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Electrical impedance tomography (EIT) is a nondestructive imaging technique used to estimate the internal conductivity distribution of a conductive domain by taking potential measurements only at the domain boundaries. If a thin electrically conductive material-that responds to pressure with local changes in conductivity-is used as a conductive domain, then EIT can be used to create a large-scale pressure-sensitive artificial skin for robotics applications. This paper presents a review of EIT and its application as a robotics sensitive skin, including EIT excitation and image reconstruction techniques, materials and skin fabrication techniques. Touch interpretation via EIT-based artificial skins is also reviewed.

This paper investigates the possibility of recognising individual persons from their walking gait using three-dimensional 'skeleton' data from an inexpensive consumer-level sensor, the Microsoft 'Kinect'. In an experimental pilot study it is shown that the K-means algorithm-as a candidate unsupervised clustering algorithm-is able to cluster gait samples from four persons with a nett accuracy of 43.6%.

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