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Journal of Vibration and Control· 2026Q2

Motion sickness incidence estimation incorporating back-measured torso biodynamic response: Modeling and real-vehicle evaluation

Jialiang Zhu, Di Ao, Lei Lü, Hongbo Yang et al.

Short summary

A new four-DOF model accurately predicts torso vibration transmission, reducing motion sickness incidence (MSI) estimation error by up to 22.10% compared to direct vehicle acceleration models.

AI-generated from the title and abstract; the full text is not read.

Key points

  • Developed axis-decoupled four-DOF models for vehicle-to-torso vibration transmission.
  • Validated models with real-vehicle experiments, achieving R² values of 0.9648 (z), 0.9665 (y), and 0.9524 (x) for transmissibility.
  • The back-response-based MSI estimation model reduced RMSE by 22.10% (straight) and 17.54% (slalom) versus direct models.
  • Model performance was analyzed across sex, body-mass groups, smartphone viewing, and input perturbations.

AI-generated from the title and abstract; the full text is not read.

Abstract

Accurate estimation of motion sickness incidence (MSI) is important for vehicle comfort optimization and motion-sickness mitigation. Conventional vibration-based functional models generally use vehicle acceleration directly and therefore do not account for mechanical transmission between the vehicle and the occupant. This study develops axis-decoupled four-degree-of-freedom (four-DOF) models of the effective vehicle-floor-to-back vibration transmission of seated occupants. The model-reconstructed back/upper-torso acceleration is used as a configuration-specific exposure descriptor in a functional MSI estimation model that accounts for frequency weighting and temporal accumulation. Real-vehicle experiments showed that the coefficients of determination R 2 between the model-predicted and experimentally measured magnitudes of effective floor-to-back acceleration transmissibility were 0.9648, 0.9665, and 0.9524 in the z-, y-, and x-directions, respectively. These results indicate that the four-DOF models closely reproduced the experimentally observed magnitude characteristics of vibration transmission, supporting their subsequent use in MSI estimation. Under straight and slalom driving, the back-response-based estimation model reduced the group-level root mean square error (RMSE) by 22.10% and 17.54%, respectively, compared with the direct model. Additional analyses examined estimation performance across sex and body-mass groups, naturalistic smartphone viewing, and input perturbations.

The authors' abstract, as published at the source. Journal of Vibration and Control, 2026 · DOI ↗

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Field: Orthopedics and Sports Medicine

Orthopedics and Sports MedicineMedicine