Estimating Co-Contraction activation of trunk muscles using a Novel musculoskeletal model for pregnant women

Saori Morino, Masaki Takahashi

Research output: Contribution to journalArticlepeer-review

3 Citations (Scopus)

Abstract

Weight gain and stretched abdominal muscles from an enlarged gravid uterus are remarkable features during pregnancy. These changes elicit postural instability and place strain on body segments, contributing to lower back pain. In general, the agonist and antagonist muscles act simultaneously to increase joint stabilization; however, this can cause additional muscle stress during movement. Furthermore, this activation can be observed in pregnant women because of their unstable body joints. Hence, physical modalities based on assessments of muscle activation are useful for managing low back pain during pregnancy. Musculoskeletal models are common when investigating muscle load. However, it is difficult to apply such models to pregnant women and estimate the co-contraction of muscles using musculoskeletal models. Therefore, the purpose of this study is to construct a musculoskeletal model for pregnant women that estimates the co-contraction of trunk muscles. First, motion analysis was conducted on a pregnant woman and the muscle activations of the rectus abdominis and erector spinae were measured. Then, the musculoskeletal model was specifically modified for pregnant women. Finally, the co-contraction was estimated from the results of the musculoskeletal model and electromyography data using a genetic algorithm. With the proposed methods, weakened abdominal muscle torque and the co-contraction activation of trunk muscles were estimated successfully.

Original languageEnglish
Article number1067
JournalApplied Sciences (Switzerland)
Volume7
Issue number10
DOIs
Publication statusPublished - 2017 Oct 15

Keywords

  • Biomechanics
  • Genetic algorithm
  • Musculoskeletal model
  • Pregnancy

ASJC Scopus subject areas

  • Materials Science(all)
  • Instrumentation
  • Engineering(all)
  • Process Chemistry and Technology
  • Computer Science Applications
  • Fluid Flow and Transfer Processes

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