Post-stroke rehabilitation training with a brain-computer interface: a clinical and neuropsychological study

Lyukmanov, Roman; Aziatskaya, G.; Мокиенко, О. А.; Varako, N.; Kovyazina, M.; Супонева, Н. А.; Черникова, Л. А.; Frolov, Alexander A.; Piradov, М. А.

doi:10.17116/jnevro201811808143

Cited by 15 publications

(8 citation statements)

References 25 publications

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“…Some BCI systems synchronize neural activity with feedback devices to create closed-loop multi-modal feedback aimed at bolstering Hebbian plasticity and thereby helping to restore lost motor functions (Wolpaw et al, 2000;Daly and Wolpaw, 2008). Numerous studies have shown that BCI therapy can trigger longlasting neurological changes and improve the motor function of the upper extremity of subacute and chronic stroke patients (Ramos-Murguialday et al, 2013Ang et al, 2014;Pichiorri et al, 2015;Cho et al, 2016;Frolov et al, 2017;Guger et al, 2017;Biasiucci et al, 2018;Cervera et al, 2018;Lyukmanov et al, 2018).…”

Section: Introductionmentioning

confidence: 99%

Brain Computer Interface Treatment for Motor Rehabilitation of Upper Extremity of Stroke Patients—A Feasibility Study

et al. 2020

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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), FMA-UE = 4.68 points, P < 0.001, reduction of the spasticity in the wrist and fingers assessed by Modified Ashworth Scale (MAS), MAS-wrist =-0.72 points (SD = 0.83), P < 0.001, MAS-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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Section: Introductionmentioning

confidence: 99%

Brain Computer Interface Treatment for Motor Rehabilitation of Upper Extremity of Stroke Patients—A Feasibility Study

et al. 2020

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“…Park et al used EEG to evaluate the cognitive engagement of 11 patients with chronic stroke while performing motor tasks and observed that active motor tasks induced greater event-related desynchronization (ERD) in the bilateral motor cortices and supplementary motor area (SMA) than did passive motor tasks [82]. In addition, Lyukmanov et al used a BCI-based system to conduct neuropsychological tests on 55 patients with motor disorders after their first stroke who were undergoing rehabilitation training.…”

Section: Assessment Of Bci For Pscimentioning

confidence: 99%

“…Due to executive dysfunction after stroke, patients may be uncoordinated and/or experience judgment errors while driving. However, BCI may remedy these problems [107]. Chung et al used brain-computer interface-controlled functional electrical stimulation (BCI-FES) rehabilitation techniques in patients with chronic hemiplegic stroke and found that the training significantly approved their ability to walk after stroke and that these differences were also significantly increased compared to patients who experienced FES rehabilitation only [89].…”

Section: 3mentioning

confidence: 99%

Poststroke Cognitive Impairment Research Progress on Application of Brain-Computer Interface

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et al. 2022

BioMed Research International

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Brain-computer interfaces (BCIs), a new type of rehabilitation technology, pick up nerve cell signals, identify and classify their activities, and convert them into computer-recognized instructions. This technique has been widely used in the rehabilitation of stroke patients in recent years and appears to promote motor function recovery after stroke. At present, the application of BCI in poststroke cognitive impairment is increasing, which is a common complication that also affects the rehabilitation process. This paper reviews the promise and potential drawbacks of using BCI to treat poststroke cognitive impairment, providing a solid theoretical basis for the application of BCI in this area.

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“…Many studies have shown that MI-BCI treatment can trigger long-term neurological changes in the upper limbs of patients with stroke and improve their motor function (Cervera et al, 2018;Lyukmanov et al, 2018;Ramos-Murguialday et al, 2019). In addition, MI combined with external mechanical assist devices can make the affected limb perform corresponding actions, which can produce corresponding event-related desynchronization/synchronization (ERD/ERS) and enhance the activity pattern of the brain (Tam et al, 2011;Yao et al, 2019;Aljalal et al, 2020).…”

Section: Introductionmentioning

confidence: 99%

Multimodal Neural Response and Effect Assessment During a BCI-Based Neurofeedback Training After Stroke

et al. 2022

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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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Post-stroke rehabilitation training with a brain-computer interface: a clinical and neuropsychological study

Cited by 15 publications

References 25 publications

Brain Computer Interface Treatment for Motor Rehabilitation of Upper Extremity of Stroke Patients—A Feasibility Study

Brain Computer Interface Treatment for Motor Rehabilitation of Upper Extremity of Stroke Patients—A Feasibility Study

Poststroke Cognitive Impairment Research Progress on Application of Brain-Computer Interface

Multimodal Neural Response and Effect Assessment During a BCI-Based Neurofeedback Training After Stroke

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