Get 20M+ Full-Text Papers For Less Than $1.50/day. Start a 14-Day Trial for You or Your Team.

Learn More →

Modeling perceived quality of haptic impressions based on various sensor data sources

Modeling perceived quality of haptic impressions based on various sensor data sources This paper aims to provide an approach of modeling haptic impressions of surfaces over a wide range of applications by using multiple sensor sources.Design/methodology/approachA multisensory measurement experiment was conducted using various leather and artificial leather surfaces. After processing of measurement data and feature extraction, different learning algorithms were applied to the measurement data and a corresponding set of data from a sensory study. The study contained evaluations of the same surfaces regarding descriptors of haptic quality (e.g. roughness) by human subjects and was conducted in a former research project.FindingsThe research revealed that it is possible to model and project haptic impressions by using multiple sensor sources in combination with data fusion. The presented method possesses the potential for an industrial application.Originality/valueThis paper provides a new approach to predict haptic impressions of surfaces by using multiple sensor sources. http://www.deepdyve.com/assets/images/DeepDyve-Logo-lg.png Sensor Review Emerald Publishing

Modeling perceived quality of haptic impressions based on various sensor data sources

Loading next page...
 
/lp/emerald-publishing/modeling-perceived-quality-of-haptic-impressions-based-on-various-Nm6NNDKQsU

References (16)

Publisher
Emerald Publishing
Copyright
© Emerald Publishing Limited
ISSN
0260-2288
DOI
10.1108/sr-07-2017-0123
Publisher site
See Article on Publisher Site

Abstract

This paper aims to provide an approach of modeling haptic impressions of surfaces over a wide range of applications by using multiple sensor sources.Design/methodology/approachA multisensory measurement experiment was conducted using various leather and artificial leather surfaces. After processing of measurement data and feature extraction, different learning algorithms were applied to the measurement data and a corresponding set of data from a sensory study. The study contained evaluations of the same surfaces regarding descriptors of haptic quality (e.g. roughness) by human subjects and was conducted in a former research project.FindingsThe research revealed that it is possible to model and project haptic impressions by using multiple sensor sources in combination with data fusion. The presented method possesses the potential for an industrial application.Originality/valueThis paper provides a new approach to predict haptic impressions of surfaces by using multiple sensor sources.

Journal

Sensor ReviewEmerald Publishing

Published: May 24, 2018

Keywords: Haptic devices; Sensor fusion; Neural networks; Metrology; Perceived quality; Human haptic prediction

There are no references for this article.