ArticleInterface focus2015
Predicting electromyographic signals under realistic conditions using a multiscale chemo-electro-mechanical finite element model.
Article in Interface focus, 2015. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 10 papers.
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Who cites it
10 citing papers in PubMed.
- Linking cortex and contraction-Integrating models along the corticomuscular pathway.Frontiers in physiology · 2023Article
- Morphological Computation Increases From Lower- to Higher-Level of Biological Motor Control Hierarchy.Frontiers in robotics and AI · 2020Article
- Anatomically accurate model of EMG during index finger flexion and abduction derived from diffusion tensor imaging.PLoS computational biology · 2019Article
- Intramuscular Pressure of Human Tibialis Anterior Muscle ReflectsFrontiers in physiology · 2019Article
- A Comprehensive Mathematical Model of Motor Unit Pool Organization, Surface Electromyography, and Force Generation.Frontiers in physiology · 2019Article
- Enabling Detailed, Biophysics-Based Skeletal Muscle Models on HPC Systems.Frontiers in physiology · 2018Article
- The formation of extracellular potentials over the innervation zone: Are these potentials affected by changes in fibre membrane properties?Medical & biological engineering & computing · 2016Article
- Mechanisms of in vivo muscle fatigue in humans: investigating age-related fatigue resistance with a computational model.The Journal of physiology · 2016Article
- Multiscale musculoskeletal modelling, data-model fusion and electromyography-informed modelling.Interface focus · 2016Article
- The Role of Parvalbumin, Sarcoplasmatic Reticulum Calcium Pump Rate, Rates of Cross-Bridge Dynamics, and Ryanodine Receptor Calcium Current on Peripheral Muscle Fatigue: A Simulation Study.Computational and mathematical methods in medicine · 2016Article
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Authors and funding
3 authors.
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Abstract
This paper presents a novel multiscale finite element-based framework for modelling electromyographic (EMG) signals. The framework combines (i) a biophysical description of the excitation-contraction coupling at the half-sarcomere level, (ii) a model of the action potential (AP) propagation along muscle fibres, (iii) a continuum-mechanical formulation of force generation and deformation of the muscle, and (iv) a model for predicting the intramuscular and surface EMG. Owing to the biophysical description of the half-sarcomere, the model inherently accounts for physiological properties of skeletal muscle. To demonstrate this, the influence of membrane fatigue on the EMG signal during sustained contractions is investigated. During a stimulation period of 500 ms at 100 Hz, the predicted EMG amplitude decreases by 40% and the AP propagation velocity decreases by 15%. Further, the model can take into account contraction-induced deformations of the muscle. This is demonstrated by simulating fixed-length contractions of an idealized geometry and a model of the human tibialis anterior muscle (TA). The model of the TA furthermore demonstrates that the proposed finite element model is capable of simulating realistic geometries, complex fibre architectures, and can include different types of heterogeneities. In addition, the TA model accounts for a distributed innervation zone, different fibre types and appeals to motor unit discharge times that are based on a biophysical description of the α motor neurons.
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