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

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:	TK Electrical engineering. Electronics Nuclear engineering
Online Access:	http://irep.iium.edu.my/50799/ http://irep.iium.edu.my/50799/ http://irep.iium.edu.my/50799/ http://irep.iium.edu.my/50799/1/IET.pdf

id	iium-50799
recordtype	eprints
spelling	iium-507992018-06-25T00:22:43Z 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
repository_type	Digital Repository
institution_category	Local University
institution	International Islamic University Malaysia
building	IIUM Repository
collection	Online Access
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/ http://irep.iium.edu.my/50799/ http://irep.iium.edu.my/50799/ http://irep.iium.edu.my/50799/1/IET.pdf
first_indexed	2023-09-18T21:11:52Z
last_indexed	2023-09-18T21:11:52Z
_version_	1777411306425417728

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

Similar Items