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Related Experiment Video

Updated: Jul 2, 2026

Quantifying Arms and Legs Contributions during Repetitive Electrically-Assisted Sit-To-Stand Exercise in Paraplegics: A Pilot Study
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Quantifying Arms and Legs Contributions during Repetitive Electrically-Assisted Sit-To-Stand Exercise in Paraplegics: A Pilot Study

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Neuromechanical synergy patterns explain metabolic efficiency differences during the sit-to-walk transition.

Wanli Zang1, Jiarong Wu1, Chen Zhu2

  • 1School of Physical Education, Soochow University, 215021, Suzhou, China.

Journal of Neuroengineering and Rehabilitation
|July 1, 2026
PubMed
Summary

Understanding sit-to-walk (STW) metabolic cost is crucial. This study linked metabolic cost to localized neuromuscular coordination patterns using a novel simulation framework, revealing subtle differences in movement control.

Keywords:
Metabolic powerMixed-matrix factorizationMuscle synergiesOpenSimUmberger model

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Published on: April 18, 2011

Area of Science:

  • Biomechanics
  • Human Movement Science
  • Computational Physiology

Background:

  • The sit-to-walk (STW) transition is vital for daily activities and a key part of mobility assessments like the Timed Up and Go test.
  • Neuromuscular control and coordination during STW, especially concerning metabolic cost, are not fully understood.
  • Existing methods lack integrated approaches to link metabolic expenditure with detailed internal movement coordination.

Purpose of the Study:

  • To develop and validate a simulation-informed framework for analyzing neuromuscular and cross-modal coordination during STW.
  • To investigate the relationship between estimated metabolic cost and synergy features during the STW transition in healthy adults.
  • To identify how different metabolic cost phenotypes relate to underlying biomechanical and electromyographic coordination patterns.

Main Methods:

  • Developed a framework combining musculoskeletal modeling (OpenSim-Umberger), metabolic cost estimation, and factorization techniques (NMF, MMF).
  • Recruited 71 healthy participants performing STW trials, collecting kinematic, ground reaction force, and surface electromyography (sEMG) data.
  • Stratified participants into metabolic cost groups and analyzed differences in temporal activation coefficients and muscle/EMG-biomechanical weights.

Main Results:

  • The simulation framework accurately estimated metabolic cost, validated against oxygen consumption.
  • Non-negative matrix factorization (NMF) revealed localized differences in temporal activation patterns between metabolic cost groups, particularly in early and late STW phases.
  • Mixed-matrix factorization (MMF) identified limited, localized differences in synergy patterns, suggesting specific EMG-biomechanical coordination variations.
  • Despite similar external movement patterns, distinct metabolic cost groups exhibited subtle, localized differences in internal coordination features.

Conclusions:

  • Metabolic cost during STW is associated with localized, rather than global, differences in neuromuscular synergy features.
  • The developed framework offers a robust method for exploring the relationship between metabolic cost and coordination in human movement.
  • This approach provides a healthy reference and generates hypotheses for studying coordination deficits in various populations and conditions.