Brain-computer interfaces in neurological rehabilitation

被引:734
作者
Daly, Janis J. [1 ,2 ]
Wolpaw, Jonathan R. [3 ]
机构
[1] Louis Stokes Cleveland VA Med Ctr, Cognit & Motor Learning Lab, Res Serv 151 W, Cleveland, OH 44106 USA
[2] Case Western Reserve Univ, Sch Med, Dept Neurol, Cleveland, OH 44106 USA
[3] New York State Dept Hlth, Wadsworth Ctr, Lab Nervous Syst Disorders, Albany, NY USA
关键词
D O I
10.1016/S1474-4422(08)70223-0
中图分类号
R74 [神经病学与精神病学];
学科分类号
摘要
Recent advances in analysis of brain signals, training patients to control these signals, and improved computing capabilities have enabled people with severe motor disabilities to use their brain signals for communication and control of objects in their environment, thereby bypassing their impaired neuromuscular system. Non-invasive, electroencephalogram (EEG)-based brain-computer interface (BCI) technologies can be used to control a computer cursor or a limb orthosis, for word processing and accessing the internet, and for other functions such as environmental control or entertainment. By re-establishing some independence, BCI technologies can substantially improve the lives of people with devastating neurological disorders such as advanced amyotrophic lateral sclerosis. BCI technology might also restore more effective motor control to people after stroke or other traumatic brain disorders by helping to guide activity-dependent brain plasticity by use of EEG brain signals to indicate to the patient the current state of brain activity and to enable the user to subsequently lower abnormal activity. Alternatively, by use of brain signals to supplement impaired muscle control, BCIs might increase the efficacy of a rehabilitation protocol and thus improve muscle control for the patient.
引用
收藏
页码:1032 / 1043
页数:12
相关论文
共 111 条
  • [51] Brain-computer communication:: Self-regulation of slow cortical potentials for verbal communication
    Kübler, A
    Neumann, N
    Kaiser, J
    Kotchoubey, B
    Hinterberger, T
    Birbaumer, NP
    [J]. ARCHIVES OF PHYSICAL MEDICINE AND REHABILITATION, 2001, 82 (11): : 1533 - 1539
  • [52] Leeb Robert, 2007, Comput Intell Neurosci, P79642, DOI 10.1155/2007/79642
  • [53] An adaptive P300-based online brain-computer interface
    Lenhardt, Alexander
    Kaper, Matthias
    Ritter, Helge J.
    [J]. IEEE TRANSACTIONS ON NEURAL SYSTEMS AND REHABILITATION ENGINEERING, 2008, 16 (02) : 121 - 130
  • [54] A brain-computer interface using electrocorticographic signals in humans
    Leuthardt, Eric C.
    Schalk, Gerwin
    Wolpaw, Jonathan R.
    Ojemann, Jeffrey G.
    Moran, Daniel W.
    [J]. JOURNAL OF NEURAL ENGINEERING, 2004, 1 (02) : 63 - 71
  • [55] Growth-associated gene and protein expression in the region of axonal sprouting in the aged brain after stroke
    Li, Songlin
    Carmichael, S. Thomas
    [J]. NEUROBIOLOGY OF DISEASE, 2006, 23 (02) : 362 - 373
  • [56] Motor cortex plasticity during forced-use therapy in stroke patients:: a preliminary study
    Liepert, J
    Uhde, I
    Gräf, S
    Leidner, O
    Weiller, C
    [J]. JOURNAL OF NEUROLOGY, 2001, 248 (04) : 315 - 321
  • [57] Maillot F, 2001, NEUROLOGY, V57, P1939, DOI 10.1212/WNL.57.10.1939
  • [58] Evolution of cortical activation during recovery from corticospinal tract infarction
    Marshall, RS
    Perera, GM
    Lazar, RM
    Krakauer, JW
    Constantine, RC
    DeLaPaz, RL
    [J]. STROKE, 2000, 31 (03) : 656 - 661
  • [59] MCFARLAND DJ, 2008, ELECTROENCEPHALOGRAP
  • [60] Electroencephalographic biofeedback in the treatment of attention-deficit/hyperactivity disorder
    Monastra, VJ
    Lynn, S
    Linden, M
    Lubar, JF
    Gruzelier, J
    LaVaque, TJ
    [J]. APPLIED PSYCHOPHYSIOLOGY AND BIOFEEDBACK, 2005, 30 (02) : 95 - 114