From measured physical parameters to the haptic feeling of fabric

Abstract real-time cloth simulation involves the solution of many computational challenges, particularly in the context of haptic applications, where high frame rates are necessary for obtaining a satisfactory tactile experience. In this paper, we present a real-time cloth simulation system that offers a compromise between a realistic physically-based simulation of fabrics and a haptic application with high requirements in terms of computation speed. We place emphasis on architecture and algorithmic choices for obtaining the best compromise in the context of haptic applications. A first implementation using a haptic device demonstrates the features of the proposed system and leads to the development of new approaches for haptic rendering using the proposed approac

Modelling the metabolic effects of protective clothing

Protective clothing is worn in many industrial and military situations. Although worn for protection from one or more hazards, protective clothing can add significantly to the metabolic (energy) cost of work. Suggestions put forward as to the mechanisms behind the observed increases include, the additional clothing weight of the protective garments, possible friction between the number of layers that must be worn and restriction of movement due to clothing bulk. However, despite much speculation, these areas have not received much investigation. Wearing protective clothing from a range of industries and with quite different characteristics for example weight, bulk and stiffness significantly increased metabolic rate when walking, stepping and completing an obstacle course activity. Increases in the metabolic rate of up to 20% above control conditions (lightweight tracksuit and trainers worn) were seen. A number of clothing properties were then investigated to try and understand the causes of these recorded metabolic rate increases. Clothing bulk was measured at 3 sites, upper arm, torso and thigh. The stiffness of the clothing was also calculated, using a method which measured the clothing drape of the sleeve, main body of the garment and trouser leg. A multiple regression carried out on the data showed body weight to be the best predictor of absolute metabolic increases across all work modes. For the % increase in metabolic rate total clothing weight was the best predictor. Torso bulk was negatively correlated with the increased metabolic rate for walking and stepping and the overall average, whereas leg bulk was a significant predictor of an increased stepping metabolic rate and leg stiffness a significant predictor for the obstacle course work mode