Complexity-based analysis of the correlation between stride interval variability and muscle reaction at different walking speeds
The result's identifiers
Result code in IS VaVaI
<a href="https://www.isvavai.cz/riv?ss=detail&h=RIV%2F00216224%3A14510%2F21%3A00121893" target="_blank" >RIV/00216224:14510/21:00121893 - isvavai.cz</a>
Result on the web
<a href="http://www.sciencedirect.com/science/article/pii/S174680942100553X?via%3Dihub" target="_blank" >http://www.sciencedirect.com/science/article/pii/S174680942100553X?via%3Dihub</a>
DOI - Digital Object Identifier
<a href="http://dx.doi.org/10.1016/j.bspc.2021.102956" target="_blank" >10.1016/j.bspc.2021.102956</a>
Alternative languages
Result language
angličtina
Original language name
Complexity-based analysis of the correlation between stride interval variability and muscle reaction at different walking speeds
Original language description
In this research, for the first time, we evaluated the correlation between the variations of leg muscle reaction and gait at different walking speeds. Since leg muscle reaction in the form of Electromyogram (EMG) signals and stride interval time series (as gait variability) have complex structures, we utilized fractal theory and sample entropy to decode their alterations at different walking speeds. Twenty-two subjects walked at three different speeds (slow, comfortable, and fast) in six trials, and we analyzed the fractal dimension and sample entropy of EMG signals and stride interval time series. Based on the results, increasing the walking speed causes lower complexity in EMG signals and stride interval time series. Besides, strong correlations were found among the changes in the complexity of EMG signals and stride interval time series at different walking speeds. This method can be applied to analyze the correlation between other complex physiological signals of humans (e.g., EEG and ECG) during walking and running.
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
30306 - Sport and fitness sciences
Result continuities
Project
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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
Biomedical Signal Processing and Control
ISSN
1746-8094
e-ISSN
1746-8108
Volume of the periodical
69
Issue of the periodical within the volume
Aug 2021
Country of publishing house
GB - UNITED KINGDOM
Number of pages
13
Pages from-to
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UT code for WoS article
000685643500009
EID of the result in the Scopus database
2-s2.0-85109429223