Complexity-based analysis of the correlation between stride interval variability and muscle reaction at different walking speeds

Kód výsledku v 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>

Výsledek na webu

<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>

Jazyk výsledku

angličtina

Název v původním jazyce

Complexity-based analysis of the correlation between stride interval variability and muscle reaction at different walking speeds

Popis výsledku v původním jazyce

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.

Název v anglickém jazyce

Complexity-based analysis of the correlation between stride interval variability and muscle reaction at different walking speeds

Popis výsledku anglicky

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.

Druh

J_imp - Článek v periodiku v databázi Web of Science

CEP obor

—

OECD FORD obor

30306 - Sport and fitness sciences

Projekt

—

Návaznosti

I - Institucionalni podpora na dlouhodoby koncepcni rozvoj vyzkumne organizace

Rok uplatnění

2021

Kód důvěrnosti údajů

S - Úplné a pravdivé údaje o projektu nepodléhají ochraně podle zvláštních právních předpisů

Název periodika

Biomedical Signal Processing and Control

ISSN

1746-8094

e-ISSN

1746-8108

Svazek periodika

69

Číslo periodika v rámci svazku

Aug 2021

Stát vydavatele periodika

GB - Spojené království Velké Británie a Severního Irska

Počet stran výsledku

13

Strana od-do

—

Kód UT WoS článku

000685643500009

EID výsledku v databázi Scopus

2-s2.0-85109429223