Open AccessSensing texture using an artificial finger and a data analysis based on the standard deviation
Author(s) -
Chappell Paul H.,
Muridan Norasmahan,
Hanif N. Hazrin H. Mohamad,
Cranny Andy,
White Neil M.
Publication year - 2015
Publication title -
iet science, measurement and technology
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.418
H-Index - 49
eISSN - 1751-8830
pISSN - 1751-8822
DOI - 10.1049/iet-smt.2015.0003
Subject(s) - standard deviation , signal (programming language) , waveform , computer science , artificial intelligence , fast fourier transform , pattern recognition (psychology) , signal processing , computer vision , fourier transform , algorithm , mathematics , statistics , radar , telecommunications , mathematical analysis , programming language
The results from experiments with a screen‐printed 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 (SD) of signal data from the sensor. The SD analysis for texture detection is novel as it uses a combination of arithmetic processes. It windows the data sequentially and calculates the SD of the data in the windows and then averages the SDs. The output from the algorithm is the frequency spectrum of a signal. Plots, from the output of the algorithm, show events that correspond to the cyclic waveforms produced from the regularity of object surface patterns. The results from the algorithm are confirmed with an analysis of the signals using fast Fourier transforms.