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用于上肢和下肢康复的脑机接口系统:一项系统综述。

Brain-Computer Interfaces Systems for Upper and Lower Limb Rehabilitation: A Systematic Review.

作者信息

Camargo-Vargas Daniela, Callejas-Cuervo Mauro, Mazzoleni Stefano

机构信息

Software Research Group, Universidad Pedagógica y Tecnológica de Colombia, Tunja 150002, Colombia.

School of Computer Science, Universidad Pedagógica y Tecnológica de Colombia, Tunja 150002, Colombia.

出版信息

Sensors (Basel). 2021 Jun 24;21(13):4312. doi: 10.3390/s21134312.

Abstract

In recent years, various studies have demonstrated the potential of electroencephalographic (EEG) signals for the development of brain-computer interfaces (BCIs) in the rehabilitation of human limbs. This article is a systematic review of the state of the art and opportunities in the development of BCIs for the rehabilitation of upper and lower limbs of the human body. The systematic review was conducted in databases considering using EEG signals, interface proposals to rehabilitate upper/lower limbs using motor intention or movement assistance and utilizing virtual environments in feedback. Studies that did not specify which processing system was used were excluded. Analyses of the design processing or reviews were excluded as well. It was identified that 11 corresponded to applications to rehabilitate upper limbs, six to lower limbs, and one to both. Likewise, six combined visual/auditory feedback, two haptic/visual, and two visual/auditory/haptic. In addition, four had fully immersive virtual reality (VR), three semi-immersive VR, and 11 non-immersive VR. In summary, the studies have demonstrated that using EEG signals, and user feedback offer benefits including cost, effectiveness, better training, user motivation and there is a need to continue developing interfaces that are accessible to users, and that integrate feedback techniques.

摘要

近年来,各种研究已经证明了脑电图(EEG)信号在开发用于人类肢体康复的脑机接口(BCI)方面的潜力。本文是对用于人体上肢和下肢康复的BCI发展的现有技术水平和机遇的系统综述。该系统综述是在数据库中进行的,这些数据库考虑使用EEG信号、利用运动意图或运动辅助来康复上肢/下肢的接口建议以及在反馈中利用虚拟环境。未明确说明使用哪种处理系统的研究被排除。设计处理分析或综述也被排除。结果发现,11项研究对应于上肢康复应用,6项对应于下肢康复应用,1项对应于上下肢康复应用。同样,6项研究结合了视觉/听觉反馈,2项结合了触觉/视觉反馈,2项结合了视觉/听觉/触觉反馈。此外,4项研究采用了完全沉浸式虚拟现实(VR),3项采用了半沉浸式VR,11项采用了非沉浸式VR。总之,这些研究表明,使用EEG信号和用户反馈具有成本、有效性、更好的训练效果、用户积极性等优势,并且需要继续开发用户可使用的接口,并整合反馈技术。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/d0c9/8271710/c85ca1f665d9/sensors-21-04312-g001.jpg

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