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Recognition, classification, and prediction of tactile sense

Abstract

The emulation of tactile senses is presented with the encoding of a complex surface texture through an electrical sensor device. To achieve a functional capability comparable to a human mechanoreceptor, a tactile sensor is designed by employing a naturally formed porous structure of graphene film. The inherent tactile patterns are achievable by means of proper analysis of the electrical signals that the sensor provides during the event of touching with the interacting objects. It is confirmed that the pattern-recognition method using machine learning is suitable for quantifying human tactile sensations. The classification accuracy of the tactile senor system is better than that of human touch for the tested fabric samples, which have a delicate surface texture.

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Publication details

The article was received on 22 Jan 2018, accepted on 30 Apr 2018 and first published on 01 May 2018


Article type: Paper
DOI: 10.1039/C8NR00595H
Citation: Nanoscale, 2018, Accepted Manuscript
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    Recognition, classification, and prediction of tactile sense

    S. Chun, I. Hwang, W. Son, J. H. Chang and W. Park, Nanoscale, 2018, Accepted Manuscript , DOI: 10.1039/C8NR00595H

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