Sensing texture using an artificial finger and a data analysis based on the standard deviation

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 a...

Full description

Saved in:
Bibliographic Details
Main Authors: Chappell, Paul H., Muridan, Norasmahan, Mohamad Hanif, N. H. H, Cranny, Andy, White, Neil M.
Format: Article
Language:English
Published: The Institution of Engineering & Technology (IET) 2015
Subjects:
Online Access:http://irep.iium.edu.my/50799/1/IET.pdf
http://irep.iium.edu.my/50799/
http://ieeexplore.ieee.org/xpls/abs_all.jsp?arnumber=7331773&tag=1
Tags: Add Tag
No Tags, Be the first to tag this record!
Institution: Universiti Islam Antarabangsa Malaysia
Language: English
id my.iium.irep.50799
record_format dspace
spelling my.iium.irep.50799 http://irep.iium.edu.my/50799/ 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. TK Electrical engineering. Electronics Nuclear engineering 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. The Institution of Engineering & Technology (IET) 2015-11 Article PeerReviewed application/pdf en http://irep.iium.edu.my/50799/1/IET.pdf Chappell, Paul H. and Muridan, Norasmahan and Mohamad Hanif, N. H. H and Cranny, Andy and White, Neil M. (2015) Sensing texture using an artificial finger and a data analysis based on the standard deviation. IET Science, Measurement & Technology, 9 (8). pp. 998-1006. ISSN 1751-8822 http://ieeexplore.ieee.org/xpls/abs_all.jsp?arnumber=7331773&tag=1 10.1049/iet-smt.2015.0003
institution Universiti Islam Antarabangsa Malaysia
building IIUM Library
collection Institutional Repository
continent Asia
country Malaysia
content_provider International Islamic University Malaysia
content_source IIUM Repository (IREP)
url_provider http://irep.iium.edu.my/
language English
topic TK Electrical engineering. Electronics Nuclear engineering
spellingShingle TK Electrical engineering. Electronics Nuclear engineering
Chappell, Paul H.
Muridan, Norasmahan
Mohamad Hanif, N. H. H
Cranny, Andy
White, Neil M.
Sensing texture using an artificial finger and a data analysis based on the standard deviation
description 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.
format Article
author Chappell, Paul H.
Muridan, Norasmahan
Mohamad Hanif, N. H. H
Cranny, Andy
White, Neil M.
author_facet Chappell, Paul H.
Muridan, Norasmahan
Mohamad Hanif, N. H. H
Cranny, Andy
White, Neil M.
author_sort Chappell, Paul H.
title Sensing texture using an artificial finger and a data analysis based on the standard deviation
title_short Sensing texture using an artificial finger and a data analysis based on the standard deviation
title_full Sensing texture using an artificial finger and a data analysis based on the standard deviation
title_fullStr Sensing texture using an artificial finger and a data analysis based on the standard deviation
title_full_unstemmed Sensing texture using an artificial finger and a data analysis based on the standard deviation
title_sort sensing texture using an artificial finger and a data analysis based on the standard deviation
publisher The Institution of Engineering & Technology (IET)
publishDate 2015
url http://irep.iium.edu.my/50799/1/IET.pdf
http://irep.iium.edu.my/50799/
http://ieeexplore.ieee.org/xpls/abs_all.jsp?arnumber=7331773&tag=1
_version_ 1643616923422818304