Brain–machine interfaces for rehabilitation of poststroke hemiplegia

Ushiba, Junichi; Soekadar, Surjo R.

doi:10.1016/bs.pbr.2016.04.020

Cited by 45 publications

(29 citation statements)

References 89 publications

(110 reference statements)

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“…Since then, an international effort has taken place to investigate whether repeated BCI training can lead to motor recovery. Several studies reported neurological and behavioral improvements, such as increased event‐related desynchronization (ERD) of SMR in the ipsilesional hemisphere,36, 37 changes of motor‐related functional connectivity assessed by functional magnetic resonance imaging;38 increased control of volitional electromyographic activity of the paralyzed muscles,37, 39 and learned control of the reanimated hand and arm 32, 34, 35, 36, 37, 40. These results have encouraged the use of BCI in post‐stroke motor rehabilitation, but however clinical efficacy is unknown so far.…”

Section: Introductionmentioning

confidence: 99%

Brain‐computer interfaces for post‐stroke motor rehabilitation: a meta‐analysis

Cervera

Soekadar

Ushiba

et al. 2018

Ann Clin Transl Neurol

341

267

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Brain‐computer interfaces (BCIs) can provide sensory feedback of ongoing brain oscillations, enabling stroke survivors to modulate their sensorimotor rhythms purposefully. A number of recent clinical studies indicate that repeated use of such BCIs might trigger neurological recovery and hence improvement in motor function. Here, we provide a first meta‐analysis evaluating the clinical effectiveness of BCI‐based post‐stroke motor rehabilitation. Trials were identified using MEDLINE, CENTRAL, PEDro and by inspection of references in several review articles. We selected randomized controlled trials that used BCIs for post‐stroke motor rehabilitation and provided motor impairment scores before and after the intervention. A random‐effects inverse variance method was used to calculate the summary effect size. We initially identified 524 articles and, after removing duplicates, we screened titles and abstracts of 473 articles. We found 26 articles corresponding to BCI clinical trials, of these, there were nine studies that involved a total of 235 post‐stroke survivors that fulfilled the inclusion criterion (randomized controlled trials that examined motor performance as an outcome measure) for the meta‐analysis. Motor improvements, mostly quantified by the upper limb Fugl‐Meyer Assessment (FMA‐UE), exceeded the minimal clinically important difference (MCID=5.25) in six BCI studies, while such improvement was reached only in three control groups. Overall, the BCI training was associated with a standardized mean difference of 0.79 (95% CI: 0.37 to 1.20) in FMA‐UE compared to control conditions, which is in the range of medium to large summary effect size. In addition, several studies indicated BCI‐induced functional and structural neuroplasticity at a subclinical level. This suggests that BCI technology could be an effective intervention for post‐stroke upper limb rehabilitation. However, more studies with larger sample size are required to increase the reliability of these results.

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Section: Introductionmentioning

confidence: 99%

Brain‐computer interfaces for post‐stroke motor rehabilitation: a meta‐analysis

Cervera

Soekadar

Ushiba

et al. 2018

Ann Clin Transl Neurol

341

267

View full text Add to dashboard Cite

show abstract

“… 56 A brain–computer interface (BCI) or brain–machine interface (BMI), a direct technological interface between the brain and a computer, based on the ERD and/or the ERS has recently been found to be a new tool to facilitate motor recovery after stroke. 57 Clinical reports of stroke rehabilitation using a BCI system to trigger NMES (EEG-triggered NMES) for finger function, 58 upper 59 and lower 60 limb training, and gait rehabilitation 61 have been published. Similar to the EMG-modulated NMES described earlier, an EEG-modulated NMES system has also been reported, which controls the current intensity of the NMES in a stepwise manner according to the appearance or disappearance of ERD.…”

Section: Therapeutic Electrical Stimulationmentioning

confidence: 99%

Review of devices used in neuromuscular electrical stimulation for stroke rehabilitation

Takeda¹,

Tanino

Miyasaka

2017

MDER

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Neuromuscular electrical stimulation (NMES), specifically functional electrical stimulation (FES) that compensates for voluntary motion, and therapeutic electrical stimulation (TES) aimed at muscle strengthening and recovery from paralysis are widely used in stroke rehabilitation. The electrical stimulation of muscle contraction should be synchronized with intended motion to restore paralysis. Therefore, NMES devices, which monitor electromyogram (EMG) or electroencephalogram (EEG) changes with motor intention and use them as a trigger, have been developed. Devices that modify the current intensity of NMES, based on EMG or EEG, have also been proposed. Given the diversity in devices and stimulation methods of NMES, the aim of the current review was to introduce some commercial FES and TES devices and application methods, which depend on the condition of the patient with stroke, including the degree of paralysis.

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“…Several studies reported neurological and behavioral improvements, such as increased event-related desynchronization (ERD) of SMR in the ipsilesional hemisphere, 36,37 changes of motor-related functional connectivity assessed by functional MRI; 38 increased control of volitional electromyographic (EMG) activity of the 10 paralyzed muscles, 37,39 and learned control of the reanimated hand and arm. 32,[34][35][36][37] These results have encouraged the use of BCI in post-stroke motor rehabilitation, but the clinical efficacy is unknown so far. In this article, we aim to quantify the effectiveness of BCI training in post-stroke rehabilitation through a meta-analysis on existing randomized controlled trials (RCTs) reporting changes in motor function between the beginning and the end of the intervention.…”

Section: Introductionmentioning

confidence: 99%

Brain-Computer Interfaces for Post-Stroke Motor Rehabilitation: A Meta-Analysis

Cervera

Soekadar²,

Ushiba

et al. 2017

Preprint

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GG were employees of MindMaze SA, Switzerland and NB was an employee of Wyss Center, Switzerland. JU and ML are collaborating with Panasonic Inc., Japan. 30ABSTRACT Objective: Brain-computer interfaces (BCIs) can provide sensory feedback of ongoing brain oscillations enabling stroke survivors to modulate their sensorimotor rhythms purposefully. A number of recent clinical studies indicate that repeated use of such BCIs might trigger neurological recovery and hence improvement in motor function. Here we provide a first meta-analysis evaluating the clinical effectiveness of BCI-based post-stroke motor rehabilitation. 5Methods: Trials were identified using MEDLINE, CENTRAL, PEDro and by inspection of references in several review articles. We selected randomized controlled trials that used BCIs for post-stroke motor rehabilitation and provided motor impairment scores before and after the intervention. A random-effects inverse variance method was used to calculate the summary effect size. Results:We initially identified 524 articles and, after removing duplicates, we screened titles and abstracts of 473 10 articles. We found 26 articles corresponding to BCI clinical trials, of these, there were nine studies that involved a total of 235 post-stroke survivors fulfilling the inclusion criterion (randomized controlled trials that examined motor performance as an outcome measure) for the meta-analysis. Motor improvements, mostly quantified by the upper limb Fugl-Meyer Assessment (FMA-UE), exceeded the minimal clinical important difference (MCID=5.25) in six BCI studies, while such improvement was reached only in three control groups. Overall, the BCI training was 15 associated with a standardized mean difference (SMD) of 0.79 (95% CI: 0.37 to 1.20) in FMA-UE compared to control conditions, which is in the range of medium to large summary effect size. In addition, several studies indicated BCI-induced functional and structural neuroplasticity at a sub-clinical level. Interpretation:We found a medium to large effect size of BCI therapy compared to controls. This suggests that BCI technology might be an effective intervention for post-stroke upper limb rehabilitation. However, more studies with 20 larger sample size are required to increase the reliability of these results. 44 ) were considered for the meta-analysis. 1 https://www.ncbi.nlm.nih.gov/pubmed 2

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Brain–machine interfaces for rehabilitation of poststroke hemiplegia

Cited by 45 publications

References 89 publications

Brain‐computer interfaces for post‐stroke motor rehabilitation: a meta‐analysis

Brain‐computer interfaces for post‐stroke motor rehabilitation: a meta‐analysis

Review of devices used in neuromuscular electrical stimulation for stroke rehabilitation

Brain-Computer Interfaces for Post-Stroke Motor Rehabilitation: A Meta-Analysis

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