Vector Interpolation on Natural Element Method

Botelho, Diego Pereira; Maréchal, Yves; Ramdane, Brahim

doi:10.1109/tmag.2015.2496422

Cited by 4 publications

(1 citation statement)

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“…Tissue anisotropy within the FDI volume was taken into account through the implementation of a local coordinate system one of whose axes was defined to align with the muscle fiber direction. The estimated muscle fiber direction for any given point in the FDI was obtained from a natural neighbor interpolation [40] of the directions of the muscle tracks obtained from the DTI fiber tracking. In this way, for each point within the FDI, an electrical conductivity tensor was first created in terms of the local coordinate system and then mapped to the global system through a simple coordinate transformation.…”

Section: Methodsmentioning

confidence: 99%

Anatomically accurate model of EMG during index finger flexion and abduction derived from diffusion tensor imaging

2019

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This study presents a modelling framework in which information on muscle fiber direction and orientation during contraction is derived from diffusion tensor imaging (DTI) and incorporated in a computational model of the surface electromyographic (EMG) signal. The proposed model makes use of the principle of reciprocity to simultaneously calculate the electric potentials produced at the recording electrode by charges distributed along an arbitrary number of muscle fibers within the muscle, allowing for a computationally efficient evaluation of extracellular motor unit action potentials. The approach is applied to the complex architecture of the first dorsal interosseous (FDI) muscle of the hand to simulate EMG during index finger flexion and abduction. Using diffusion tensor imaging methods, the results show how muscle fiber orientation and curvature in this intrinsic hand muscle change during flexion and abduction. Incorporation of anatomically accurate muscle architecture and other hand tissue morphologies enables the model to capture variations in extracellular action potential waveform shape across the motor unit population and to predict experimentally observed differences in EMG signal features when switching from index finger abduction to flexion. The simulation results illustrate how structural and electrical properties of the tissues comprising the volume conductor, in combination with fiber direction and curvature, shape the detected action potentials. Using the model, the relative contribution of motor units of different sizes located throughout the muscle under both conditions is examined, yielding a prediction of the detection profile of the surface EMG electrode array over the muscle cross-section.

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Section: Methodsmentioning

confidence: 99%