Effect of brain-computer interface training based on non-invasive electroencephalography using motor imagery on functional recovery after stroke - a systematic review and meta-analysis

Abstract

Background Training with brain-computer interface (BCI) technology in the rehabilitation of patients after a stroke is rapidly developing. Numerous RCT investigated the effects of BCI training (BCIT) on recovery of motor and brain function in patients after stroke. Methods A systematic literature search was performed in Medline, IEEE Xplore Digital Library, Cochrane library, and Embase in July 2018 and was repeated in March 2019. RCT or controlled clinical trials that included BCIT for improving motor and brain recovery in patients after a stroke were identified. Data were meta-analysed using the random-effects model. Standardized mean difference (SMD) with 95% confidence (95%CI) and 95% prediction interval (95%PI) were calculated. A meta-regression was performed to evaluate the effects of covariates on the pooled effect-size. Results In total, 14 studies, including 362 patients after ischemic and hemorrhagic stroke (cortical, subcortical, 121 females; mean age 53.0+/− 5.8; mean time since stroke onset 15.7+/− 18.2 months) were included. Main motor recovery outcome measure used was the Fugl-Meyer Assessment. Quantitative analysis showed that a BCI training compared to conventional therapy alone in patients after stroke was effective with an SMD of 0.39 (95%CI: 0.17 to 0.62; 95%PI of 0.13 to 0.66) for motor function recovery of the upper extremity. An SMD of 0.41 (95%CI: − 0.29 to 1.12) for motor function recovery of the lower extremity was found. BCI training enhanced brain function recovery with an SMD of 1.11 (95%CI: 0.64 to 1.59; 95%PI ranging from 0.33 to 1.89). Covariates such as training duration, impairment level of the upper extremity, and the combination of both did not show significant effects on the overall pooled estimate. Conclusion This meta-analysis showed evidence that BCI training added to conventional therapy may enhance motor functioning of the upper extremity and brain function recovery in patients after a stroke. We recommend a standardised evaluation of motor imagery ability of included patients and the assessment of brain function recovery should consider neuropsychological aspects (attention, concentration). Further influencing factors on motor recovery due to BCI technology might consider factors such as age, lesion type and location, quality of performance of motor imagery, or neuropsychological aspects. Trial Registration PROSPERO registration: CRD42018105832.

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

“…BCI can also be used to improve visuospatial abilities. Tonin et al [86] have shown that BCI can improve laterally dominant attentional visuospatial deficits. By using covert visual spatial attention-(CVSA-) BCI in three patients with left spatial neglect (SN) stroke, they found that the patients could control CVSA-BCI with accuracy rates above 50%.…”

Motor-Imagery EEG-Based BCIs in Wheelchair Movement and Control: A Systematic Literature Review

“…In addition to neuroprosthetics, the use of MI-based BCIs attracted considerable interest also as a potential neurorehabilitation technique to restore motor function after stroke [ 38 , 58 , 59 ]. Indeed, the scientific interest in the use of robotics in rehabilitation scenario is increasing considerably due to the growing number of people requiring rehabilitation following problems such as stroke and, at the same time, to the insufficient number of therapists available to deliver rehabilitation protocols to patients [ 59 ].…”

Discussion on the Rehabilitation of Stroke Hemiplegia Based on Interdisciplinary Combination of Medicine and Engineering

“…Brain-computer interface (BCI) is a direct connection path established between the human brain and external devices. This technology translates the neurophysiological signals in the brain into control signals that can operate external devices or computers to assist in performing different tasks [ 39 ]. The accuracy of the cortical signals obtained by noninvasive BCI systems is not as high as the signals from invasive BCI [ 40 ], but portability, safety, comfort, and low cost make noninvasive BCI the first choice for obtaining relevant brain electrical signals and electroencephalogram (EGG) [ 41 ].…”