Use of Electroencephalography Brain‐Computer Interface Systems as a Rehabilitative Approach for Upper Limb Function After a Stroke: A Systematic Review

Monge-Pereira, Esther; Ibanez-Pereda, J; Alguacil-Diego, Isabel M.; Serrano, J. Ignacio; Spottorno-Rubio, María P.; Molina‐Rueda, Francisco

doi:10.1016/j.pmrj.2017.04.016

Cited by 74 publications

(47 citation statements)

References 93 publications

(333 reference statements)

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“…Motor network reorganization after stroke is time-and activity-dependent (4). Hebbian plasticity describes the phenomenon of coincident activation of pre-and post-synaptic neurons, leading to a reinforcement of synaptic strength, finally resulting in increased and more reliable communication between the activated neurons (5,6). The potential relevance of this concept in behavioral change is particularly wellillustrated in the context of stroke rehabilitation (7).…”

Section: Introductionmentioning

confidence: 99%

Brain Functional Networks Study of Subacute Stroke Patients With Upper Limb Dysfunction After Comprehensive Rehabilitation Including BCI Training

Zan

et al. 2020

Front. Neurol.

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Brain computer interface (BCI)-based training is promising for the treatment of stroke patients with upper limb (UL) paralysis. However, most stroke patients receive comprehensive treatment that not only includes BCI, but also routine training. The purpose of this study was to investigate the topological alterations in brain functional networks following comprehensive treatment, including BCI training, in the subacute stage of stroke. Twenty-five hospitalized subacute stroke patients with moderate to severe UL paralysis were assigned to one of two groups: 4-week comprehensive treatment, including routine and BCI training (BCI group, BG, n = 14) and 4-week routine training without BCI support (control group, CG, n = 11). Functional UL assessments were performed before and after training, including, Fugl-Meyer Assessment-UL (FMA-UL), Action Research Arm Test (ARAT), and Wolf Motor Function Test (WMFT). Neuroimaging assessment of functional connectivity (FC) in the BG was performed by resting state functional magnetic resonance imaging. After training, as compared with baseline, all clinical assessments (FMA-UL, ARAT, and WMFT) improved significantly (p < 0.05) in both groups. Meanwhile, better functional improvements were observed in FMA-UL (p < 0.05), ARAT (p < 0.05), and WMFT (p < 0.05) in the BG. Meanwhile, FC of the BG increased across the whole brain, including the temporal, parietal, and occipital lobes and subcortical regions. More importantly, increased inter-hemispheric FC between the somatosensory association cortex and putamen was strongly positively associated with UL motor function after training. Our findings demonstrate that comprehensive rehabilitation, including BCI training, can enhance UL motor function better than routine training for subacute stroke patients. The reorganization of brain functional networks topology in subacute stroke patients allows for increased coordination between the Wu et al.Clinical and rs-fMRI Study multi-sensory and motor-related cortex and the extrapyramidal system. Future long-term, longitudinal, controlled neuroimaging studies are needed to assess the effectiveness of BCI training as an approach to promote brain plasticity during the subacute stage of stroke.

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Section: Introductionmentioning

confidence: 99%

Brain Functional Networks Study of Subacute Stroke Patients With Upper Limb Dysfunction After Comprehensive Rehabilitation Including BCI Training

Zan

et al. 2020

Front. Neurol.

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“…Brain-computer interface (BCI) systems offer a new direct communication channel between the brain and the outside world for patients with severe neuromuscular disease, such as amyotrophic lateral sclerosis or progressive muscular dystrophy, who have normal cognitive function (Carelli et al, 2017;Lazarou, Nikolopoulos, Petrantonakis, Kompatsiaris, & Tsolaki, 2018;Wolpaw, Birbaumer, McFarland, Pfurtscheller, & Vaughan, 2002). BCI systems usually translate the intentions of a user into computer commands by noninvasively recording electroencephalography (EEG) signals on the head surface (Allison, Wolpaw, & Wolpaw, 2007;Daly & Huggins, 2015;Monge-Pereira et al, 2017).…”

Section: Introductionmentioning

confidence: 99%

Happy emotion cognition of bimodal audiovisual stimuli optimizes the performance of the P300 speller

Gao

et al. 2019

Brain and Behavior

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Objective Prior studies of emotional cognition have found that emotion‐based bimodal face and voice stimuli can elicit larger event‐related potential (ERP) amplitudes and enhance neural responses compared with visual‐only emotional face stimuli. Recent studies on brain–computer interface have shown that emotional face stimuli have significantly improved the performance of the traditional P300 speller system, but its performance needs to be further improved for practical applications. Therefore, we herein propose a novel audiovisual P300 speller based on bimodal emotional cognition to further improve the performance of the P300 system. Methods The audiovisual P300 speller we proposed is based on happy emotions, with visual and auditory stimuli that consist of several pairs of smiling faces and audible chuckles (E‐AV spelling paradigm) of different ages and sexes. The control paradigm was the visual‐only emotional face P300 speller (E‐V spelling paradigm). Results We compared the ERP amplitudes, accuracy, and raw bit rate between the E‐AV and E‐V spelling paradigms. The target stimuli elicited significantly increased P300 amplitudes (p < .05) and P600 amplitudes (p < .05) in the E‐AV spelling paradigm compared with those in the E‐V paradigm. The E‐AV spelling paradigm also significantly improved the spelling accuracy and the raw bit rate compared with those in the E‐V paradigm at one superposition (p < .05) and at two superpositions (p < .05). Significance The proposed emotion‐based audiovisual spelling paradigm not only significantly improves the performance of the P300 speller, but also provides a basis for the development of various bimodal P300 speller systems, which is a step forward in the clinical application of brain–computer interfaces.

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“…Brain computer interface (BCI) systems can detect a user's intention and provide them with brain state-dependent feedback through certain feedback mechanisms using brain signals to assist with patient rehabilitation [22,23]. Recently, steady-state visual-evoked potential (SSVEP) technology has been introduced in BCI systems [24][25][26].…”

Section: Introductionmentioning

confidence: 99%

Brain Computer Interface-Based Action Observation Game Enhances Mu Suppression in Patients with Stroke

et al. 2019

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Action observation (AO), based on the mirror neuron theory, is a promising strategy to promote motor cortical activation in neurorehabilitation. Brain computer interface (BCI) can detect a user’s intention and provide them with brain state-dependent feedback to assist with patient rehabilitation. We investigated the effects of a combined BCI-AO game on power of mu band attenuation in stroke patients. Nineteen patients with subacute stroke were recruited. A BCI-AO game provided real-time feedback to participants regarding their attention to a flickering action video using steady-state visual-evoked potentials. All participants watched a video of repetitive grasping actions under two conditions: (1) BCI-AO game and (2) conventional AO, in random order. In the BCI-AO game, feedback on participants’ observation scores and observation time was provided. In conventional AO, a non-flickering video and no feedback were provided. The magnitude of mu suppression in the central motor, temporal, parietal, and occipital areas was significantly higher in the BCI-AO game than in the conventional AO. The magnitude of mu suppression was significantly higher in the BCI-AO game than in the conventional AO both in the affected and unaffected hemispheres. These results support the facilitatory effects of the BCI-AO game on mu suppression over conventional AO.

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Use of Electroencephalography Brain‐Computer Interface Systems as a Rehabilitative Approach for Upper Limb Function After a Stroke: A Systematic Review

Abstract: II.

Cited by 74 publications

References 93 publications

Brain Functional Networks Study of Subacute Stroke Patients With Upper Limb Dysfunction After Comprehensive Rehabilitation Including BCI Training

Brain Functional Networks Study of Subacute Stroke Patients With Upper Limb Dysfunction After Comprehensive Rehabilitation Including BCI Training

Happy emotion cognition of bimodal audiovisual stimuli optimizes the performance of the P300 speller

Brain Computer Interface-Based Action Observation Game Enhances Mu Suppression in Patients with Stroke

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