Brain–computer interfaces (BCIs) are communication and control systems centered on neural signals that incorporate both the user and the brain into a closed-loop interaction framework, and are widely regarded as a transformative paradigm in human–computer interaction. However, despite the existence of broadly accepted definitions within the research community, the rapid acceleration of BCI translation and commercialization has led to increasing ambiguity in scientific definitions, expansion of conceptual scope, and overstatement of technical capabilities. To address these issues, this paper proposed a scientifically grounded definition of BCIs and systematically analyzed their essential system components and fundamental characteristics. On this basis, the major and specific factors that constrain the capability boundaries of current and foreseeable BCI systems were examined. Furthermore, the scope of BCI was explicitly delineated by distinguishing BCIs from adjacent neurotechnologies based on their functional roles and system characteristics. This work aims to promote a more rigorous and coherent understanding of BCI definitions, scope, and capability limits within the academic community, and to provide essential theoretical foundations for responsible translation and long-term development. By clarifying conceptual boundaries and realistic expectations, it seeks to mitigate risks associated with conceptual generalization and distorted projections in both research and industrial practice, thereby fostering a more rational, robust, and sustainable ecosystem for the BCI field.
Brain-computer interfaces (BCIs) has developed rapidly in recent years, yet a systematic understanding of its inherent limitations and capability boundaries remains insufficient. This paper analyzes the constraint mechanisms through which inherent limitations shape BCI capability boundaries and discusses corresponding strategies from the perspectives of neural information generation, representation, acquisition, and utilization. The analysis indicates that the inherent limitations of BCI mainly arise from the dynamic nature of neural coding, inter-individual variability, low signal-to-noise ratios, partial observability, and paradigm dependence. As the intrinsic basis for capability boundary formation, these limitations jointly constrain the capability boundaries at the neural information, human-factors, and system levels, which are manifested as the upper performance limits of decoding accuracy, information transfer rate, complex intention decoding, user experience, as well as system stability, reliability, and safety. To address these constraints, this paper summarizes representative strategies, including information enhancement, adaptive decoding, human-machine collaboration, and system optimization. The analysis suggests that improvements in BCI performance fundamentally rely on enhancing neural information utilization and progressively expanding achievable capability boundaries under existing constraints, rather than overcoming their underlying limitations. The proposed framework provides a theoretical basis for understanding the relationship between inherent limitations and capability boundaries, and provides a reference for BCI research, technological innovation, practical applications, and scientific communication.
ObjectiveTo systematically review the efficacy and safety of lumbrokinase capsule for patients with acute ischemic stroke (AIS).MethodsPubMed, EMbase, The Cochrane Library, CNKI, VIP, CBM and WanFang Data databases were electronically searched to collect randomized controlled trials (RCTs) on lumbrokinase capsule for patients with AIS from inception to 1st December, 2019. Two reviewers independently screened literature, extracted data and assessed risk of bias of included studies, then, meta-analysis was performed by using Stata 12.0 software.ResultsA total of 33 RCTs involving 4 751 patients were included. The results of meta-analysis indicated that compared with control group, lumbrokinase capsule could improve the treatment efficiency (RR=3.51, 95%CI 2.29 to 5.39, P<0.001), enhance neurological function (SMD=?0.55, 95%CI ?0.72 to ?0.38, P<0.001) and reduce fibrinogen after treatment (SMD=?0.93, 95%CI ?1.41 to ?0.44, P<0.001). Reported adverse reactions included dizziness, nausea and gastric discomfort, and no mortality was reported.ConclusionsCurrent evidence shows that lumbrokinase capsule can improve the neurological deficit in patients with AIS. Due to limited quality and quantity of the included studies, more high quality studies are required to verify above conclusions.