Age related neuromuscular changes in sEMG of m. Tibialis Anterior using higher order statistics (Gaussianity and linearity test)

Siddiqi, A, Poosapadi Arjunan, S and Kumar, D 2016, 'Age related neuromuscular changes in sEMG of m. Tibialis Anterior using higher order statistics (Gaussianity and linearity test)', in Proceedings of the IEEE 38th Annual International Conference of the Engineering in Medicine and Biology Society (EMBC 2016), Orlando, Florida, United States, 16-20 August 2016, pp. 3638-3641.


Document type: Conference Paper
Collection: Conference Papers

Title Age related neuromuscular changes in sEMG of m. Tibialis Anterior using higher order statistics (Gaussianity and linearity test)
Author(s) Siddiqi, A
Poosapadi Arjunan, S
Kumar, D
Year 2016
Conference name EMBC 2016: Empowering Individual Healthcare Decisions through Technology
Conference location Orlando, Florida, United States
Conference dates 16-20 August 2016
Proceedings title Proceedings of the IEEE 38th Annual International Conference of the Engineering in Medicine and Biology Society (EMBC 2016)
Publisher IEEE
Place of publication United States
Start page 3638
End page 3641
Total pages 4
Abstract Age-associated changes in the surface electromyogram (sEMG) of Tibialis Anterior (TA) muscle can be attributable to neuromuscular alterations that precede strength loss. We have used our sEMG model of the Tibialis Anterior to interpret the age-related changes and compared with the experimental sEMG. Eighteen young (20-30 years) and 18 older (60-85 years) performed isometric dorsiflexion at 6 different percentage levels of maximum voluntary contractions (MVC), and their sEMG from the TA muscle was recorded. Six different age-related changes in the neuromuscular system were simulated using the sEMG model at the same MVCs as the experiment. The maximal power of the spectrum, Gaussianity and Linearity Test Statistics were computed from the simulated and experimental sEMG. A correlation analysis at α=0.05 was performed between the simulated and experimental age-related change in the sEMG features. The results show the loss in motor units was distinguished by the Gaussianity and Linearity test statistics; while the maximal power of the PSD distinguished between the muscular factors. The simulated condition of 40% loss of motor units with halved the number of fast fibers best correlated with the age-related change observed in the experimental sEMG higher order statistical features. The simulated aging condition found by this study corresponds with the moderate motor unit remodelling and negligible strength loss reported in literature for the cohorts aged 60-70 years.
Subjects Signal Processing
Rehabilitation Engineering
DOI - identifier 10.1109/EMBC.2016.7591516
Copyright notice © IEEE 2016
ISBN 9781457702204
ISSN 1558-4615
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