Surface EMG model for tibialis anterior muscle with experimentally based simulation parameters

Siddiqi, A, Kumar, D and Poosapadi Arjunan, S 2014, 'Surface EMG model for tibialis anterior muscle with experimentally based simulation parameters', in Dinesh K Kumar, Teodiano Freire Bastos, (ed.) Proceedings of 5th ISSNIP-IEEE Biosignals and Biorobotics Conference (2014): Biosignals and Robotics for Better and Safer Living (BRC), Salvador, Brazil, 26-28 May 2014, pp. 156-160.


Document type: Conference Paper
Collection: Conference Papers

Title Surface EMG model for tibialis anterior muscle with experimentally based simulation parameters
Author(s) Siddiqi, A
Kumar, D
Poosapadi Arjunan, S
Year 2014
Conference name 2014 ISSNIP- IEEE Biosignals and Biorobotics Conference
Conference location Salvador, Brazil
Conference dates 26-28 May 2014
Proceedings title Proceedings of 5th ISSNIP-IEEE Biosignals and Biorobotics Conference (2014): Biosignals and Robotics for Better and Safer Living (BRC)
Editor(s) Dinesh K Kumar, Teodiano Freire Bastos,
Publisher IEEE
Place of publication United States
Start page 156
End page 160
Total pages 5
Abstract An Electromyogram model for the Tibialis Anterior muscle with novel firing rate equation, recruitment threshold, and spatial localisation of muscle fibres has been designed. This model has used a parallel-fibred volume conductor equation for this pennate muscle. Surface EMG was simulated using the experimental based parameters. Eight healthy subjects performed isometric dorsiflexion at 10, 20, 30, 50, 75 and 100% maximal voluntary contractions. To validate this model, the root mean square (RMS) and median frequency (MNF) were computed for both the experimental and simulated EMG. The rate of change in normalised EMG RMS and median frequency with MVC was statistically analysed using ANOCOVA between experimental and simulated signal. The gradients were found to be similar (p> 0.05), suggesting that the parallel fibred TA muscle model is suitable for analysing changes in the EMG amplitude and median frequency with MVC.
Subjects Signal Processing
Rehabilitation Engineering
Keyword(s) Electromyography (EMG)
Model
Simulation
Tibialis Anterior
Timeinvariant
DOI - identifier 10.1109/BRC.2014.6880987
Copyright notice © 2014 IEEE
ISBN 9781479956883
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