High-bandwidth tribometry as a means of recording natural textures

Research output: Chapter in Book/Report/Conference proceedingConference contribution

6 Scopus citations

Abstract

The measurement of perceptually relevant information about textures has been approached through profilometry, vibrometry, and tribometry. Manfredi et al. [1] used a laser Doppler vibrometer to measure skin surface vibrations as a texture sample slides across a fingertip. In our work, we treat the Manfredi et al. measurements as a gold standard, and assess the performance of a simpler and more portable device: A high-bandwidth tribometer. The tribometer was used to measure shear and normal forces applied to each of six texture samples as a fingertip scanned across them. The collected data was used to build two classifiers: One based on features extracted from the spectra (which treats the data as stationary); and a second based on the first through fourth order statistics associated with a set of band-pass filters (which treats the data as nonstationary). The results indicate that tribometry, while not as effective as vibrometry, may nonetheless prove effective as a means of recording natural texture. Additionally, we find that the non-stationarity of skin vibrations may serve as means of texture classification. Ongoing work aims to couple tribometric recordings with texture rendering and playback via surface haptic devices, and to understand the perceptual significance of non-stationarity in vibrations.

Original languageEnglish (US)
Title of host publication2017 IEEE World Haptics Conference, WHC 2017
PublisherInstitute of Electrical and Electronics Engineers Inc.
Pages629-634
Number of pages6
ISBN (Electronic)9781509014255
DOIs
StatePublished - Jul 21 2017
Event7th IEEE World Haptics Conference, WHC 2017 - Munich, Germany
Duration: Jun 6 2017Jun 9 2017

Publication series

Name2017 IEEE World Haptics Conference, WHC 2017

Other

Other7th IEEE World Haptics Conference, WHC 2017
CountryGermany
CityMunich
Period6/6/176/9/17

ASJC Scopus subject areas

  • Instrumentation
  • Cognitive Neuroscience
  • Sensory Systems
  • Human Factors and Ergonomics
  • Human-Computer Interaction

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