A Method for Constructing a Dynamic Seat Adjustment Model to Mitigate Prolonged-Sitting Discomfort

ObjectiveTo develop and preliminarily validate a behavior- and height-based strategy-group-specific dynamic seat-adjustment model that generates coordinated low-frequency seat trajectories to reduce subjective discomfort during prolonged public-transport sitting.BackgroundDynamic seating may relieve sitting-related discomfort, but existing strategies rarely model coupled seat adjustments while considering behavioral and anthropometric variability.MethodsSixty-six adults completed counterbalanced 2-h resting and phone-use sessions. Every 15 min, they adjusted seven seat dimensions to their preferred configuration and rated overall and regional discomfort before and after adjustment. An improvement-driven weighted multi-output random forest was trained within Behavior × Height-Based Strategy Group strata, using elapsed sitting time as the only input and seven-dimensional seat configuration as the output; discomfort improvement was used only for sample weighting. Predicted configurations were smoothed into low-frequency trajectories. An independent within-subject crossover experiment compared Static, Mean-trajectory, and Dynamic conditions.ResultsPreferred configurations differed by behavior and height-based strategy group and changed systematically over time. Multi-output forests outperformed independent single-output models, supporting coordinated trajectory learning, whereas improvement-driven weighting mainly provided a relief-oriented training bias. In validation, the Dynamic condition reduced overall discomfort relative to Static seating across both behaviors and time points. Compared with the non-individualized Mean-trajectory baseline, Dynamic seating produced additional region- and behavior-dependent perceived-comfort benefits, especially in neck and trunk-related regions.ConclusionA stratified multi-output model can generate coordinated time-varying seat trajectories associated with lower subjective discomfort.ApplicationThis framework offers a preliminary basis for low-frequency passive adjustment in transportation seats with comparable geometry while requiring limited passenger input.