Principles of Motor Recovery in Post-Stroke Patients using Hand Exoskeleton Controlled by the Brain-Computer Interface Based on Motor Imagery
The result's identifiers
Result code in IS VaVaI
<a href="https://www.isvavai.cz/riv?ss=detail&h=RIV%2F67985807%3A_____%2F17%3A00472302" target="_blank" >RIV/67985807:_____/17:00472302 - isvavai.cz</a>
Result on the web
<a href="http://dx.doi.org/10.14311/NNW.2017.27.006" target="_blank" >http://dx.doi.org/10.14311/NNW.2017.27.006</a>
DOI - Digital Object Identifier
<a href="http://dx.doi.org/10.14311/NNW.2017.27.006" target="_blank" >10.14311/NNW.2017.27.006</a>
Alternative languages
Result language
angličtina
Original language name
Principles of Motor Recovery in Post-Stroke Patients using Hand Exoskeleton Controlled by the Brain-Computer Interface Based on Motor Imagery
Original language description
Motor recovery in post-stroke and post-traumatic patients using exoskeleton controlled by the brain-computer interface (BCI) is a new and promising rehabilitation procedure. Its development is a multidisciplinary research which requires, the teamwork of experts in neurology, neurophysiology, physics, mathematics, biomechanics and robotics. Some aspects of all these fields of study concerning the development of this rehabilitation procedure are described in the paper. The description includes the principles and physiological prerequisites of BCI based on motor imagery, biologically adequate principles of exoskeleton design and control and the results of clinical application.
Czech name
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Czech description
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Classification
Type
J<sub>imp</sub> - Article in a specialist periodical, which is included in the Web of Science database
CEP classification
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OECD FORD branch
10201 - Computer sciences, information science, bioinformathics (hardware development to be 2.2, social aspect to be 5.8)
Result continuities
Project
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Continuities
I - Institucionalni podpora na dlouhodoby koncepcni rozvoj vyzkumne organizace
Others
Publication year
2017
Confidentiality
S - Úplné a pravdivé údaje o projektu nepodléhají ochraně podle zvláštních právních předpisů
Data specific for result type
Name of the periodical
Neural Network World
ISSN
1210-0552
e-ISSN
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Volume of the periodical
27
Issue of the periodical within the volume
1
Country of publishing house
CZ - CZECH REPUBLIC
Number of pages
31
Pages from-to
107-137
UT code for WoS article
000396645200007
EID of the result in the Scopus database
2-s2.0-85020185489