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

Sensing texture using an artificial finger and a data analysis based on the standard deviation
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 23 artificial finger-tip and including a cosmetic covering, are shown to detect surface information from 24 regular texture patterns. For the automatic control of an artificial hand and to feedback information to 25 the amputee, an algorithm has been developed based on the standard deviation of signal data from the 26 sensor. The standard deviation analysis for texture detection is novel as it uses a combination of 27 arithmetic processes. It windows the data sequentially and calculates the standard deviation of the data 28 in the windows and then averages the standard deviations. The output from the algorithm is the 29 frequency spectrum of a signal. Plots for the output from the algorithm show events that correspond to 30 the cyclic waveforms produced from the regularity of object surface patterns. The results from the 31 algorithm are confirmed with an analysis of the signals using Fast Fourier Transforms.
electric sensing devices, piezoelectric transducers, data analysis, surface texture, prosthetics, fast fourier transforms, surface topography measurement
1751-8830
1-9
Chappell, Paul H.
2d2ec52b-e5d0-4c36-ac20-0a86589a880e
Muridan, Norasmahan
5a68e73f-593c-4aa2-b7c4-e92cda3de69e
Mohamad Hanif, N. Hazrin H.
bac9233d-8e9f-4b10-8abb-28ab8ffcd948
Cranny, Andy
2ebc2ccb-7d3e-4a6a-91ac-9f089741939e
White, Neil M.
c7be4c26-e419-4e5c-9420-09fc02e2ac9c
Chappell, Paul H.
2d2ec52b-e5d0-4c36-ac20-0a86589a880e
Muridan, Norasmahan
5a68e73f-593c-4aa2-b7c4-e92cda3de69e
Mohamad Hanif, N. Hazrin H.
bac9233d-8e9f-4b10-8abb-28ab8ffcd948
Cranny, Andy
2ebc2ccb-7d3e-4a6a-91ac-9f089741939e
White, Neil M.
c7be4c26-e419-4e5c-9420-09fc02e2ac9c

Chappell, Paul H., Muridan, Norasmahan, Mohamad Hanif, N. Hazrin H., 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, 1-9.

Record type: Article

Abstract

The results from experiments with a screen-printed piezoelectric sensor, mounted on an 23 artificial finger-tip and including a cosmetic covering, are shown to detect surface information from 24 regular texture patterns. For the automatic control of an artificial hand and to feedback information to 25 the amputee, an algorithm has been developed based on the standard deviation of signal data from the 26 sensor. The standard deviation analysis for texture detection is novel as it uses a combination of 27 arithmetic processes. It windows the data sequentially and calculates the standard deviation of the data 28 in the windows and then averages the standard deviations. The output from the algorithm is the 29 frequency spectrum of a signal. Plots for the output from the algorithm show events that correspond to 30 the cyclic waveforms produced from the regularity of object surface patterns. The results from the 31 algorithm are confirmed with an analysis of the signals using Fast Fourier Transforms.

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More information

Accepted/In Press date: 29 April 2015
e-pub ahead of print date: 3 August 2015
Keywords: electric sensing devices, piezoelectric transducers, data analysis, surface texture, prosthetics, fast fourier transforms, surface topography measurement
Organisations: EEE

Identifiers

Local EPrints ID: 380020
URI: https://eprints.soton.ac.uk/id/eprint/380020
ISSN: 1751-8830
PURE UUID: dbfead8f-5960-4c35-9d99-38692c98841e
ORCID for Neil M. White: ORCID iD orcid.org/0000-0003-1532-6452

Catalogue record

Date deposited: 01 Sep 2015 12:42
Last modified: 06 Jun 2018 13:12

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