Neurofeedback in the Rehabilitation of Patients with Motor Disorders after Stroke

被引:3
作者
Kovyazina M.S. [1 ,2 ]
Varako N.A. [1 ,2 ]
Lyukmanov R.K. [2 ]
Asiatskaya G.A. [2 ]
Suponeva N.A. [2 ]
Trofimova A.K. [1 ]
机构
[1] Moscow State University, Moscow
[2] Research Center of Neurology, Moscow
基金
俄罗斯基础研究基金会;
关键词
brain–computer interface; exoskeleton; motor disorders; rehabilitation; stroke;
D O I
10.1134/S0362119719040042
中图分类号
学科分类号
摘要
Abstract: Traditional rehabilitation procedures do not meet all the latest requirements of ecological validity and new challenges in public health in terms of their technical characteristics. The article discusses new methods of rehabilitation in clinical practice based on modern information technologies, in particular, neurofeedback. Since motor functions are of central significance for human life, an important innovation is the use of the brain–computer interface (BCI) technology in the rehabilitation of patients after stroke. Two major directions in BCI technology development in neurorehabilitation and the efficacy of mental training are discussed. The results of pilot experiments on voluntary movement restoration using a hand exoskeleton with priming are analyzed. The efficacy of motor imagery training with and without priming is compared in groups of patients with post-stroke hand paresis using exoskeleton and the noninvasive BCI technology. Our data did not support the empirical hypothesis that special regulatory priming would influence the effectiveness of practice on motor imagery (extension of the hand). Qualitative analysis showed that priming provided prior to a mentally performed motion increased the effectiveness of technology in the rehabilitation of patients and had a nonspecific effect on the possibility of mentally performing the movement. These findings contribute to the understanding of clinical and psychological mechanisms of the rehabilitation process based on computer technologies and can help to promote the mental training technology and improve its effectiveness. © 2019, Pleiades Publishing, Inc.
引用
收藏
页码:444 / 451
页数:7
相关论文
共 53 条
  • [1] Bayona N.A., Bitensky J., Salter K., Teasell R., The role of task-specific training in rehabilitation therapies, Top. Stroke Rehabil, 12, (2005)
  • [2] Rickhag M., Wieloch T., Gido G., Comprehensive regional and temporal gene expression profiling of the rat brain during the first 24 h after experimental stroke identifies dynamic ischemia-induced gene expression patterns, and reveals a biphasic activation of genes in surviving tissue, J. Neurochem, 96, (2005)
  • [3] Liu K.P., Chan C.C., Lee T.M., Hui-Chan C.W., Mental imagery for promoting relearning for people after stroke: a randomized controlled trial, Arch. Phys. Med. Rehabil, 85, (2004)
  • [4] Birbaumer N., Ghanayim N., Hinterberger T., A spelling device for the paralyzed, Nature, 398, (1999)
  • [5] Kubler A., Nijboer F., Mellinger J., Patients with ALS can use sensorimotor rhythms to operate a brain-computer interface, Neurology, 64, (2005)
  • [6] Pfurtscheller G., Neuper C., Future prospects of ERD/ERS in the context of brain–computer interface (BCI) developments, Prog. Brain Res, 159, (2006)
  • [7] Pfurtscheller G., Muller-Putz G.R., Scherer R., Neuper C., Rehabilitation with brain-computer interface systems, Computer, 41, (2008)
  • [8] Hochberg L.R., Serruya M.D., Friehs G.M., Neuronal ensemble control of prosthetic devices by a human with tetraplegia, Nature, 442, (2006)
  • [9] Wang W., Collinger J.L., Perez M.A., Neural interface technology for rehabilitation: exploiting and promoting neuroplasticity, Phys. Med. Rehabil. Clin, 21, (2010)
  • [10] Leeb R., Tonin L., Rohm M., Towards independence: a BCI telepresence robot for people with severe motor disabilities, Proc. IEEE, 103, (2015)