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本文引用的文献

1
A Review of Brain Activity and EEG-Based Brain-Computer Interfaces for Rehabilitation Application.基于脑电图的脑机接口在康复应用中的脑活动综述。
Bioengineering (Basel). 2022 Dec 5;9(12):768. doi: 10.3390/bioengineering9120768.
2
Stop Explaining Black Box Machine Learning Models for High Stakes Decisions and Use Interpretable Models Instead.停止为高风险决策解释黑箱机器学习模型,转而使用可解释模型。
Nat Mach Intell. 2019 May;1(5):206-215. doi: 10.1038/s42256-019-0048-x. Epub 2019 May 13.
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Progress in the brain-computer interface: an interview with Bin He.脑机接口的进展:对何斌的采访
Natl Sci Rev. 2020 Feb;7(2):480-483. doi: 10.1093/nsr/nwz152. Epub 2019 Oct 12.
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Signal Generation, Acquisition, and Processing in Brain Machine Interfaces: A Unified Review.脑机接口中的信号生成、采集与处理:综合综述
Front Neurosci. 2021 Sep 13;15:728178. doi: 10.3389/fnins.2021.728178. eCollection 2021.
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Brain-Computer Interface: Advancement and Challenges.脑机接口:进展与挑战。
Sensors (Basel). 2021 Aug 26;21(17):5746. doi: 10.3390/s21175746.
6
Letter: Need and Impact of the Development of Robotic Neurosurgery in Latin America.信函:拉丁美洲机器人神经外科发展的需求与影响
Neurosurgery. 2021 May 13;88(6):E580-E581. doi: 10.1093/neuros/nyab088.
7
Summary of over Fifty Years with Brain-Computer Interfaces-A Review.脑机接口五十多年综述
Brain Sci. 2021 Jan 3;11(1):43. doi: 10.3390/brainsci11010043.
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The combination of brain-computer interfaces and artificial intelligence: applications and challenges.脑机接口与人工智能的结合:应用与挑战。
Ann Transl Med. 2020 Jun;8(11):712. doi: 10.21037/atm.2019.11.109.
9
The unreasonable effectiveness of deep learning in artificial intelligence.深度学习在人工智能中取得的不合理成效。
Proc Natl Acad Sci U S A. 2020 Dec 1;117(48):30033-30038. doi: 10.1073/pnas.1907373117. Epub 2020 Jan 28.
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Brain-Computer Interfaces in Quadriplegic Patients.四肢瘫痪患者的脑机接口
Neurosurg Clin N Am. 2019 Apr;30(2):275-281. doi: 10.1016/j.nec.2018.12.009. Epub 2019 Feb 18.

医疗保健领域脑机接口技术综述。

Review on brain-computer interface technologies in healthcare.

作者信息

Karikari Evelyn, Koshechkin Konstantin A

机构信息

Department of Public Health and Healthcare, I.M. Sechenov First Moscow State Medical University, Moscow, Russia.

The Digital Health Institute, I.M. Sechenov First Moscow State Medical University, Moscow, Russia.

出版信息

Biophys Rev. 2023 Sep 14;15(5):1351-1358. doi: 10.1007/s12551-023-01138-6. eCollection 2023 Oct.

DOI:10.1007/s12551-023-01138-6
PMID:37974976
原文链接:https://pmc.ncbi.nlm.nih.gov/articles/PMC10643750/
Abstract

Brain-computer interface (BCI) technologies have developed as a game changer, altering how humans interact with computers and opening up new avenues for understanding and utilizing the power of the human brain. The goal of this research study is to assess recent breakthroughs in BCI technologies and their future prospects. The paper starts with an outline of the fundamental concepts and principles that underpin BCI technologies. It examines the many forms of BCIs, including as invasive, partially invasive, and non-invasive interfaces, emphasizing their advantages and disadvantages. The progress of BCI hardware and signal processing techniques is investigated, with a focus on the shift from bulky and invasive systems to more portable and user-friendly options. Following that, the article delves into the important advances in BCI applications across several fields. It investigates the use of BCIs in healthcare, particularly in neurorehabilitation, assistive technology, and cognitive enhancement. BCIs' potential for boosting human capacities such as communication, motor control, and sensory perception is being thoroughly researched. Furthermore, the article investigates developing BCI applications in gaming, entertainment, and virtual reality, demonstrating how BCI technologies are growing outside medical and therapeutic settings. The study also gives light on the problems and limits that prevent BCIs from being widely adopted. Ethical concerns about privacy, data security, and informed permission are addressed, highlighting the importance of strong legislative frameworks to enable responsible and ethical usage of BCI technologies. Furthermore, the study delves into technological issues such as increasing signal resolution and precision, increasing system reliability, and enabling smooth connection with existing technology. Finally, this study paper gives an in-depth examination of the advances and future possibilities of BCI technologies. It emphasizes the transformative influence of BCIs on human-computer interaction and their potential to alter healthcare, gaming, and other industries. This research intends to stimulate further innovation and progress in the field of brain-computer interfaces by addressing problems and imagining future possibilities.

摘要

脑机接口(BCI)技术已经成为一种变革性技术,改变了人类与计算机交互的方式,并为理解和利用人类大脑的力量开辟了新途径。本研究的目的是评估BCI技术的最新突破及其未来前景。本文首先概述了支撑BCI技术的基本概念和原理。它研究了多种形式的脑机接口,包括侵入性、部分侵入性和非侵入性接口,强调了它们的优缺点。研究了BCI硬件和信号处理技术的进展,重点是从笨重的侵入性系统向更便携、用户友好的选项转变。在此之后,文章深入探讨了BCI在多个领域的重要进展。它研究了BCI在医疗保健中的应用,特别是在神经康复、辅助技术和认知增强方面。正在深入研究BCI在提高人类沟通、运动控制和感官感知等能力方面的潜力。此外,文章还研究了BCI在游戏、娱乐和虚拟现实中的应用发展,展示了BCI技术如何在医疗和治疗环境之外不断发展。该研究还揭示了阻碍BCI广泛应用的问题和限制。讨论了关于隐私、数据安全和知情同意的伦理问题,强调了强大的立法框架对于负责任和符合伦理地使用BCI技术的重要性。此外,该研究还深入探讨了技术问题,如提高信号分辨率和精度、提高系统可靠性以及实现与现有技术的顺畅连接。最后,本研究论文对BCI技术的进展和未来可能性进行了深入研究。它强调了脑机接口对人机交互的变革性影响及其改变医疗保健、游戏和其他行业的潜力。本研究旨在通过解决问题和设想未来可能性,激发脑机接口领域的进一步创新和进步。