Recovery of the motor function of the arm with the aid of a hand exoskeleton controlled by a brain–computer interface in a patient with an extensive brain lesion

详细信息    查看全文

• 作者：E. V. Biryukova ; O. G. Pavlova ; M. E. Kurganskaya ; P. D. Bobrov…
• 关键词：brain–computer interface ; neurorehabilitation ; biomechanical analysis of movement ; assessment of motor function
• 刊名：Human Physiology
• 出版年：2016
• 出版时间：January 2016
• 年：2016
• 卷：42
• 期：1
• 页码：13-23
• 全文大小：1,676 KB
• 参考文献：1.Kotov, S.V., Stakhovskaya, L.V., Isakova, E.V., et al., in Insul’t (Stroke), Stakhovskaya, L.V. Kotov, S.V., Eds., Moscow: Med. Inf. Agentstvo, 2014.
  2.Kübler, A. and Birbaumer, N., Brain-computer interfaces and communication in paralysis: Extinction of goal directed thinking in completely paralysed patients?, Clin. Neurophysiol., 2008, vol. 119, no. 11, p. 2658.CrossRef PubMed PubMedCentral
  3.Millán, J.d.R., Rupp, R., Müller-Putz, G.R., et al., Combining brain-computer interfaces and assistive technologies: State-of the-art and challenges, Front. Neurosci., 2010, no. 4, p. 161.PubMed PubMedCentral
  4.Nudo, R.J., Milliken, G.W., Jenkins, W.M., and Merzenich, M.M., Use-dependent alterations of movement representations in primary motor cortex of adult squirrel monkeys, J. Neurosci., 1996, vol. 16, no. 2, p. 785.PubMed
  5.Bach-Y-Rita, P., Theoretical and practical considerations in the restoration of function after stroke, Top Stroke Rehabil., 2001, vol. 8, no. 3, p. 1.CrossRef PubMed
  6.Taub, E., Uswatte, G., and Elbert, T., New treatments in neurorehabilitation founded on basic research, Nat. Rev. Neurosci., 2002, vol. 3, no. 3, p. 228.CrossRef PubMed
  7.Butler, A.J. and Page, S.J., Mental practice with motor imagery: Evidence for motor recovery and cortical reorganization after stroke, Arch. Phys. Med. Rehabil., 2006, vol. 87, no. 12, suppl. 2, p. S2.CrossRef PubMed PubMedCentral
  8.Sharma, N., Pomeroy, V.M., and Baron, J.C., Motor imagery: A backdoor to the motor system after stroke?, Stroke, 2006, vol. 37, no. 7, p. 1941.CrossRef PubMed
  9.Mokienko, O.A., Brain-computer interface based on motor imagery during rehabilitation of patients with focal brain lesions, Cand. Sci. (Med.) Dissertation, Moscow, 2013.
  10.Frolov, A.A., Biryukova, E.V., Bobrov, P.D., et al., Principles of neurorehabilitation based on the brain-computer interface and biologically adequate control of the exoskeleton, Hum. Physiol., 2013, vol. 39, no. 2, p. 196.CrossRef
  11.Machado, S., Araújo, F., Paes, F., et al., EEG-base brain-computer interfaces: an overview of basic concepts and clinical applications in neurorehabilitation, Rev. Neurosci., 2010, vol. 21, no. 6, p. 451.CrossRef PubMed
  12.Lotze, M., Braun, C., Birbaumer, N., et al., Motor learning elicited by voluntary drive, Brain, 2003, vol. 126, pt. 4, p. 866.CrossRef PubMed
  13.Jackson, P.L., Doyon, J., Richards, C.L., and Malouin, F., The efficacy of combined physical and mental practice in the learning of a foot-sequence task after stroke: A case report, Neurorehabil. Neural Repair, 2004, vol. 18, no. 2, p. 106.CrossRef PubMed
  14.Ang, K.K., Guan, C., Chua, K.S., et al., A large clinical study on the ability of stroke patients to use an EEG-based motor imagery brain-computer interface, Clin. EEG Neurosci., 2011, vol. 42, no. 4, p. 253.CrossRef PubMed
  15.Ang, K.K., Guan, C., Phua, K.S., et al., Brain-computer interface-based robotic and effector system for wrist and hand rehabilitation: results of a three-armed randomized controlled trial for chronic stroke, Front. Neuroeng., 2014, art. 30. doi 10.3389/fneng.2014.00030.
  16.Buch, E., Weber, C., Cohen, L.G., et al., Think to move: A neuromagnetic brain-computer interface (BCI) system for chronic stroke, Stroke, 2008, vol. 39, no. 3, p. 910.CrossRef PubMed
  17.Kotov, S.V., Turbina, L.G., Bobrov, P.D., et al., Rehabilitation of post stroke patients using a bioengineering system “brain-computer interface + exoskeleton”, Zh. Nevrol. Psikhiatr. im. S.S. Korsakova, 2014, vol. 12, pp. 66.
  18.Teo, W.P. and Chew, E., Is motor imagery brain-computer interface feasible in stroke rehabilitation?, Phys. Med. Rehabil., 2014, vol. 6, no. 8, p. 723.
  19.Fugl-Meyer, A.R., Jääko, L., Leyman, I., et al., The post stroke hemiplegic patient. A method for evaluation of physical performance, Scand. J. Rehabil. Med., 1975, vol. 7, no. 1, p. 13.PubMed
  20.Scott, S.H. and Dukelow, S.P., Potential of robots as next-generation technology for clinical assessment of neurological disorders and upper-limb therapy, J. Rehabil. Res. Dev., 2011, vol. 48, no. 4, p. 335.CrossRef PubMed
  21.Levin, M., Interjoint coordination during pointing movements is disrupted in spastic hemiparesis, Brain, 1996, vol. 119, pt. 1, p. 281.CrossRef PubMed
  22.Krebs, H.I., Hogan, N., Aisen, M.L., and Volpe, B.T., Robot-aided neurorehabilitation, IEEE Trans. Rehabil. Eng., 1998, vol. 6, no. 1, p. 75.CrossRef PubMed PubMedCentral
  23.Beer, R.F., Dewald, J.P.A., and Rymer, W.Z., Deficits in the coordination of multijoint arm movements in patients with hemiparesis: evidence for disturbed control of limb dynamics, Exp. Brain Res., 2000, vol. 131, no. 3, p. 305.CrossRef PubMed
  24.Cirstea, M.C. and Levin, M.F., Compensatory strategies for reaching in stroke, Brain, 2000, vol. 123, no. 5, p. 940.CrossRef PubMed
  25.Cirstea, M.C., Mitnitski, A.B., Feldman, A.G., and Levin, M.F., Interjoint coordination dynamics during reaching in stroke, Exp. Brain Res., 2003, vol. 151, no. 3, p. 289.CrossRef PubMed
  26.Rohrer, B., Fasoli, S., Krebs, H.I., et al., Submovements grow larger, fewer, and more blended during stroke recovery, Mot. Control, 2004, vol. 8, pp. 472.
  27.Chang, J.-J., Wu, T.-I., Wu, W.-L., and Su, F.-C., Kinematical measure for spastic reaching in children with cerebral palsy, Clin. Biomech., 2005, vol. 20, no. 4, p. 381.CrossRef
  28.Finley, M.A., Fasoli, S.E., Dipietro, L., et al., Short duration upper extremity robotic therapy in stroke patients with severe upper extremity motor impairment, J. Rehabil. Res. Dev., 2005, vol. 42, no. 5, p. 683.CrossRef PubMed
  29.Micera, S., Carpaneto, J., Posteraro, F., et al., Characterization of upper arm synergies during reaching tasks in able-bodied and hemiparetic subjects, Clin. Biomech., 2005, vol. 20, no. 9, p. 939.CrossRef
  30.Hogan, N. and Flash, T., Moving gracefully: quantitative theories of motor coordination, Trends Neurosci., 1987, vol. 10, no. 4, p. 170.CrossRef
  31.Frolov, A.A., Dufosse, M., Rizek, S., and Kaladjan, A., On the possibility of linear modeling of the human arm neuromuscular apparatus, Biol. Cybern., 2000, vol. 82, no. 6, p. 499.CrossRef PubMed
  32.Frolov, A.A., Prokopenko, R.A., Dufosse, M., and Ouezdou, F.B., Adjustment of the human arm viscoelastic properties to the direction of reaching, Biol. Cybern., 2006, vol. 94, pp. 97.CrossRef PubMed
  33.Shelton, F.N.A.P. and Reding, M.J., Effect of lesion location on upper limb motor recovery after stroke, Stroke, 2001, vol. 32, no. 1, p. 107.CrossRef PubMed
  34.Mercier, C. and Bourbonnais, D., Relative shoulder flexor and handgrip strength is related to upper limb function after stroke, Clin. Rehabil., 2004, vol. 18, no. 2, p. 215.CrossRef PubMed
  35.Paolucci, S., Bragoni, M., Coiro, P., et al., Quantification of the probability of reaching mobility independence at discharge from a rehabilitation hospital in nonwalking early ischemic stroke patients: a multivariate study, Cerebrovasc. Dis., 2008, vol. 26, no. 1, p. 16.CrossRef PubMed
  36.Bobrov, P.D., Gusek, D., Korshakov, A.V., and Frolov, A.A., Sources of brain activity that either contribute or not to EEG pattern classification corresponding to motor imagery, Neirokomp. Razrab. Primen., 2011, vol. 12, pp. 1.
  37.Bobrov, P.D., Korshakov, A.V., Roshchin, V.Yu., and Frolov, A.A., Bayesian classifier for brain-computer interface based on mental representation of movements, Zh. Vyssh. Nervn. Deyat. im. I.P. Pavlova, 2012, vol. 62, no. 1, p. 89.
  38.Bobrov, P., Frolov, A., Cantor, C., et al., Brain-computer interface based on generation of visual images, PLoS One, 2011, vol. 6, no. 6, e20674. doi 10.1371/journal.pone.0020674.CrossRef PubMed PubMedCentral
  39.Frolov, A., Húsek, D., and Bobrov, P., Comparison of four classification methods for brain computer interface, Neural Network World, 2011, vol. 21, no. 2, p. 101.CrossRef
  40.Biryukova, E.V., Roby-Brami, A., Frolov, A.A., and Mokhtari, M., Kinematics of human arm reconstructed from spatial tracking system recordings, J. Biomech., 2000, vol. 33, no. 8, p. 985.CrossRef PubMed
  41.Prokopenko, R.A., Frolov, A.A., Biryukova, E.V., and Roby-Brami, A., Assessment of the accuracy of a human arm model with seven degrees of freedom, J. Biomech., 2001, vol. 34, no. 2, p. 177.CrossRef PubMed
  42.Jaspers, E., Desloovere, K., Bruyninckx, H., et al., Review of quantitative measurements of upper limb movements in hemiplegic cerebral palsy, Gait Posture, 2009, vol. 30, no. 4, p. 395.CrossRef PubMed
  43.Michaelsen, S.M., Jacobs, S., Roby-Brami, A., and Levin, M.F., Compensation for distal impairments of grasping in adults with hemiparesis, Exp. Brain Res., 2004, vol. 157, no. 2, p. 162.CrossRef PubMed
  44.Roby-Brami, A., Feydy, A., Combeaud, M., et al., Motor compensation and recovery for reaching in stroke patients, Acta Neurol. Scand., 2003, vol. 107, no. 5, p. 369.CrossRef PubMed
  45.Neumann, N. and Birbaumer, N., Predictors of successful self control during brain-computer communication, J. Neurol., Neurosurg. Psychiatry, 2003, vol. 74, no. 8, p. 1117.CrossRef
  46.Kübler, A., Neumann, N., Wilhelm, B., et al., Predictability of brain-computer communication, J. Psychophysiol., 2004, vol. 18, pp. 121.CrossRef
  47.Kung, P.-C., Lin, C.-C.K., and Ju, M.-S., Neurorehabilitation robot-assisted assessments of synergy patterns of forearm, elbow and shoulder joints in chronic stroke patients, Clin. Biomech., 2010, vol. 25, no. 7, p. 647.CrossRef
  48.Latash, M.L. and Anson, J.G., What are normal movements in atypical populations?, J. Behav. Brain Sci., 1996, vol. 19, no. 1, p. 55.CrossRef
  49.Dipietro, L., Krebs, H.I., Fasoli, S.E., et al., Submovement changes characterize generalization of motor recovery after stroke, Cortex, 2009, vol. 45, no. 3, p. 318.CrossRef PubMed
  50.Feldman, A.G. and Levin, M.F., The origin and use of positional frames of reference in motor control., J. Behav. Brain Sci., 1995, vol. 18, no. 4, p. 723.CrossRef
  51.Sprague, S.A., Ryan, D.B., and Sellers, E.W., The effects of motivation on task performance using a braincomputer interface, Proc. 6th Int. Brain-Computer Interface Conf., 2014, art. ID:101-1.
  
• 作者单位：E. V. Biryukova (1) (2)
  O. G. Pavlova (1)
  M. E. Kurganskaya (1)
  P. D. Bobrov (1)
  L. G. Turbina (3)
  A. A. Frolov (1) (2) (4)
  V. I. Davydov (1)
  A. V. Silchenko (1) (5)
  O. A. Mokienko (6)
  
  1. Institute of Higher Nervous Activity and Neurophysiology, Russian Academy of Sciences, Moscow, Russia
  2. Pirogov National Medical Research University, Moscow, Russia
  3. Vladimirskii Regional Clinical Research Institute, Moscow, Russia
  4. Technical University of Ostrava, Ostrava, Czech Republic
  5. Moscow State University, Moscow, Russia
  6. Center of Neurology Research, Moscow, Russia
  
• 刊物类别：Biomedical and Life Sciences
• 刊物主题：Life Sciences
  Life Sciences
  Human Physiology
  Biomedicine
  Russian Library of Science
  
• 出版者：MAIK Nauka/Interperiodica distributed exclusively by Springer Science+Business Media LLC.
• ISSN：1608-3164

文摘

The dynamics of motor function recovery in a patient with an extensive brain lesion has been investigated during a course of neurorehabilitation assisted by a hand exoskeleton controlled by a brain–computer interface. Biomechanical analysis of the movements of the paretic arm recorded during the rehabilitation course was used for an unbiased assessment of motor function. Fifteen procedures involving hand exoskeleton control (one procedure per week) yielded the following results: (a) the velocity profile for targeted movements of the paretic hand became nearly bell-shaped; (b) the patient began to extend and abduct the hand, which was flexed and adducted at the beginning of the course; and (c) the patient started supinating the forearm, which was pronated at the beginning of the rehabilitation course. The first result is interpreted as improvement of the general level of control over the paretic hand, and the two other results are interpreted as a decrease in spasticity of the paretic hand.