A Review of Medical Applications of Brain-Computer Interface Technology

Abstract

Brain–computer interfaces (BCIs) are opening new avenues for treating neurological disorders and physical impairments, yet clinical practice continues to be split between invasive and non-invasive strategies. This work approaches BCI medical applications from three angles: a systematic review of the principal literature, a comparative case analysis contrasting invasive techniques (electrocorticography, microelectrode arrays) with non-invasive ones (electroencephalography, functional near-infrared spectroscopy), and an interdisciplinary assessment that draws together neuroscience, engineering, and ethical perspectives. The findings indicate that invasive BCIs offer strong motor and sensory restoration—for instance, robotic arm control reaching 80–100% task success rates and partial recovery of hand movement—but are limited by surgical hazards, progressive signal deterioration, and price tags above $250,000. Non-invasive BCIs are safer and have seen wider deployment in community-based neurorehabilitation (e.g., around 70% effectiveness for post-stroke upper-limb recovery); nevertheless, they struggle with inherently poor signal-to-noise ratios, a BCI illiteracy rate near 30%, and low information transfer speeds. Current trends spotlight the domestication of non-invasive systems, multimodal sensor fusion, adaptive algorithms, and attempts to clear clinical translation hurdles. Importantly, the assessment reveals mounting ethical and societal strains—neural data privacy, autonomy paradoxes, inequitable access, stigmatization, and military coercion among them. The study stresses the necessity of embedding relational autonomy and neural rights into BCI development, tying technological trajectories to governance demands in order to shape responsible paths for future neurotechnologies.