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The relationship between two different mechanical cost functions and muscle oxygen consumption
M Praagman1, E K J Chadwick, F C T van der Helm
1Faculty of Human Movement Sciences, Institute for Fundamental and Clinical Human Movement Sciences, Vrije Universiteit Amsterdam, van der Boechorststraat 9, 1081 BT Amsterdam, The Netherlands. m.praagman@fbw.vu.nl
Journal of Biomechanics
|January 28, 2006
Summary
This study compared muscle stress and energy cost functions in biomechanical models. An energy-related cost function better predicted muscle energy consumption and activation patterns compared to a stress-based function.
Area of Science:
- Biomechanics
- Human Physiology
- Computational Modeling
Background:
- Inverse-dynamic models commonly use cost functions to resolve muscle load-sharing.
- Existing models often rely on mechanical measures like muscle force or stress, assuming energy minimization.
- The relationship between these mechanical cost functions and actual muscle energy consumption is not well understood.
Purpose of the Study:
- To analyze the relationship between two cost functions and experimentally measured muscle energy consumption.
- To evaluate the efficacy of a stress-based cost function versus a novel energy-related cost function in predicting muscle activation.
Main Methods:
- Four subjects performed isometric contractions involving elbow and forearm movements.
- Muscle oxygen consumption (VO2) was measured using near-infrared spectroscopy for key upper limb muscles.
- Two cost functions were implemented in an inverse-dynamic model, and their outputs were compared to VO2 data.
Main Results:
- The minimum stress cost function showed poor correspondence with VO2 for flexor muscles.
- A newly developed energy-related cost function, incorporating a linear term and muscle mass, demonstrated a significantly better correlation with experimental VO2.
- The energy-related cost function provided more realistic predictions of muscle activation.
Conclusions:
- The proposed energy-related cost function is a superior predictor of muscle energy consumption compared to stress-based functions.
- Incorporating energy-related factors improves the accuracy of inverse-dynamic models for predicting muscle activation and load sharing.