Analysis of the Effects of Obesity Classes on Manual Lifting Using Fuzzy Differential Modeling


Usanmaz B., Gündoğdu Ö., Yiğit V.

Gümüşhane Üniversitesi Sağlık Bilimleri Dergisi, cilt.14, sa.3, ss.1075-1085, 2025 (TRDizin)

Özet

Obesity has emerged as a major global public health challenge, while musculoskeletal disorders (MSDs) remain the leading cause of injury, disability, and work-related absenteeism worldwide. Increased body mass amplifies the mechanical load exerted on the musculoskeletal system during lifting tasks. In this study, a fuzzy differential equation-based model was developed to evaluate the biomechanical impact of manual material handling across varying body weights. The model quantifies the joint forces and moments at the lower back, explicitly accounting for uncertainties inherent in the model parameters.
In biomechanical modeling, obesity introduces inherent uncertainties, primarily due to inter-individual variations in body composition, particularly the relative amounts and distribution of adipose and muscle tissue, which differentially affect mechanical responses to load and movement. To address these uncertainties, fuzzy differential equations (FDEs) offer a structured approach by incorporating imprecise parameters, initial conditions, and biological variability using fuzzy logic. Unlike classical methods, FDEs represent variables as fuzzy numbers, enabling simulations to better capture the imprecision of the real world.
The results showed that with increasing obesity levels, both the forces and moments acting on the lower back during lifting tasks was increased noticeably. This pattern was observed consistently across different load weights and body heights, indicating that higher BMI leads to more greater biomechanical stress on the musculoskeletal system. The FDE model was successful in capturing the uncertainties caused by variations in body composition and changes in balance due to obesity. This approach provides a more realistic understanding of mechanical loads compared to traditional models.