Recognition, classification, and prediction of the tactile sense. Issue 22 (29th May 2018)

• Record Type: Journal Article
• Authors: Chun, Sungwoo; Hwang, Inyoung; Son, Wonkyeong; Chang, Joon-Hyuk; Park, Wanjun
• Is Part Of: Nanoscale. Volume 10:Issue 22(2018)
• Page Start: 10545
• Page End: 10553
• Publication Date: 2018-05-29
• Subjects: Nanoscience -- Periodicals; Nanotechnology -- Periodicals; 620.505
• DOI: 10.1039/c8nr00595h
• Languages: English
• ISSNs: 2040-3364

Abstract

Abstract : The emulation of the tactile sense is presented with the encoding of a complex surface texture. Abstract : The emulation of the tactile sense 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 a 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 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 sensor system is better than that of human touch for the tested fabric samples, which have a delicate surface texture.