Measuring complexity in different muscles during sustained contraction using fractal properties of SEMG signal

Poosapadi Arjunan, S and Kumar, D 2018, 'Measuring complexity in different muscles during sustained contraction using fractal properties of SEMG signal', in 2018 40th Annual International Conference of the IEEE Engineering in Medicine and Biology Society (EMBC), Honolulu, United States, 18-21 July 2018, pp. 5656-5659.


Document type: Conference Paper
Collection: Conference Papers

Title Measuring complexity in different muscles during sustained contraction using fractal properties of SEMG signal
Author(s) Poosapadi Arjunan, S
Kumar, D
Year 2018
Conference name 40th Annual International Conference of the IEEE Engineering in Medicine and Biology Society (EMBC)
Conference location Honolulu, United States
Conference dates 18-21 July 2018
Proceedings title 2018 40th Annual International Conference of the IEEE Engineering in Medicine and Biology Society (EMBC)
Publisher IEEE
Place of publication United States
Start page 5656
End page 5659
Total pages 4
Abstract Modelling and analysis of surface Electromyogram (sEMG) signal has gained increasing attention in bio-signal processing for medical and healthcare applications. This research reports the study to examine the complexity in surface electromyogram signal measured from different muscles to identify the properties of muscles. Experiments were conducted to study the properties of the four muscle groups representing four sizes in length and complexities: Zygomaticus (facial), biceps, quadriceps and flexor digitorum superficialis (FDS). Complexity of the sEMG signal was computed using Higuchi's Fractal dimension. The relationship between FD and the muscle properties was investigated. Experimental results demonstrate that for a small variation in muscle contraction, there is very small change in the value of complexity (measured using Fractal dimension ~0.1%) and indicates that the larger and more complex muscles having a higher complexity at MVC. It is observed that the change in FD with muscle contraction is a result of changes in the properties of the particular muscle and its associated movement or change in length.
Subjects Biomedical Engineering not elsewhere classified
Signal Processing
Keyword(s) Muscle
EMG
Fractal dimension
Complexity
DOI - identifier 10.1109/EMBC.2018.8513544
Copyright notice © 2018 IEEE
ISBN 9781538636466
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