Investigation of Characteristics of a Motor-Imagery Brain–Computer Interface with Quick-Response Tactile Feedback

被引:1
|
作者
Lukoyanov M.V. [1 ,2 ]
Gordleeva S.Y. [1 ]
Grigorev N.A. [1 ]
Savosenkov A.O. [1 ]
Lotareva Y.A. [1 ]
Pimashkin A.S. [1 ]
Kaplan A.Y. [1 ,3 ]
机构
[1] Lobachevsky State University of Nizhny Novgorod, Nizhny Novgorod
[2] Privolzhskiy Research Medical University, Nizhny Novgorod
[3] Department of Biology, Moscow State University, Moscow
基金
俄罗斯科学基金会;
关键词
brain-computer interface; electroencephalography; feedback; ideomotor training; motor imagery; rehabilitation;
D O I
10.3103/S0096392518040053
中图分类号
学科分类号
摘要
One of the approaches in rehabilitation after a stroke is mental training by representation of movement using a brain-computer interface (BCI), which allows one to control the result of every attempt of imaginary movement. BCI technology is based on online analysis of an electroencephalogram (EEG), detecting moments of imaginary movement representation (reaction of sensorimotor rhythm desynchronization) and presenting these events in the form of changing scenes on a computer screen or triggering electro-mechanical devices, which essentially is feedback. Traditionally used visual feedback is not always optimal for poststroke patients. Earlier, the effectiveness of tactile feedback, triggered only after a long-time mental representation of the movement, for several seconds or more, was studied. In this work, the efficiency of quick tactile feedback with motor-imagery-based BCI was investigated during classification of short (0.5 s) EEG segments. It was shown that quick tactile feedback is not inferior to the visual feedback and that it is possible to create BCI with tactile feedback that allows a quick reward of physiologically effective attempts of motor imagery and operates with acceptable accuracy for practical use. Furthermore, under certain conditions, tactile feedback can lead to a greater degree of sensorimotor rhythm desynchronization in subjects in comparison with the visual feedback, which can serve as a basis for constructing an effective neurointerface training system. © 2018, Allerton Press, Inc.
引用
收藏
页码:222 / 228
页数:6
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