Department of Computing, University Pendidikan Sultan Idris, Tanjong Malim, Perak, Malaysia; Department of Computer Science, Computer Science and Mathematics College, Tikrit University, Tikrit.
Department of Computing, University Pendidikan Sultan Idris, Tanjong Malim, Perak, Malaysia.
Comput Methods Programs Biomed. 2018 Oct;164:221-237. doi: 10.1016/j.cmpb.2018.06.012. Epub 2018 Jun 18.
Intelligent wheelchair technology has recently been utilised to address several mobility problems. Techniques based on brain-computer interface (BCI) are currently used to develop electric wheelchairs. Using human brain control in wheelchairs for people with disability has elicited widespread attention due to its flexibility.
This study aims to determine the background of recent studies on wheelchair control based on BCI for disability and map the literature survey into a coherent taxonomy. The study intends to identify the most important aspects in this emerging field as an impetus for using BCI for disability in electric-powered wheelchair (EPW) control, which remains a challenge. The study also attempts to provide recommendations for solving other existing limitations and challenges.
We systematically searched all articles about EPW control based on BCI for disability in three popular databases: ScienceDirect, IEEE and Web of Science. These databases contain numerous articles that considerably influenced this field and cover most of the relevant theoretical and technical issues.
We selected 100 articles on the basis of our inclusion and exclusion criteria. A large set of articles (55) discussed on developing real-time wheelchair control systems based on BCI for disability signals. Another set of articles (25) focused on analysing BCI for disability signals for wheelchair control. The third set of articles (14) considered the simulation of wheelchair control based on BCI for disability signals. Four articles designed a framework for wheelchair control based on BCI for disability signals. Finally, one article reviewed concerns regarding wheelchair control based on BCI for disability signals.
Since 2007, researchers have pursued the possibility of using BCI for disability in EPW control through different approaches. Regardless of type, articles have focused on addressing limitations that impede the full efficiency of BCI for disability and recommended solutions for these limitations.
Studies on wheelchair control based on BCI for disability considerably influence society due to the large number of people with disability. Therefore, we aim to provide researchers and developers with a clear understanding of this platform and highlight the challenges and gaps in the current and future studies.
智能轮椅技术最近被用于解决多种移动问题。基于脑机接口（BCI）的技术目前用于开发电动轮椅。由于其灵活性，使用残疾人士的大脑控制来控制轮椅引起了广泛关注。
本研究旨在确定基于 BCI 的残疾人士轮椅控制的最新研究背景，并将文献综述映射到一个连贯的分类法中。本研究旨在确定这个新兴领域中最重要的方面，作为在电动轮椅（EPW）控制中使用 BCI 为残疾人士提供动力，这仍然是一个挑战。本研究还试图为解决其他现有局限性和挑战提供建议。
我们在三个流行的数据库：ScienceDirect、IEEE 和 Web of Science 中系统地搜索了所有关于基于 BCI 的残疾人士 EPW 控制的文章。这些数据库包含了许多对这个领域有重大影响的文章，涵盖了大部分相关的理论和技术问题。
我们根据纳入和排除标准选择了 100 篇文章。一组大量的文章（55 篇）讨论了基于残疾人士的 BCI 信号开发实时轮椅控制系统。另一组文章（25 篇）侧重于分析用于轮椅控制的残疾人士的 BCI 信号。第三组文章（14 篇）考虑了基于残疾人士的 BCI 信号的轮椅控制模拟。四篇文章基于残疾人士的 BCI 信号设计了轮椅控制框架。最后，一篇文章综述了基于残疾人士的 BCI 信号的轮椅控制问题。
自 2007 年以来，研究人员通过不同的方法探索了在 EPW 控制中使用残疾人士的 BCI 的可能性。无论类型如何，文章都侧重于解决阻碍残疾人士的 BCI 充分效率的限制，并为这些限制提出了解决方案。
基于 BCI 的残疾人士轮椅控制的研究对社会产生了重大影响，因为残疾人士的数量众多。因此，我们旨在为研究人员和开发人员提供对这个平台的清晰理解，并强调当前和未来研究中的挑战和差距。
