A phenomenological model of the time course of maximal voluntary isometric contraction force for optimization of complex loading schemes

• Verfasst von: Herold, Johannes [VerfasserIn]
• Verfasst von: Kirches, Christian [VerfasserIn]
• Verfasst von: Schlöder, Johannes P. [VerfasserIn]
• Titel: A phenomenological model of the time course of maximal voluntary isometric contraction force for optimization of complex loading schemes
• Verf.angabe: Johannes L. Herold, Christian Kirches, Johannes P. Schlöder
• E-Jahr: 2018
• Jahr: 04 September 2018
• Umfang: 29 S.
• Teil: volume:118
• Teil: year:2018
• Teil: number:12
• Teil: pages:2587-2605
• Teil: extent:29
• Fussnoten: First Online: 04 September 2018 ; Gesehen am 19.12.2019
• Titel Quelle: Enthalten in: European journal of applied physiology
• Ort Quelle: Berlin : Springer, 1928
• Jahr Quelle: 2018
• Band/Heft Quelle: 118(2018), 12, Seite 2587-2605
• ISSN Quelle: 1439-6327
• ISSN Quelle: 1432-1025
• DOI: doi:10.1007/s00421-018-3983-z
• Datenträger: Online-Ressource
• Sprache: eng
• Sach-SW: Mathematical model
• Sach-SW: Maximal voluntary isometric contraction force
• Sach-SW: Muscle fatigue
• Sach-SW: Optimization
• Sach-SW: Resistance training
• K10plus-PPN: 1685958230

Abstract

PurposeThe time course of maximal voluntary isometric contraction (MVIC) force is of particular interest whenever force capacities are a limiting factor, e.g., during heavy manual work or resistance training (RT) sessions. The objective of this work was to develop a mathematical model of this time course that is suitable for optimization of complex loading schemes.Materials and methodsWe compiled a literature overview of existing models and justified the need for a new model. We then constructed a phenomenological ordinary differential equation model to describe the time course of MVIC force during voluntary isometric contractions and at rest. We validated the model with a comprehensive set of published data from the elbow flexors. For this, we estimated parameters from a subset of the available data and used those estimates to predict the remaining data. Afterwards, we illustrated the benefits of our model using the calibrated model to (1) analyze fatigue and recovery patterns observed in the literature (2) compute a work-rest schedule that minimizes fatigue (3) determine an isometric RT session that maximizes training volume.ResultsWe demonstrated that our model (1) is able to describe MVIC force under complex loading schemes (2) can be used to analyze fatigue and recovery patterns observed in the literature (3) can be used to optimize complex loading schemes.ConclusionsWe developed a mathematical model of the time course of MVIC force that can be efficiently employed to optimize complex loading schemes. This enables an optimal use of MVIC force capacities.