Seated Human Response to Vehicle Vibrations: A Comprehensive Review of Classical and AI-Based Models

Vibrations caused by vehicle motion are considered one of the most important factors affecting passenger comfort and health. Continuous exposure of the human body to vibrations can lead to problems such as muscle fatigue, back pain, and musculoskeletal disorders. In this seminar, studies on biomechanical models of the human body in the seated posture are reviewed and analyzed. The main objective is to evaluate and compare different models, including simple single-degree-of-freedom models, multi-degree-of-freedom models, finite element models, and data-driven models based on artificial neural networks, in order to identify the strengths and weaknesses of each in predicting the vibrational response of the body. A review of previous studies and international standards, including ISO ۲۶۳۱, shows that simple models, despite their speed and ease of calculation, are unable to accurately predict all biomechanical responses of the body. In contrast, more complex and finite element models provide higher accuracy but require significant computational time and cost. In recent years, data-driven models, particularly those based on artificial neural networks, have emerged as a novel tool capable of identifying complex nonlinear relationships from real-world data and offering more precise predictions compared to classical models. The overall findings indicate that no single approach is entirely sufficient. Combining the interpretability of classical models with the high accuracy of data-driven models can lead to the development of more comprehensive tools for assessing and mitigating the effects of vibrations on the human body. Furthermore, identifying gaps in previous research can provide valuable directions for future studies.

کلیدواژه ها:

Whole-body vibration ، Human biomechanics ، Vehicle seat ، Multi-degree-of-freedom model ، Passenger comfort ، ANN-based modeling