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解码争议:脑机接口与神经反馈的比较研究。

Decoding the Debate: A Comparative Study of Brain-Computer Interface and Neurofeedback.

机构信息

Shahid Beheshti Medical University, Tehran, Iran.

Department of aerospace engineering, Sharif University of Technology, Tehran, Iran.

出版信息

Appl Psychophysiol Biofeedback. 2024 Mar;49(1):47-53. doi: 10.1007/s10484-023-09601-6. Epub 2023 Aug 4.

Abstract

Brain-Computer Interface (BCI) and Neurofeedback (NF) both rely on the technology to capture brain activity. However, the literature lacks a clear distinction between the two, with some scholars categorizing NF as a special case of BCI while others view BCI as a natural extension of NF, or classify them as fundamentally different entities. This ambiguity hinders the flow of information and expertise among scholars and can cause confusion. To address this issue, we conducted a study comparing BCI and NF from two perspectives: the background and context within which BCI and NF developed, and their system design. We utilized Functional Flow Block Diagram (FFBD) as a system modelling approach to visualize inputs, functions, and outputs to compare BCI and NF at a conceptual level. Our analysis revealed that while NF is a subset of the biofeedback method that requires data from the brain to be extracted and processed, the device performing these tasks is a BCI system by definition. Therefore, we conclude that NF should be considered a specific application of BCI technology. By clarifying the relationship between BCI and NF, we hope to facilitate better communication and collaboration among scholars in these fields.

摘要

脑机接口(BCI)和神经反馈(NF)都依赖于捕捉大脑活动的技术。然而,文献中缺乏对这两者之间的明确区分,一些学者将 NF 归类为 BCI 的特殊情况,而另一些学者则将 BCI 视为 NF 的自然延伸,或者将它们归类为根本不同的实体。这种模糊性阻碍了学者之间信息和专业知识的交流,并可能导致混淆。为了解决这个问题,我们从两个角度对 BCI 和 NF 进行了比较研究:BCI 和 NF 发展的背景和环境,以及它们的系统设计。我们利用功能流程框图(FFBD)作为系统建模方法,以可视化输入、功能和输出,从概念层面比较 BCI 和 NF。我们的分析表明,虽然 NF 是需要提取和处理大脑数据的生物反馈方法的一个子集,但执行这些任务的设备根据定义就是 BCI 系统。因此,我们得出结论,NF 应该被视为 BCI 技术的一种特定应用。通过澄清 BCI 和 NF 之间的关系,我们希望促进这些领域的学者之间更好的沟通和合作。

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