Effect of Neurofeedback and Electromyographic-Biofeedback Therapy on Improving Hand Function in Stroke Patients

Rayegani, Seyed Mansoor; Raeissadat, Seyed Ahmad; Sedighipour, Leyla; Rezazadeh, Iman; Bahrami, Mohammad Hasan; Eliaspour, Dariush; Khosrawi, Saeid

doi:10.1310/tsr2102-137

Cited by 82 publications

(80 citation statements)

References 22 publications

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“…An improved speech and motor function were also reported by above stroke patients. Similar findings of neurological recovery were recently described by Rayegani et al [1], where patients in the neurofeedback and EMG-biofeedback groups showed hand function improvement similar to conventional occupational therapy. The most likely explanation of positive role of NFB in CVA patients may be attributed to its neuroplastic effect.…”

Section: Discussionsupporting

confidence: 89%

“…EEG biofeedback also called neurofeedback (NFB) has been shown to be a promising modality in neurorehabilitation including stroke [1][2][3][4]. Recent progress in computer technology and development of newer imaging and NFB techniques including low resolution electromagnetic tomography analysis (LORETA) as well as Z-score NFB prompted me to apply this therapy in stroke patients.…”

Section: Introductionmentioning

confidence: 99%

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Z-score LORETA Neurofeedback as a Potential Rehabilitation Modality in Patients with CVA

Koberda¹

2014

JNSK

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Section: Discussionsupporting

confidence: 89%

Section: Introductionmentioning

confidence: 99%

Z-score LORETA Neurofeedback as a Potential Rehabilitation Modality in Patients with CVA

Koberda¹

2014

JNSK

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“…The first, Rayegani et al. ( N = 20)52 reported significant improvement in Jebsen Hand Function Test53 score in six out of seven test items in the neurofeedback group and only three in the occupational therapy group. The second, Jang et al 54.…”

Section: Resultsmentioning

confidence: 96%

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

Cervera

Soekadar

Ushiba

et al. 2018

Ann Clin Transl Neurol

365

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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“…A few single-blind experiments comparing neurofeedback to control treatments such as electromyography (EMG) biofeedback [27,28] and sham EEG-nf [29,30] demonstrated greater improvements in both healthy and patient populations in the veritable EEG-nf group. In contrast, recent studies showed that EEG-nf and EMG biofeedback were comparable for chronic pain [31], stroke rehabilitation [32], and ADHD [33]. Additional studies concerning pediatric ADHD have used stimulant medication as an active control while attempting to maximize expectancy in both groups by allowing the parents of the affected children to select between medication and neurofeedback [34][35][36].…”

mentioning

confidence: 99%

Neurofeedback, Self-Regulation, and Brain Imaging: Clinical Science and Fad in the Service of Mental Disorders

Thibault

Lifshitz

Birbaumer

et al. 2015

Psychother Psychosom

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Neurofeedback draws on multiple techniques that propel both healthy and patient populations to self-regulate neural activity. Since the 1970s, numerous accounts have promoted electroencephalography-neurofeedback as a viable treatment for a host of mental disorders.Today, while the number of health care providers referring patients to neurofeedback practitioners increases steadily, substantial methodological and conceptual caveats continue to pervade empirical reports. And yet, nascent imaging technologies (e.g., real-time functional magnetic resonance imaging) and increasingly rigorous protocols are paving the road towards more effective applications and better scientific understanding of the underlying mechanisms.Here we outline common neurofeedback methods, illuminate the tenuous state of the evidence, and sketch out future directions to further unravel the potential merits of this contentious therapeutic prospect.

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Effect of Neurofeedback and Electromyographic-Biofeedback Therapy on Improving Hand Function in Stroke Patients

Abstract: Patients in the neurofeedback and EMG-biofeedback groups showed hand improvement similar to conventional OT. Further studies are suggested to assign the best protocol for neurofeedback and EMG-biofeedback therapy.

Cited by 82 publications

References 22 publications

Z-score LORETA Neurofeedback as a Potential Rehabilitation Modality in Patients with CVA

Z-score LORETA Neurofeedback as a Potential Rehabilitation Modality in Patients with CVA

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

Neurofeedback, Self-Regulation, and Brain Imaging: Clinical Science and Fad in the Service of Mental Disorders

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