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

J 2021

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

NAMAZI, Hamidreza

Basic information

Original name

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

Authors

NAMAZI, Hamidreza (364 Islamic Republic of Iran, guarantor, belonging to the institution)

Edition

Biomedical Signal Processing and Control, England, Elsevier, 2021, 1746-8094

Other information

Language

English

Type of outcome

Článek v odborném periodiku

Field of Study

30306 Sport and fitness sciences

Country of publisher

United Kingdom of Great Britain and Northern Ireland

Confidentiality degree

není předmětem státního či obchodního tajemství

References:

URL

Impact factor

Impact factor: 5.076

RIV identification code

RIV/00216224:14510/21:00121893

Organization unit

Faculty of Sports Studies

DOI

http://dx.doi.org/10.1016/j.bspc.2021.102956

UT WoS

000685643500009

Keywords in English

Muscle reaction; Gait variability; WalkingComplexity; Fractal theory; Sample entropy

Abstract

V originále

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.

Citovat

NAMAZI, Hamidreza. Complexity-based analysis of the correlation between stride interval variability and muscle reaction at different walking speeds. Biomedical Signal Processing and Control. England: Elsevier, 2021, vol. 69, Aug 2021, p. nestránkováno, 13 pp. ISSN 1746-8094. Available from: https://dx.doi.org/10.1016/j.bspc.2021.102956.

@article{1781198,
   author = {Namazi, Hamidreza},
   article_location = {England},
   article_number = {Aug 2021},
   doi = {http://dx.doi.org/10.1016/j.bspc.2021.102956},
   keywords = {Muscle reaction; Gait variability; WalkingComplexity; Fractal theory; Sample entropy},
   language = {eng},
   issn = {1746-8094},
   journal = {Biomedical Signal Processing and Control},
   title = {Complexity-based analysis of the correlation between stride interval variability and muscle reaction at different walking speeds},
   url = {http://www.sciencedirect.com/science/article/pii/S174680942100553X?via%3Dihub},
   volume = {69},
   year = {2021}
}

TY  - JOUR
ID  - 1781198
AU  - Namazi, Hamidreza
PY  - 2021
TI  - Complexity-based analysis of the correlation between stride interval variability and muscle reaction at different walking speeds
JF  - Biomedical Signal Processing and Control
VL  - 69
IS  - Aug 2021
SP  - nestránkováno
EP  - nestránkováno
PB  - Elsevier
SN  - 17468094
KW  - Muscle reaction
KW  - Gait variability
KW  - WalkingComplexity
KW  - Fractal theory
KW  - Sample entropy
UR  - http://www.sciencedirect.com/science/article/pii/S174680942100553X?via%3Dihub
N2  - 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.
ER  -

NAMAZI, Hamidreza. Complexity-based analysis of the correlation between stride interval variability and muscle reaction at different walking speeds. \textit{Biomedical Signal Processing and Control}. England: Elsevier, 2021, vol.~69, Aug 2021, p.~nestránkováno, 13 pp. ISSN~1746-8094. Available from: https://dx.doi.org/10.1016/j.bspc.2021.102956.

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