Sensing texture using an artificial finger and a data analysis based on the standard deviation - Chappell, Paul H.; Muridan, Norasmahan; Mohamad Hanif, N. H. H; Cranny, Andy; White, Neil M. (The Institution of Engineering & Technology (IET), 2015)
The results from experiments with screen-printed a piezoelectric sensor, mounted on an artificial finger-tip and including a cosmetic covering, are shown to detect surface information from regular texture patterns. For the automatic control of an artificial hand and to feedback information to the amputee, an algorithm has been developed based on the standard deviation of signal data from the sensor. The standard deviation analysis for texture detection is novel as it uses a combination of arthmetic processes. It windows the data, calculates the standard deviation of the data in the windows and then averages the standard deviations. The output from the algorthim is the frequency sepectrum of a signal. Plots for the output from the algorithm show events that correspond to the cyclic waveforms produced from the regularity of object surface patterns. The algorithm output can use any length of data input. The results from the algorithm are confirmed with an analysis of the signals using Fast Fourier Transforms.