Sensory Restoration via Brain-Computer Interfaces: A Scoping Review

arXiv:2606.15091v3 Announce Type: replace-cross Abstract: Brain-computer interfaces (BCIs) can restore sensory and motor function in individuals with severe neurological impairment, but the literature is fragmented between invasive neuroprosthetics and non-invasive electrophysiological decoders, with inconsistent terminology and metrics. This scoping review maps BCI-mediated sensory restoration along a unified 2x2 framework (invasiveness x signal direction), charts representative modalities and their trade-offs, and synthesizes a convergence roadmap for the field. Eligible sources were peer-reviewed studies, clinical trials, and authoritative reviews on BCI or neuroprosthetic systems for sensory or motor restoration, substitution, or augmentation, published in English between 1969 and 2025, restricted to high-impact venues to prioritize landmark evidence. Rather than an exhaustive database search, we charted a purposively assembled, citation-chained corpus of 31 pivotal sources for modality, signal type, invasiveness, signal direction, resolution, clinical risk, cost, and regulatory maturity. We define and distinguish restoration, substitution, and augmentation, and map the corpus onto the four quadrants of the framework. The corpus is dominated by efferent restoration (21 of 31) and invasive interfaces (22 of 31), and is concentrated after 2015 (25 of 31). Non-invasive, AI-augmented silent-speech decoding has matured rapidly since 2023, while invasive speech and motor neuroprostheses have achieved near-conversational communication rates. The unified taxonomy clarifies trade-offs between pathways and the role of foundation models in closing the gap between them. We outline a near-, medium-, and long-term roadmap toward closed-loop, bidirectional restoration, and identify gaps in metric standardization, longitudinal evidence, and cross-community collaboration as priorities for future research.

Source: arXiv cs.AI | 2026-08-20

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