观点
脑-机接口
计算机科学
模式
接口(物质)
透视图(图形)
忠诚
人机交互
数据科学
人工智能
神经科学
心理学
电信
脑电图
艺术
气泡
最大气泡压力法
社会学
社会科学
并行计算
视觉艺术
作者
Yike Sun,Xiaogang Chen,Bingchuan Liu,Liyan Liang,Yijun Wang,Shangkai Gao,Xiaorong Gao
标识
DOI:10.1016/j.fmre.2024.04.011
摘要
Brain-computer interface (BCI) technology represents a burgeoning interdisciplinary domain that facilitates direct communication between individuals and external devices. The efficacy of BCI systems is largely contingent upon the progress in signal acquisition methodologies. This paper endeavors to provide an exhaustive synopsis of signal acquisition technologies within the realm of BCI by scrutinizing research publications from the last ten years. Our review synthesizes insights from both clinical and engineering viewpoints, delineating a comprehensive two-dimensional framework for understanding signal acquisition in BCIs. We delineate nine discrete categories of technologies, furnishing exemplars for each and delineating the salient challenges pertinent to these modalities. This review furnishes researchers and practitioners with a broad-spectrum comprehension of the signal acquisition landscape in BCI, and deliberates on the paramount issues presently confronting the field. Prospective enhancements in BCI signal acquisition should focus on harmonizing a multitude of disciplinary perspectives. Achieving equilibrium between signal fidelity, invasiveness, biocompatibility, and other pivotal considerations is imperative. By doing so, we can propel BCI technology forward, bolstering its effectiveness, safety, and dependability, thereby contributing to an auspicious future for human-technology integration.
科研通智能强力驱动
Strongly Powered by AbleSci AI