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Multi-segment models for kinetic analysis of women during pregnancy: A systematic review
Jie Chen1, Xin Li2, Patria A Hume3
1Auckland Bioengineering Institute, The University of Auckland, Auckland, New Zealand.
Background:
During pregnancy, significant physiological, morphological, and hormonal changes profoundly affect women's biomechanics, increasing the risk of falls and musculoskeletal complaints, especially in the third trimester. To understand movement adaptations and musculoskeletal disorders in pregnant women, kinetic analysis using pregnant-specific multi-segment or musculoskeletal models is essential. This review aims to evaluate the development, applications and limitations of such models intended for kinetic analysis in pregnancy.
Methods:
Following the Preferred Reporting Items for Systematic Reviews and Meta-analyses (PRISMA) statement, PubMed, Web of Science, Scopus, and IEEE Xplore databases were searched systematically for kinetic studies involving the pregnant-specific multi-segment models. Quality assessment was completed to assess the methodological quality of the selected studies.
Results:
A total of 14 different pregnant-specific multi-segment models (including musculoskeletal models) used within 19 kinetic studies were included in this review. Currently, most scaling methods are marker-based and limited by pregnancy-related soft tissue artifacts. Segment inertial parameter estimations were largely based on regression models, which may not adequately capture the high degree of individual variability among pregnant women. Most existing models focus on analyzing lower-limb or lumbar kinetics during daily activities, yet many remain unvalidated and lack detailed lumbopelvic representations. Pregnant-specific musculoskeletal models are scarce and primarily rely on static optimization for lumbar muscle force estimation, which overlooks trunk co-contraction.
Conclusion:
Future research should focus on developing more detailed and validated pregnant-specific models, alongside advanced workflows for more accurate model personalization, to more accurately capture the biomechanical changes across different pregnancy stages and support clinically relevant kinetic analysis.
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