Written for the Dept. of Kinesiology and Physical Education. Title from title page of PDF (viewed 2009/06/29). Includes bibliographical references.

Empirical knowledge is lacking on reclined seating postures. To unify such data, a biomechanical model is needed that accurately predicts posture, the relative position of the pelvis, the point of load transfer to the seat, internal and external forces, and the motion paths of the support surfaces. The overall aim of this investigation was, therefore, to create and validate a biomechanical model of reclined seating postures, and to evaluate in vivo measured and predicted data. A two-dimensional biomechanical model was developed, validated and applied. A comprehensive set of biomechanical data was collected from fifteen gender and age diverse subjects to examine the foundational principles for reclined seating ergonomics. The model agreed with 98.8% of measured data on posture across the seated test conditions. There was a significant relationship between modelled and measured force (p < .001, r = .92), which improved after normalisation (p < .001, r = .97) with an 8% full scale error. The model was robust across height and gender. Significant differences in interface pressure (peak pressure, average pressure and area), stature, back muscle activity and spinal curvature were found between all of the seated test postures. Significant relationships were found between the model predictions and all of the experimental data. This research is unique in creating a framework around reclined seating postures which connects previously disparate areas of seating research. The biomechanical model, experimental results, and theories developed from this research have potential implications in research, and design, for applications including backcare chairs, seating for long-term care and patients with neuromotor deficits, wheelchairs and airline seating. Furthermore, this study exists at the interface of anthropometric and biomechanical modelling, and therefore may have cross over potential to digital humans, where their integration with biomechanical models is at the cutting edge of the field.