Title :
Surface EMG model for Tibialis Anterior muscle with experimentally based simulation parameters
Author :
Siddiqi, Ariba ; Kumar, Dinesh ; Arjunan, S.
Author_Institution :
Sch. of Electr. & Comput. Eng., RMIT Univ., Melbourne, VIC, Australia
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.
Keywords :
biomechanics; electromyography; mean square error methods; medical signal processing; natural fibres; physiological models; signal reconstruction; statistical analysis; ANOCOVA; EMG amplitude change analysis; MNF computation; MVC; RMS computation; electromyogram model; experimental EMG; experimentally based simulation parameters; firing rate equation; isometric dorsiflexion; maximal voluntary contractions; median frequency computation; normalised EMG RMS change rate; normalised EMG median frequency change rate; parallel fibred TA muscle model; parallel-fibred volume conductor equation; pennate muscle; recruitment threshold; root mean square computation; spatial muscle fibre localisation; statistical analysis; surface EMG model; surface EMG simulation; tibialis anterior muscle; Computational modeling; Electrodes; Electromyography; Firing; Mathematical model; Muscles; Recruitment; Electromyography (EMG); Model; Simulation; Tibialis Anterior; Timeinvariant;
Conference_Titel :
Biosignals and Biorobotics Conference (2014): Biosignals and Robotics for Better and Safer Living (BRC), 5th ISSNIP-IEEE
Conference_Location :
Salvador
Print_ISBN :
978-1-4799-5688-3
DOI :
10.1109/BRC.2014.6880987