Douibi Khalida, Le Bars Solène, Lemontey Alice, Nag Lipsa, Balp Rodrigo, Breda Gabrièle
Capgemini Engineering, Paris, France.
Ecole Strate Design, Sèvres, France.
Front Hum Neurosci. 2021 Aug 13;15:705064. doi: 10.3389/fnhum.2021.705064. eCollection 2021.
In the last few decades, Brain-Computer Interface (BCI) research has focused predominantly on clinical applications, notably to enable severely disabled people to interact with the environment. However, recent studies rely mostly on the use of non-invasive electroencephalographic (EEG) devices, suggesting that BCI might be ready to be used outside laboratories. In particular, Industry 4.0 is a rapidly evolving sector that aims to restructure traditional methods by deploying digital tools and cyber-physical systems. BCI-based solutions are attracting increasing attention in this field to support industrial performance by optimizing the cognitive load of industrial operators, facilitating human-robot interactions, and make operations in critical conditions more secure. Although these advancements seem promising, numerous aspects must be considered before developing any operational solutions. Indeed, the development of novel applications outside optimal laboratory conditions raises many challenges. In the current study, we carried out a detailed literature review to investigate the main challenges and present criteria relevant to the future deployment of BCI applications for Industry 4.0.
在过去几十年中，脑机接口（BCI）研究主要集中在临床应用上，特别是使严重残疾人士能够与环境进行交互。然而，最近的研究大多依赖于使用非侵入性脑电图（EEG）设备，这表明BCI可能已准备好在实验室之外使用。特别是，工业4.0是一个快速发展的领域，旨在通过部署数字工具和网络物理系统来重组传统方法。基于BCI的解决方案在该领域正吸引着越来越多的关注，以通过优化工业操作员的认知负荷、促进人机交互以及使关键条件下的操作更安全来支持工业绩效。尽管这些进展看起来很有前景，但在开发任何操作解决方案之前，必须考虑许多方面。事实上，在最佳实验室条件之外开发新应用会带来许多挑战。在本研究中，我们进行了详细的文献综述，以调查主要挑战并提出与工业4.0的BCI应用未来部署相关的标准。
