COMPLEXITY-BASED ANALYSIS OF MUSCLE ACTIVATION DURING WALKING AT DIFFERENT SPEEDS

Sridevi Sriram, Karthikeyan Rajagopal, Ondrej Krejcar, Robert Frischer and Hamidreza Namazi
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Sridevi Sriram: Centre for Computational Modelling, Chennai Institute of Technology, Tamil Nadu, India
Karthikeyan Rajagopal: ��Centre for Nonlinear Systems, Chennai Institute of Technology, Tamil Nadu, India‡Department of Electronics and Communications Engineering, University Centre for Research & Development, Chandigarh University, Mohali 140413, Punjab, India
Ondrej Krejcar: �Center for Basic and Applied Research, Faculty of Informatics and Management, University of Hradec Kralove, 50003 Hradec Kralove, Czechia¶Institute of Technology and Business in Ceske Budejovice, Ceske Budejovice, Czechia∥Department of Biomedical Engineering and Measurement, Faculty of Mechanical Engineering, Technical University of Kosice, Slovakia
Robert Frischer: �Institute of Technology and Business in Ceske Budejovice, Ceske Budejovice, Czechia
Hamidreza Namazi: �Center for Basic and Applied Research, Faculty of Informatics and Management, University of Hradec Kralove, 50003 Hradec Kralove, Czechia**School of Engineering, Monash University, Selangor, Malaysia

FRACTALS (fractals), 2023, vol. 31, issue 03, 1-9

Abstract: In this research, we investigated the effect of changes in walking speed on variations of the complexity of electromyogram (EMG) signals recorded from the right and left legs of subjects. We specifically employed fractal theory and approximate entropy to analyze the changes in the complexity of EMG signals recorded from 13 subjects walked at 1.0, 1.5, 2.0, 2.5, 3.0, 3.5, and 4.0 km/h on a flat surface. The results showed that by increasing of walking speed, the complexity of EMG signals decreases. The statistical analysis also indicated the significant effect of variations in walking speed on the variations of the complexity of EMG signals. This method analysis can be applied to other physiological signals of humans (e.g. electroencephalogram (EEG) signals) to investigate the effect of walking speed on other organs’ activations (e.g. brain).

Keywords: Walking Speed; Electromyogram (EMG) Signals; Complexity; Fractal Dimension; Approximate Entropy (search for similar items in EconPapers)
Date: 2023
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DOI: 10.1142/S0218348X23500329

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