ArticleMedical & biological engineering & computing2017
Modifying motor unit territory placement in the Fuglevand model.
Article in Medical & biological engineering & computing, 2017. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 3 papers.
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Who cites it
3 citing papers in PubMed.
- Spatial Dependence of Log-Transformed Electromyography-Force Relation: Model-Based Sensitivity Analysis and Experimental Study of Biceps Brachii.Bioengineering (Basel, Switzerland) · 2023Article
- Model-Based Analysis of Muscle Strength and EMG-Force Relation with respect to Different Patterns of Motor Unit Loss.Neural plasticity · 2021Article
- A Comprehensive Mathematical Model of Motor Unit Pool Organization, Surface Electromyography, and Force Generation.Frontiers in physiology · 2019Article
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Authors and funding
2 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
The Fuglevand model is often used to address challenging questions in neurophysiology; however, there are elements of the neuromuscular system unaccounted for in the model. For instance, in some muscles, slow and fast motor units (MUs) tend to reside deep and superficially in the muscle, respectively, necessarily altering the development of surface electromyogram (EMG) power during activation. Thus, the objective of this study was to replace the randomized MU territory (MUT) placement algorithm in the Fuglevand model with an optimized method capable of reflecting these observations. To accomplish this, a weighting term was added to a previously developed optimization algorithm to encourage regionalized MUT placement. The weighting term consequently produced significantly different muscle fibre type content in the deep and superficial portions of the muscle. The relation between simulated EMG and muscle force was found to be significantly affected by regionalization. These changes were specifically a function of EMG power, as force was unaffected by regionalization. These findings suggest that parameterizing MUT regionalization will allow the model to produce a larger variety of EMG-force relations, as is observed physiologically, and could potentially simulate the loss of specific MU types as observed in ageing and clinical populations.
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Registered trials
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