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Article 2026 · 0 atıf

An Investigation of Variable Segmental Inertial Parameters in Manual Load Lifting: A Genetic Algorithm-Based Inverse Dynamics Approach

Cil, Muhammed, Usanmaz, Bilal, Gundogdu, Omer

Özet

This study investigates the common assumption that segmental inertial parameters remain constant during manual lifting using a model-based experimental approach. The primary objective was to evaluate the variability in these parameters and the subsequent effects on biomechanical calculations. The research was conducted with 20 participants (10 females and 10 males) who performed lifting tasks in the two-dimensional sagittal plane under three distinct load conditions: 2.5 kg, 5.0 kg, and 7.5 kg. Angular variations of the hand, arm, and leg joints were recorded using video-based image processing techniques. These kinematic data, integrated with anthropometric measurements, were incorporated into Newton-Euler-based equations of motion to determine joint reaction forces and net joint moments. During the initial forward dynamics stage, the solvability of the problem was tested using constant mass ratios from the established literature. In the following inverse dynamics stage, genetic algorithms were utilized to overcome solution diversity and identify the variable inertial parameters responsible for the observed motion. The results indicate that changes in segment moments of inertia reached 18-37%, leading to variations of 0-19% in net joint moments. These findings highlight the critical necessity of incorporating dynamic inertial parameters into accurate biomechanical moment calculations for manual materials handling.

Anahtar Kelimeler
2D biomechanical modeling image-based pose estimation variable inertia manual load lifting genetic algorithm OPTIMIZATION SIMULATION
WoS Kategorileri
Mathematics
Künye
Dergi
MATHEMATICS
Yıl
2026
Cilt
14
Sayı
6
eISSN
2227-7390
DOI
10.3390/math14061065
WoS UID
WOS:001725923300001
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