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Damping and energy dissipation in soft tissue vibrations during running
Arash Khassetarash1, Reza Hassannejad1, Hendrik Enders2
1Department of Mechanical Engineering, University of Tabriz 51666-14766, Tabriz, Iran.
Soft tissue vibrations are complex, involving multiple modes. This study used partly ensemble empirical mode decomposition (PEEMD) to analyze gastrocnemius muscle vibrations during sprinting, revealing distinct damping properties for different vibration modes.
Area of Science:
- Biomechanics
- Biomedical Engineering
- Muscle Physiology
Background:
- Soft tissue vibrations are complex and cannot be represented by a single sinusoidal function.
- These vibrations comprise multiple distinct modes, each potentially having unique characteristics.
- Understanding these modes is crucial for analyzing muscle dynamics during movement.
Purpose of the Study:
- To extract and analyze individual vibration modes in soft tissues.
- To quantify damping properties and energy dissipation for each identified vibration mode.
- To investigate the implications of these findings for understanding muscle tuning during locomotion.
Main Methods:
- Partly Ensemble Empirical Mode Decomposition (PEEMD) was employed to extract vibration modes from acceleration signals.
- A novel methodology was developed and validated for estimating damping properties and energy dissipation per mode.
- The methods were applied to acceleration data from the gastrocnemius muscle during sprinting.
Main Results:
- High-frequency vibration modes exhibited higher damping properties than low-frequency modes.
- All identified vibration modes were underdamped, indicating an oscillatory nature.
- Lower frequency modes showed significantly increased damping ratios and greater energy dissipation compared to higher frequency modes.
- Findings align with the muscle tuning paradigm, supported by ground reaction force (GRF) power spectrum analysis.
Conclusions:
- Damping properties and energy dissipation vary significantly across different vibration modes in soft tissues.
- The analysis provides insights into muscle tuning mechanisms during activities like sprinting.
- Suggested that these parameters could serve as indicators for different running conditions, such as surface variations or fatigue levels.
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