Cargando…

Nonlinear Tactile Estimation Model Based on Perceptibility of Mechanoreceptors Improves Quantitative Tactile Sensing

Tactile sensing has attracted significant attention as a tactile quantitative evaluation method because the tactile sensation is an important factor while evaluating consumer products. Although the human tactile perception mechanism has nonlinearity, previous studies have often developed linear regr...

Descripción completa

Detalles Bibliográficos
Autores principales: Sagara, Momoko, Nobuyama, Lisako, Takemura, Kenjiro
Formato: Online Artículo Texto
Lenguaje:English
Publicado: MDPI 2022
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9460129/
https://www.ncbi.nlm.nih.gov/pubmed/36081155
http://dx.doi.org/10.3390/s22176697
_version_ 1784786671073492992
author Sagara, Momoko
Nobuyama, Lisako
Takemura, Kenjiro
author_facet Sagara, Momoko
Nobuyama, Lisako
Takemura, Kenjiro
author_sort Sagara, Momoko
collection PubMed
description Tactile sensing has attracted significant attention as a tactile quantitative evaluation method because the tactile sensation is an important factor while evaluating consumer products. Although the human tactile perception mechanism has nonlinearity, previous studies have often developed linear regression models. In contrast, this study proposes a nonlinear tactile estimation model that can estimate sensory evaluation scores from physical measurements. We extracted features from the vibration data obtained by a tactile sensor based on the perceptibility of mechanoreceptors. In parallel, a sensory evaluation test was conducted using 10 evaluation words. Then, the relationship between the extracted features and the tactile evaluation results was modeled using linear/nonlinear regressions. The best model was concluded by comparing the mean squared error between the model predictions and the actual values. The results imply that there are multiple evaluation words suitable for adopting nonlinear regression models, and the average error was 43.8% smaller than that of building only linear regression models.
format Online
Article
Text
id pubmed-9460129
institution National Center for Biotechnology Information
language English
publishDate 2022
publisher MDPI
record_format MEDLINE/PubMed
spelling pubmed-94601292022-09-10 Nonlinear Tactile Estimation Model Based on Perceptibility of Mechanoreceptors Improves Quantitative Tactile Sensing Sagara, Momoko Nobuyama, Lisako Takemura, Kenjiro Sensors (Basel) Article Tactile sensing has attracted significant attention as a tactile quantitative evaluation method because the tactile sensation is an important factor while evaluating consumer products. Although the human tactile perception mechanism has nonlinearity, previous studies have often developed linear regression models. In contrast, this study proposes a nonlinear tactile estimation model that can estimate sensory evaluation scores from physical measurements. We extracted features from the vibration data obtained by a tactile sensor based on the perceptibility of mechanoreceptors. In parallel, a sensory evaluation test was conducted using 10 evaluation words. Then, the relationship between the extracted features and the tactile evaluation results was modeled using linear/nonlinear regressions. The best model was concluded by comparing the mean squared error between the model predictions and the actual values. The results imply that there are multiple evaluation words suitable for adopting nonlinear regression models, and the average error was 43.8% smaller than that of building only linear regression models. MDPI 2022-09-04 /pmc/articles/PMC9460129/ /pubmed/36081155 http://dx.doi.org/10.3390/s22176697 Text en © 2022 by the authors. https://creativecommons.org/licenses/by/4.0/Licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license (https://creativecommons.org/licenses/by/4.0/).
spellingShingle Article
Sagara, Momoko
Nobuyama, Lisako
Takemura, Kenjiro
Nonlinear Tactile Estimation Model Based on Perceptibility of Mechanoreceptors Improves Quantitative Tactile Sensing
title Nonlinear Tactile Estimation Model Based on Perceptibility of Mechanoreceptors Improves Quantitative Tactile Sensing
title_full Nonlinear Tactile Estimation Model Based on Perceptibility of Mechanoreceptors Improves Quantitative Tactile Sensing
title_fullStr Nonlinear Tactile Estimation Model Based on Perceptibility of Mechanoreceptors Improves Quantitative Tactile Sensing
title_full_unstemmed Nonlinear Tactile Estimation Model Based on Perceptibility of Mechanoreceptors Improves Quantitative Tactile Sensing
title_short Nonlinear Tactile Estimation Model Based on Perceptibility of Mechanoreceptors Improves Quantitative Tactile Sensing
title_sort nonlinear tactile estimation model based on perceptibility of mechanoreceptors improves quantitative tactile sensing
topic Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9460129/
https://www.ncbi.nlm.nih.gov/pubmed/36081155
http://dx.doi.org/10.3390/s22176697
work_keys_str_mv AT sagaramomoko nonlineartactileestimationmodelbasedonperceptibilityofmechanoreceptorsimprovesquantitativetactilesensing
AT nobuyamalisako nonlineartactileestimationmodelbasedonperceptibilityofmechanoreceptorsimprovesquantitativetactilesensing
AT takemurakenjiro nonlineartactileestimationmodelbasedonperceptibilityofmechanoreceptorsimprovesquantitativetactilesensing