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

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 am...

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Main Authors: Chappell, Paul H., Muridan, Norasmahan, Mohamad Hanif, Nik Hazrin, Cranny, Andy, White, Neil M.
Format: Article
Language:English
English
Published: The Institution of Engineering & Technology (IET) 2015
Subjects:
Online Access:http://irep.iium.edu.my/50757/1/50757_Sensing_texture_using_an_artificial_finger_and_a_data_analysis.pdf
http://irep.iium.edu.my/50757/2/50757_Sensing_texture_using_an_artificial_finger_and_a_data_analysis_SCOPUS.pdf
http://irep.iium.edu.my/50757/
http://ieeexplore.ieee.org/xpls/abs_all.jsp?arnumber=7331773
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spelling my.iium.irep.507572016-12-05T03:32:40Z http://irep.iium.edu.my/50757/ Sensing texture using an artificial finger and a data analysis based on the standard deviation Chappell, Paul H. Muridan, Norasmahan Mohamad Hanif, Nik Hazrin Cranny, Andy White, Neil M. TK Electrical engineering. Electronics Nuclear engineering 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. The Institution of Engineering & Technology (IET) 2015 Article REM application/pdf en http://irep.iium.edu.my/50757/1/50757_Sensing_texture_using_an_artificial_finger_and_a_data_analysis.pdf application/pdf en http://irep.iium.edu.my/50757/2/50757_Sensing_texture_using_an_artificial_finger_and_a_data_analysis_SCOPUS.pdf Chappell, Paul H. and Muridan, Norasmahan and Mohamad Hanif, Nik Hazrin 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 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
English
topic TK Electrical engineering. Electronics Nuclear engineering
spellingShingle TK Electrical engineering. Electronics Nuclear engineering
Chappell, Paul H.
Muridan, Norasmahan
Mohamad Hanif, Nik Hazrin
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 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.
format Article
author Chappell, Paul H.
Muridan, Norasmahan
Mohamad Hanif, Nik Hazrin
Cranny, Andy
White, Neil M.
author_facet Chappell, Paul H.
Muridan, Norasmahan
Mohamad Hanif, Nik Hazrin
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/50757/1/50757_Sensing_texture_using_an_artificial_finger_and_a_data_analysis.pdf
http://irep.iium.edu.my/50757/2/50757_Sensing_texture_using_an_artificial_finger_and_a_data_analysis_SCOPUS.pdf
http://irep.iium.edu.my/50757/
http://ieeexplore.ieee.org/xpls/abs_all.jsp?arnumber=7331773
_version_ 1643613806670118912
score 13.188404