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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

  • Czech description

Classification

  • Type

    J<sub>imp</sub> - Article in a specialist periodical, which is included in the Web of Science database

  • CEP classification

  • OECD FORD branch

    30306 - Sport and fitness sciences

Result continuities

  • Project

  • 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

  • UT code for WoS article

    000685643500009

  • EID of the result in the Scopus database

    2-s2.0-85109429223