Classification of Ataxic Gait
The result's identifiers
Result code in IS VaVaI
<a href="https://www.isvavai.cz/riv?ss=detail&h=RIV%2F62690094%3A18470%2F21%3A50018390" target="_blank" >RIV/62690094:18470/21:50018390 - isvavai.cz</a>
Alternative codes found
RIV/00216208:11150/21:10431624 RIV/60461373:22340/21:43922535 RIV/00179906:_____/21:10431624 RIV/68407700:21730/21:00354811
Result on the web
<a href="https://www.mdpi.com/1424-8220/21/16/5576/htm" target="_blank" >https://www.mdpi.com/1424-8220/21/16/5576/htm</a>
DOI - Digital Object Identifier
<a href="http://dx.doi.org/10.3390/s21165576" target="_blank" >10.3390/s21165576</a>
Alternative languages
Result language
angličtina
Original language name
Classification of Ataxic Gait
Original language description
Gait disorders accompany a number of neurological and musculoskeletal disorders that significantly reduce the quality of life. Motion sensors enable high-quality modelling of gait stereotypes. However, they produce large volumes of data, the evaluation of which is a challenge. In this publication, we compare different data reduction methods and classification of reduced data for use in clinical practice. The best accuracy achieved between a group of healthy individuals and patients with ataxic gait extracted from the records of 43 participants (23 ataxic, 20 healthy), forming 418 segments of straight gait pattern, is 98% by random forest classifier preprocessed by t-distributed stochastic neighbour embedding
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
<a href="/en/project/LTAIN19007" target="_blank" >LTAIN19007: Development of Advanced Computational Algorithms for evaluating post-surgery rehabilitation</a><br>
Continuities
I - Institucionalni podpora na dlouhodoby koncepcni rozvoj vyzkumne organizace
Others
Publication year
2021
Confidentiality
S - Úplné a pravdivé údaje o projektu nepodléhají ochraně podle zvláštních právních předpisů
Data specific for result type
Name of the periodical
Sensors
ISSN
1424-8220
e-ISSN
—
Volume of the periodical
21
Issue of the periodical within the volume
16
Country of publishing house
CH - SWITZERLAND
Number of pages
12
Pages from-to
"Article Number: 5576"
UT code for WoS article
000689890300001
EID of the result in the Scopus database
2-s2.0-85113162057