Development and experimental validation of a mathematical model for friction between fabrics and a volar forearm phantom.

An analytical mathematical model for friction between a fabric strip and the volar forearm has been developed and validated experimentally. The model generalizes the common assumption of a cylindrical arm to any convex prism, and makes predictions for pressure and tension based on Amontons' law. This includes a relationship between the coefficient of static friction (mu) and forces on either end of a fabric strip in contact with part of the surface of the arm and perpendicular to its axis. Coefficients of friction were determined from experiments between arm phantoms of circular and elliptical cross-section (made from Plaster of Paris covered in Neoprene) and a nonwoven fabric. As predicted by the model, all values of mu calculated from experimental results agreed within +/- 8 per cent, and showed very little systematic variation with the deadweight, geometry, or arc of contact used. With an appropriate choice of coordinates the relationship predicted by this model for forces on either end of a fabric strip reduces to the prediction from the common model for circular arms. This helps to explain the surprisingly accurate values of mu obtained by applying the cylindrical model to experimental data on real arms.

BOLTZMANN MACHINES FOR SPEECH RECOGNITION.

Boltzmann machines offer a new and exciting approach to automatic speech recognition, and provide a rigorous mathematical formalism for parallel computing arrays. In this paper we briefly summarize Boltzmann machine theory, and present results showing their ability to recognize both static and time-varying speech patterns. A machine with 2000 units was able to distinguish between the 11 steady-state vowels in English with an accuracy of 85%. The stability of the learning algorithm and methods of preprocessing and coding speech data before feeding it to the machine are also discussed. A new type of unit called a carry input unit, which involves a type of state-feedback, was developed for the processing of time-varying patterns and this was tested on a few short sentences. Use is made of the implications of recent work into associative memory, and the modelling of neural arrays to suggest a good configuration of Boltzmann machines for this sort of pattern recognition.