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

Momoko Sagara, Lisako Nobuyama, Kenjiro Takemura

研究成果: Article査読

抄録

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.

本文言語English
論文番号6697
ジャーナルSensors
22
17
DOI
出版ステータスPublished - 2022 9月

ASJC Scopus subject areas

  • 分析化学
  • 情報システム
  • 生化学
  • 原子分子物理学および光学
  • 器械工学
  • 電子工学および電気工学

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