Khan Muhammad Ahmed, Das Rig, Iversen Helle K, Puthusserypady Sadasivan
Department of Health Technology, Technical University of Denmark, 2800, Kgs. Lyngby, Denmark.
Department of Health Technology, Technical University of Denmark, 2800, Kgs. Lyngby, Denmark.
Comput Biol Med. 2020 Aug;123:103843. doi: 10.1016/j.compbiomed.2020.103843. Epub 2020 Jun 7.
Strokes are a growing cause of mortality and many stroke survivors suffer from motor impairment as well as other types of disabilities in their daily life activities. To treat these sequelae, motor imagery (MI) based brain-computer interface (BCI) systems have shown potential to serve as an effective neurorehabilitation tool for post-stroke rehabilitation therapy. In this review, different MI-BCI based strategies, including "Functional Electric Stimulation, Robotics Assistance and Hybrid Virtual Reality based Models," have been comprehensively reported for upper-limb neurorehabilitation. Each of these approaches have been presented to illustrate the in-depth advantages and challenges of the respective BCI systems. Additionally, the current state-of-the-art and main concerns regarding BCI based post-stroke neurorehabilitation devices have also been discussed. Finally, recommendations for future developments have been proposed while discussing the BCI neurorehabilitation systems.
中风是导致死亡的一个日益严重的原因,许多中风幸存者在日常生活活动中遭受运动障碍以及其他类型的残疾。为了治疗这些后遗症,基于运动想象(MI)的脑机接口(BCI)系统已显示出作为中风后康复治疗有效神经康复工具的潜力。在这篇综述中,已全面报道了不同的基于MI-BCI的策略,包括“基于功能性电刺激、机器人辅助和混合虚拟现实的模型”用于上肢神经康复。每种方法都已被呈现,以说明各自BCI系统的深入优势和挑战。此外,还讨论了基于BCI的中风后神经康复设备的当前技术水平和主要关注点。最后,在讨论BCI神经康复系统时提出了对未来发展的建议。