Published: Oct. 3, 2019

Language: Английский

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EEG-Based Brain-Computer Interfaces (BCIs): A Survey of Recent Studies on Signal Sensing Technologies and Computational Intelligence Approaches and Their Applications

IEEE/ACM Transactions on Computational Biology and Bioinformatics, Journal Year: 2021, Volume and Issue: 18(5), P. 1645 - 1666

Published: Aug. 25, 2021

Brain-Computer interfaces (BCIs) enhance the capability of human brain activities to interact with environment. Recent advancements in technology and machine learning algorithms have increased interest electroencephalographic (EEG)-based BCI applications. EEG-based intelligent systems can facilitate continuous monitoring fluctuations cognitive states under monotonous tasks, which is both beneficial for people need healthcare support general researchers different domain areas. In this review, we survey recent literature on EEG signal sensing technologies computational intelligence approaches applications, compensating gaps systematic summary past five years. Specifically, first review current status collecting reliable signals. Then, demonstrate state-of-the-art techniques, including fuzzy models transfer deep algorithms, detect, monitor, maintain task performance prevalent Finally, present a couple innovative BCI-inspired applications discuss future research directions research.

Language: Английский

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EEG-Based BCI Control Schemes for Lower-Limb Assistive-Robots

Frontiers in Human Neuroscience, Journal Year: 2018, Volume and Issue: 12

Published: Aug. 6, 2018

Over recent years, brain-computer interface (BCI) has emerged as an alternative communication system between the human brain and output device. Deciphered intents, after detecting electrical signals from scalp, are translated into control commands used to operate external devices, computer displays virtual objects in real-time. BCI provides augmentative by creating a muscle-free channel primarily for subjects having neuromotor disorders, or trauma nervous system, notably spinal cord injuries (SCI), with unaffected sensorimotor functions but disarticulated amputated residual limbs. This review identifies potentials of electroencephalography (EEG) based applications locomotion mobility rehabilitation. Patients could benefit its advancements such as, wearable lower-limb (LL) exoskeletons, orthosis, prosthesis, wheelchairs, assistive-robot devices. The EEG employed aforementioned that also provide feasibility future development field rhythms (SMR), event-related (ERP) visual evoked (VEP). is effort progress user’s mental task related LL reliability confidence measures. As novel contribution, reviewed paradigms assistive-robots presented general framework fitting hierarchical layers. It reflects informatic interactions, user, operator, shared controller, robotic device environment. Each sub layer operator discussed detail, highlighting feature extraction, classification execution methods various systems. All applications’ key features their interaction environment EEG-based activity mode recognition, form table. suggested structure EEG-BCI controlled assistive devices within framework, generation intent-based multifunctional controllers. Despite controllers, BCI-based can seamlessly integrate user intent, practical challenges associated systems exist have been discerned, which be constructive developments field.

Language: Английский

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Review on motor imagery based BCI systems for upper limb post-stroke neurorehabilitation: From designing to application

Computers in Biology and Medicine, Journal Year: 2020, Volume and Issue: 123, P. 103843 - 103843

Published: June 7, 2020

Strokes are a growing cause of mortality and many stroke survivors suffer from motor impairment as well other types disabilities in their daily life activities. To treat these sequelae, imagery (MI) based brain-computer interface (BCI) systems have shown potential to serve an effective neurorehabilitation tool for post-stroke rehabilitation therapy. In this review, different MI-BCI strategies, including "Functional Electric Stimulation, Robotics Assistance Hybrid Virtual Reality Models," been comprehensively reported upper-limb neurorehabilitation. Each approaches presented illustrate the in-depth advantages challenges respective BCI systems. Additionally, current state-of-the-art main concerns regarding devices also discussed. Finally, recommendations future developments proposed while discussing

Language: Английский

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Assessment of the Efficacy of EEG-Based MI-BCI With Visual Feedback and EEG Correlates of Mental Fatigue for Upper-Limb Stroke Rehabilitation

IEEE Transactions on Biomedical Engineering, Journal Year: 2019, Volume and Issue: 67(3), P. 786 - 795

Published: June 5, 2019

This single-arm multisite trial investigates the efficacy of neurostyle brain exercise therapy towards enhanced recovery (nBETTER) system, an electroencephalogram (EEG)-based motor imagery brain-computer interface (MI-BCI) employing visual feedback for upper-limb stroke rehabilitation, and presence EEG correlates mental fatigue during BCI usage.A total 13 recruited patients underwent thrice-weekly nBETTER coupled with standard arm over six weeks. Upper-extremity Fugl-Meyer assessment (FMA) scores were measured at baseline (week 0), post-intervention 6), follow-ups (weeks 12 24). In total, 11/13 (mean age 55.2 years old, mean post-stroke duration 333.7 days, FMA 35.5) completed study.Significant gains relative to observed weeks 6 24. Retrospectively comparing (SAT) control group haptic knob (BCI-HK) intervention from a previous similar study, SAT had no significant gains, whereas BCI-HK 6, 12, analysis revealed positive correlations between beta power performance in frontal central regions, suggesting that may contribute poorer performance.nBETTER, EEG-based MI-BCI only feedback, helps survivors sustain short-term improvement. Analysis indicates be present.This study adds growing literature safe effective rehabilitation MI-BCI, suggests additional fatigue-monitoring role future such BCI.

Language: Английский

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Immediate and long-term effects of BCI-based rehabilitation of the upper extremity after stroke: a systematic review and meta-analysis

Journal of NeuroEngineering and Rehabilitation, Journal Year: 2020, Volume and Issue: 17(1)

Published: April 25, 2020

Abstract Background A substantial number of clinical studies have demonstrated the functional recovery induced by use brain-computer interface (BCI) technology in patients after stroke. The objective this review is to evaluate effect sizes investigating BCIs restoring upper extremity function stroke and potentiating transcranial direct current stimulation (tDCS) on BCI training for motor recovery. Methods databases (PubMed, Medline, EMBASE, CINAHL, CENTRAL, PsycINFO, PEDro) were systematically searched eligible single-group or controlled regarding effects hemiparetic Single-group qualitatively described, but only controlled-trial included meta-analysis. PEDro scale was used assess methodological quality studies. meta-analysis performed pooling standardized mean difference (SMD). Subgroup meta-analyses external devices combination with application also carried out. We summarized neural mechanism Results total 1015 records screened. Eighteen 15 included. showed that seem be safe consistently a trend suggested effective improving function. (of 12 studies) medium size favoring intervention (SMD = 0.42; 95% CI 0.18–0.66; I 2 48%; P < 0.001; fixed-effects model), while long-term (five not significant 0.12; − 0.28 – 0.52; 0%; 0.540; model). subgroup indicated using electrical as device more than other ( 0.010). Using movement attempts trigger task appears imagery 0.070). tDCS (two could further facilitate restore 0.30; 0.96 0.36; 0.370; Conclusion has immediate improvement stroke, limited does support its effects. combined may better kinds feedback. attributed activation ipsilesional premotor sensorimotor cortical network.

Language: Английский

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Brain–computer interface robotics for hand rehabilitation after stroke: a systematic review

Journal of NeuroEngineering and Rehabilitation, Journal Year: 2021, Volume and Issue: 18(1)

Published: Jan. 23, 2021

Abstract Background Hand rehabilitation is core to helping stroke survivors regain activities of daily living. Recent studies have suggested that the use electroencephalography-based brain-computer interfaces (BCI) can promote this process. Here, we report first systematic examination literature on BCI-robot systems for fine motor skills associated with hand movement and profile these from a technical clinical perspective. Methods A search January 2010–October 2019 articles using Ovid MEDLINE, Embase, PEDro, PsycINFO, IEEE Xplore Cochrane Library databases was performed. The selection criteria included BCI-hand robotic at different stages development involving tests healthy participants or people who had stroke. Data fields include those related study design, participant characteristics, specifications system, outcome measures. Results 30 were identified as eligible qualitative review among these, 11 involved testing robot chronic subacute patients. Statistically significant improvements in assessment scores relative controls observed three interventions. degree control majority limited triggering device perform grasping pinching movements imagery. Most employed combination kinaesthetic visual response via display screen, respectively, match feedback Conclusion 19 out BCI-robotic prototype pre-clinical development. We large heterogeneity reporting emphasise need develop standard protocol assessing outcomes so necessary evidence base efficiency efficacy be developed.

Language: Английский

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Physical principles of brain–computer interfaces and their applications for rehabilitation, robotics and control of human brain states

Physics Reports, Journal Year: 2021, Volume and Issue: 918, P. 1 - 133

Published: March 24, 2021

Language: Английский

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