Perruchoud David, Pisotta Iolanda, Carda Stefano, Murray Micah M, Ionta Silvio
The Laboratory for Investigative Neurophysiology (The LINE), Department of Radiology and Department of Clinical Neurosciences, University Hospital Center and University of Lausanne, Lausanne, Switzerland.
J Neural Eng. 2016 Aug;13(4):041001. doi: 10.1088/1741-2560/13/4/041001. Epub 2016 May 25.
Brain-machine interfaces (BMIs) re-establish communication channels between the nervous system and an external device. The use of BMI technology has generated significant developments in rehabilitative medicine, promising new ways to restore lost sensory-motor functions. However and despite high-caliber basic research, only a few prototypes have successfully left the laboratory and are currently home-deployed.
The failure of this laboratory-to-user transfer likely relates to the absence of BMI solutions for providing naturalistic feedback about the consequences of the BMI's actions. To overcome this limitation, nowadays cutting-edge BMI advances are guided by the principle of biomimicry; i.e. the artificial reproduction of normal neural mechanisms.
Here, we focus on the importance of somatosensory feedback in BMIs devoted to reproducing movements with the goal of serving as a reference framework for future research on innovative rehabilitation procedures. First, we address the correspondence between users' needs and BMI solutions. Then, we describe the main features of invasive and non-invasive BMIs, including their degree of biomimicry and respective advantages and drawbacks. Furthermore, we explore the prevalent approaches for providing quasi-natural sensory feedback in BMI settings. Finally, we cover special situations that can promote biomimicry and we present the future directions in basic research and clinical applications.
The continued incorporation of biomimetic features into the design of BMIs will surely serve to further ameliorate the realism of BMIs, as well as tremendously improve their actuation, acceptance, and use.
脑机接口(BMI)重新建立了神经系统与外部设备之间的通信通道。BMI技术的应用在康复医学领域取得了重大进展,有望为恢复失去的感觉运动功能提供新方法。然而,尽管有高水平的基础研究,但只有少数原型成功走出实验室,目前已在家中部署。
这种从实验室到用户的转化失败可能与缺乏能提供关于BMI动作后果的自然主义反馈的BMI解决方案有关。为克服这一局限性,如今前沿的BMI进展以仿生学原理为指导;即正常神经机制的人工再现。
在此,我们聚焦于在致力于重现运动的BMI中体感反馈的重要性,旨在为未来创新性康复程序的研究提供一个参考框架。首先,我们探讨用户需求与BMI解决方案之间的对应关系。然后,我们描述侵入性和非侵入性BMI的主要特征,包括它们的仿生程度以及各自的优缺点。此外,我们探究在BMI环境中提供准自然感觉反馈的普遍方法。最后,我们涵盖可促进仿生学的特殊情况,并介绍基础研究和临床应用的未来方向。
在BMI设计中持续融入仿生特征必将有助于进一步提升BMI的逼真度,以及极大地改善其驱动性、可接受性和实用性。