奇纳
物理医学与康复
脑-机接口
梅德林
神经假体
结果(博弈论)
计算机科学
医学
心理学
神经科学
精神科
心理干预
政治学
法学
脑电图
数学
数理经济学
作者
Esmee Dohle,Eleanor Swanson,Luka Jovanović,Suraya Yusuf,Lucy Thompson,Hugo Layard Horsfall,William Muirhead,Luke Bashford,Jamie Brannigan
标识
DOI:10.1002/advs.202501912
摘要
Implantable brain-computer interfaces (iBCIs) decode neural signals to control external effectors, offering potential to restore function in individuals with severe motor impairments, such as loss of limb function or speech. This systematic review examines the evolution of iBCI research and key bottlenecks to clinical translation, particularly the absence of standardized, clinically meaningful outcome measures. A comprehensive search of MEDLINE, Embase, and CINAHL identifies 112 studies, nearly half (49.1%) published since 2020. Eighty unique iBCI participants were identified, providing the most up-to-date estimate of global users. Research remains concentrated in the United States (83%), with growing contributions from Europe, China, and Australia. Electrocorticography (ECoG)-based devices increasingly emerge alongside micro-electrode arrays. iBCI devices are now being used to control a broader range of effectors, including robotic prosthetics and digital technologies. Although most (69.6%) studies reported outcome measures prospectively, these primarily related to decoding (69.6%) and task performance (62.5%), with only 17.9% assessing clinical outcomes. When cassessed, clinical outcomes were highly heterogeneous due to varied approaches across target populations. iBCIs show potential to restore functional independence at scale. However, challenges remain around cross-subject generalization, scalable implantation, and outcome standardization. Novel measures should be developed collaboratively with engineers, clinicians, and individuals with lived experience of motor impairment.
科研通智能强力驱动
Strongly Powered by AbleSci AI