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Updated: Sep 9, 2026

Subject-specific Musculoskeletal Model for Studying Bone Strain During Dynamic Motion
Published on: April 11, 2018
[Research on a dynamic evolution model of driving fatigue-induced musculoskeletal disorders risk]
1Department of Exercise Biochemistry, Exercise Science School, Beijing Sport University, Beijing 100084, China Occupational Protection and Ergonomics Research Laboratory, National Institute for Occupational Health and Poison Control, Chinese Center for Disease Control and Prevention, Beijing 100050, China.
Abstract:
Objective: To analyze the temporal changes of pressure distribution at the driver's buttock-thigh interface during prolonged driving, and to construct a dynamic progression model of driving fatigue-induced musculoskeletal injury risk, thereby provide a theoretical basis for early warning of work related musculoskeletal disorders (WMSDs) . Methods: From September to October 2024, sixteen healthy adult male drivers were recruited to complete a 2-hour simulated driving task. Seat-body interface pressure data were collected using a BodiTrak®array pressure sensing cushion system, divided into sequential 15-minute windows. Repeated-measures ANOVA was used to analyze and compare changes in representative peak pressure (REP(MAX)) and effective loaded area (REP(AREA)) in the gluteal region, total path length of the center of pressure (COP(LEN)), 95% confidence ellipse area of COP(LEN) (COP(AREA)), and bilateral comprehensive asymmetry index (AIPL) . Results: In both the first and second hours, the main effects of time on REP(MAX) and REP(AREA) in the left and right gluteal regions, as well as on COP(AREA) and COP(LEN), were statistically significant (P<0.001). Post-hoc pairwise comparisons showed that REP(MAX) in the gluteal region at T1-2, T1-3, and T1-4 were significantly higher than that at T1-1, and REP(MAX) in the gluteal region at T2-2, T2-3, and T2-4 were significantly higher than that at T2-1 (P<0.05). Both COP(LEN) and COP(AREA) at T1-3 and T1-4 were significantly higher than those at T1-1, and at T2-3 and T2-4 were significantly higher than those at T2-1 (P<0.05). During the first hour, the main effect of time on AIPL was statistically significant (P<0.05), post-hoc pairwise comparisons showed that AIPL at T1-2, T1-3, and T1-4 were significantly higher than that at T1-1 (P<0.05) . Conclusion: A three-stage dynamic progression model of driving fatigue, characterized by pressure concentration-postural instability-bilateral imbalance, is established. Asymmetric compensation is proposed as an early signal of fatigue initiation, providing a theoretical basis for early risk warning of WMSDs based on seat pressure distribution.
