Development and validation of a new method for measuring friction between skin and nonwoven materials.

A new method for measuring the coefficient of friction between nonwoven materials and the curved surface of the volar forearm has been developed and validated. The method was used to measure the coefficient of static friction for three different nonwoven materials on the normal (dry) and over-hydrated volar forearms of five female volunteers (ages 18-44). The method proved simple to run and had good repeatability: the coefficient of variation (standard deviation expressed as a percentage of the mean) for triplets of repeat measurements was usually (80 per cent of the time) less than 10 per cent. Measurements involving the geometrically simpler configuration of pulling a weighted fabric sample horizontally across a quasi-planar area of volar forearm skin proved experimentally more difficult and had poorer repeatability. However, correlations between values of coefficient of static friction derived using the two methods were good (R = 0.81 for normal (dry) skin, and 0.91 for over-hydrated skin). Measurements of the coefficient of static friction for the three nonwovens for normal (dry) and for over-hydrated skin varied in the ranges of about 0.3-0.5 and 0.9-1.3, respectively. In agreement with Amontons' law, coefficients of friction were invariant with normal pressure over the entire experimental range (0.1-8.2 kPa).

Multiple object tracking using evolutionary MCMC-based particle algorithms

Algorithms are presented for detection and tracking of multiple clusters of co-ordinated targets. Based on a Markov chain Monte Carlo sampling mechanization, the new algorithms maintain a discrete approximation of the filtering density of the clusters' state. The filters' tracking efficiency is enhanced by incorporating various sampling improvement strategies into the basic Metropolis-Hastings scheme. Thus, an evolutionary stage consisting of two primary steps is introduced: 1) producing a population of different chain realizations, and 2) exchanging genetic material between samples in this population. The performance of the resulting evolutionary filtering algorithms is demonstrated in two different settings. In the first, both group and target properties are estimated whereas in the second, which consists of a very large number of targets, only the clustering structure is maintained. © 2009 IFAC.