Enhancing Post-Stroke Arm Function with Combined Brain Signals and Muscle Stimulation: A Quantitative Meta-Analysis and Critical Framework for Next-Generation Rehabilitation Systems

Seventy percent of stroke survivors experience upper-limb compromised functionality, making it one of the greatest rehabilitation concerns. Thus, hybrid systems driven by motor imagery-based brain-computer interfaces (MI-BCI) and functional electrical stimulation (FES) can be clinically beneficial, yet systematic quantitative review yields significant heterogeneity in findings and methods. This meta-analysis of 21 randomized control trials (n = 886) on MI-BCI+FES shows that MI-BCI + FES is significantly more effective than control (pooled effect size standardized mean difference: 0.72, 95% CI: 0.58-0.86, p < 0.001) for conventional treatment. However, this novel integrative evaluative comparison championed by translational neuroscience reveals three glaring limitations which may impact clinical efficacy: (1) temporal overlap of movement intention and stimulation provision; (2) relative facilitation levels are limited in adjustability to promote relative neuroplasticity patterns; and (3) there are no compensatory recalibrative approaches to stimulate. These shortcomings are better understood through the lens of the NIAS model, or Neuroplasticity-Informed Adaptive Stimulation, as a single theoretical framework for cross-comparative understanding. In addition, costs associated with implementation pose a problem as an average price range of $12,000-18,000 per patient, per year, suggests that further advancements in technology are needed before MIAS becomes widely applicable across populations.