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Transferring brain-computer interfaces beyond the laboratory: Successful application control for motor-disabled users

机译:将脑机接口转移到实验室之外:电​​机残障用户的成功应用控制

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摘要

Objectives: Brain-computer interfaces (BCIs) are no longer only used by healthy participants under controlled conditions in laboratory environments, but also by patients and end-users, controlling applications in their homes or clinics, without the BCI experts around. But are the technology and the field mature enough for this? Especially the successful operation of applications - like text entry systems or assistive mobility devices such as tele-presence robots - requires a good level of BCI control. How much training is needed to achieve such a level? Is it possible to train naieve end-users in 10 days to successfully control such applications? Materials and methods: In this work, we report our experiences of training 24 motor-disabled participants at rehabilitation clinics or at the end-users' homes, without BCI experts present. We also share the lessons that we have learned through transferring BCI technologies from the lab to the user's home or clinics. Results: The most important outcome is that 50% of the participants achieved good BCI performance and could successfully control the applications (tele-presence robot and text-entry system). In the case of the tele-presence robot the participants achieved an average performance ratio of 0.87 (max. 0.97) and for the text entry application a mean of 0.93 (max. 1.0). The lessons learned and the gathered user feedback range from pure BCI problems (technical and handling), to common communication issues among the different people involved, and issues encountered while controlling the applications. Conclusion: The points raised in this paper are very widely applicable and we anticipate that they might be faced similarly by other groups, if they move on to bringing the BCI technology to the end-user, to home environments and towards application prototype control.
机译:目标:健康的参与者不仅在实验室环境中的受控条件下使用脑机接口(BCI),而且在没有BCI专家在场的情况下,也可以由患者和最终用户使用它们在家里或诊所控制应用程序。但是技术和领域是否足够成熟呢?尤其是应用程序(例如文本输入系统或辅助移动设备,例如远程呈现机器人)的成功运行,需要良好的BCI控制水平。要达到这样的水平需要多少培训?是否可以在10天内培训天真的最终用户以成功控制此类应用程序?资料和方法:在这项工作中,我们报告了我们在没有BCI专家在场的情况下在康复诊所或最终用户家中培训24名行动不便的参与者的经验。我们还将分享通过将BCI技术从实验室转移到用户家中或诊所而获得的经验教训。结果:最重要的结果是50%的参与者达到了良好的BCI性能,并且可以成功地控制应用程序(远程呈现机器人和文本输入系统)。在远程呈现机器人的情况下,参与者的平均演奏率为0.87(最大0.97),对于文本输入应用程序,平均演奏率为0.93(最大1.0)。所汲取的教训和收集到的用户反馈,从纯BCI问题(技术和处理)到涉及的不同人员之间的常见通信问题,以及在控制应用程序时遇到的问题,不一而足。结论:本文提出的观点非常广泛地适用,并且我们预计,如果其他群体继续将BCI技术带给最终用户,家庭环境和应用程序原型控制,它们可能也会面临类似的问题。

著录项

  • 来源
    《Artificial intelligence in medicine》 |2013年第2期|121-132|共12页
  • 作者单位

    Chair in Non-Invasive Brain-Machine Interface, Center for Neuroprosthetics, Ecole Polytechnique Federate de Lausanne, Station 11, CH-1015 Lausanne, Switzerland;

    Chair in Non-Invasive Brain-Machine Interface, Center for Neuroprosthetics, Ecole Polytechnique Federate de Lausanne, Station 11, CH-1015 Lausanne, Switzerland;

    Chair in Non-Invasive Brain-Machine Interface, Center for Neuroprosthetics, Ecole Polytechnique Federate de Lausanne, Station 11, CH-1015 Lausanne, Switzerland;

    Chair in Non-Invasive Brain-Machine Interface, Center for Neuroprosthetics, Ecole Polytechnique Federate de Lausanne, Station 11, CH-1015 Lausanne, Switzerland;

    Chair in Non-Invasive Brain-Machine Interface, Center for Neuroprosthetics, Ecole Polytechnique Federate de Lausanne, Station 11, CH-1015 Lausanne, Switzerland;

    Chair in Non-Invasive Brain-Machine Interface, Center for Neuroprosthetics, Ecole Polytechnique Federate de Lausanne, Station 11, CH-1015 Lausanne, Switzerland;

    Chair in Non-Invasive Brain-Machine Interface, Center for Neuroprosthetics, Ecole Polytechnique Federate de Lausanne, Station 11, CH-1015 Lausanne, Switzerland;

    Clinique Romande de Readaptation-Suvacare, Avenue du Grand-Champsec 90, CH-1950 Sion, Switzerland;

    Chair in Non-Invasive Brain-Machine Interface, Center for Neuroprosthetics, Ecole Polytechnique Federate de Lausanne, Station 11, CH-1015 Lausanne, Switzerland;

    Chair in Non-Invasive Brain-Machine Interface, Center for Neuroprosthetics, Ecole Polytechnique Federate de Lausanne, Station 11, CH-1015 Lausanne, Switzerland;

  • 收录信息
  • 原文格式 PDF
  • 正文语种 eng
  • 中图分类
  • 关键词

    Brain-computer interface (BCI); Electroencephalogram (EEC); Motor imagery; Application control; End-user; Technology transfer;

    机译:脑机接口(BCI);脑电图(EEC);汽车影像;应用程序控制;最终用户;技术转让;
  • 入库时间 2022-08-18 03:47:26

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