Immediate and long-term effects of BCI-based rehabilitation of the upper extremity after stroke: a systematic review and meta-analysis

Zhongfei Bai, Kenneth N K Fong, Jack Jiaqi Zhang, Josephine Chan, K H Ting, Zhongfei Bai, Kenneth N K Fong, Jack Jiaqi Zhang, Josephine Chan, K H Ting

Abstract

Background: A substantial number of clinical studies have demonstrated the functional recovery induced by the use of brain-computer interface (BCI) technology in patients after stroke. The objective of this review is to evaluate the effect sizes of clinical studies investigating the use of BCIs in restoring upper extremity function after stroke and the potentiating effect of transcranial direct current stimulation (tDCS) on BCI training for motor recovery.

Methods: The databases (PubMed, Medline, EMBASE, CINAHL, CENTRAL, PsycINFO, and PEDro) were systematically searched for eligible single-group or clinical controlled studies regarding the effects of BCIs in hemiparetic upper extremity recovery after stroke. Single-group studies were qualitatively described, but only controlled-trial studies were included in the meta-analysis. The PEDro scale was used to assess the methodological quality of the controlled studies. A meta-analysis of upper extremity function was performed by pooling the standardized mean difference (SMD). Subgroup meta-analyses regarding the use of external devices in combination with the application of BCIs were also carried out. We summarized the neural mechanism of the use of BCIs on stroke.

Results: A total of 1015 records were screened. Eighteen single-group studies and 15 controlled studies were included. The studies showed that BCIs seem to be safe for patients with stroke. The single-group studies consistently showed a trend that suggested BCIs were effective in improving upper extremity function. The meta-analysis (of 12 studies) showed a medium effect size favoring BCIs for improving upper extremity function after intervention (SMD = 0.42; 95% CI = 0.18-0.66; I2 = 48%; P < 0.001; fixed-effects model), while the long-term effect (five studies) was not significant (SMD = 0.12; 95% CI = - 0.28 - 0.52; I2 = 0%; P = 0.540; fixed-effects model). A subgroup meta-analysis indicated that using functional electrical stimulation as the external device in BCI training was more effective than using other devices (P = 0.010). Using movement attempts as the trigger task in BCI training appears to be more effective than using motor imagery (P = 0.070). The use of tDCS (two studies) could not further facilitate the effects of BCI training to restore upper extremity motor function (SMD = - 0.30; 95% CI = - 0.96 - 0.36; I2 = 0%; P = 0.370; fixed-effects model).

Conclusion: The use of BCIs has significant immediate effects on the improvement of hemiparetic upper extremity function in patients after stroke, but the limited number of studies does not support its long-term effects. BCIs combined with functional electrical stimulation may be a better combination for functional recovery than other kinds of neural feedback. The mechanism for functional recovery may be attributed to the activation of the ipsilesional premotor and sensorimotor cortical network.

Keywords: Brain-computer interface; Hemiparetic upper extremity function; Motor imagery; Movement attempt; Neural mechanism; Stroke.

Conflict of interest statement

The author(s) declare no potential conflicts of interest with respect to the research, authorship, and/or publication of this article.

Figures

Fig. 1
Fig. 1
Flow chart of study selection
Fig. 2
Fig. 2
Comparison of the immediate effects of BCI interventions and control interventions on upper extremity motor function. The change in scores and standard deviations (SD) of both BCI and control groups in the 12 included studies were pooled and the overall effect of the BCIs was computed as a standard mean difference (SMD) with 95% confidence interval. The results indicated that BCI training was significantly effective at improving upper extremity function SMD = 0.42; 95% CI = 0.18–0.66; I2 = 48%; P < 0.001; fixed-effects model)
Fig. 3
Fig. 3
Meta-regression scatterplots show the relationship between the effect size (standardized mean difference) and number of sessions (a), and the cumulative training time (b). In each subplot, the straight line shows the regression line and the curves around it show the 95% confidence interval
Fig. 4
Fig. 4
A subgroup analysis for the effects of different BCI mental tasks. The 12 included studies were categorized into motor imagery-based BCIs (eight studies), movement attempt-based BCIs (two studies), and action observation-based BCIs (two studies), depending on the nature of the mental tasks. The results indicted that both movement attempt-based (SMD = 0.69; 95% CI = 0.16–1.22; I2 = 0%; P = 0.010; random-effects model) and action observation-based BCIs (SMD = 1.25; 95% CI = 0.0.05–2.45; I2 = 72%; P = 0.040; random-effects model) tended to show superior clinical effects, compared to MI-based BCIs (SMD = 0.16; 95% CI = − 0.13 – 0.45; I2 = 0%; P = 0.290; random-effects model) in regard to improving upper extremity function. However, the difference among subgroups was not significant (P = 0.070)
Fig. 5
Fig. 5
A subgroup analysis of the effects of different devices combined with BCIs. The results indicated that only BCIs triggering the stimulation of FES had a significantly large effect size on motor function recovery, compared with control interventions (SMD = 1.04; 95% CI = 0.47–1.62; I2 = 37%; P < 0.001; random-effects model), while both BCIs combined with robots (SMD = 0.04; 95% CI = − 0.30 – 0.38; I2 = 0%; P = 0.820; random-effects model) and with visual feedback (SMD = 0.46; 95% CI = − 0.03 – 0.95; I2 = 0%; P = 0.060; random-effects model) had no significant differential clinical effects with control interventions
Fig. 6
Fig. 6
A comparison of the long-term effects of BCI interventions and control interventions on upper extremity motor function. The inputted data consisted of the change in scores between baseline and follow-up. Five studies followed up with patients from between 6 weeks to six-to-12 months. Ang et al. followed up with subjects twice after the intervention, after 6 weeks and after 18 weeks [48]. Our meta-analysis indicated that BCIs did not show any significant differential effects compared with control interventions when we used the follow-up data from Ang et al.’s study at 6 weeks [48] (SMD = 0.12; 95% CI = − 0.28 – 0.52; I2 = 0%; P = 0.540; fixed-effects model)
Fig. 7
Fig. 7
The potentiating effects of tDCS on BCI training in regard to improving upper extremity function. The meta-analysis indicated that the tDCS could not further potentiate the clinical effects of BCIs in regard to improving upper extremity motor function in patients with stroke (SMD = − 0.30; 95% CI = − 0.96 – 0.36; I2 = 0%; P = 0.370; fixed-effects model)

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