A Standard Methodology to Characterize the Intrinsic Material Properties of Compliant Test Stimuli
| Autor: | Gregory J. Gerling, Alexis K. Bowen, Yuxiang Wang, Steven C. Hauser, Bryan R. Soltis, Kathryn D. Fanta |
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| Rok vydání: | 2018 |
| Předmět: |
Computer science
Acoustics Modulus Stiffness Uniaxial compression 02 engineering and technology 021001 nanoscience & nanotechnology Article Computer Science Applications Human-Computer Interaction 03 medical and health sciences 0302 clinical medicine medicine Elasticity (economics) medicine.symptom 0210 nano-technology Material properties 030217 neurology & neurosurgery Tactile sensor Haptic technology |
| Zdroj: | IEEE Transactions on Haptics. 11:498-508 |
| ISSN: | 2334-0134 1939-1412 |
| DOI: | 10.1109/toh.2018.2825396 |
| Popis: | Understanding how we perceive differences in material compliance, or 'softness,' is a central topic in the field of haptics. The intrinsic elasticity of an object is the primary factor thought to influence our perceptual estimates. Therefore, most studies test and report the elasticity of their stimuli, typically as stiffness or modulus. However, many reported estimates are of very high magnitude for silicone-elastomers, which may be due to artifacts in characterization technique. This makes it very difficult to compare the perceptual results between the studies. The work herein defines a standardized and easy-to-implement way to characterize test stimuli. The procedure involves the unconstrained, uniaxial compression of a plate into cylindrical substrates 10 mm tall by 10 mm diameter. The resultant force-displacement data are straightforwardly converted into stress-strain data, from which a modulus is readily derived. This procedure was used to re-characterize stimuli from prior studies. The revised results from the validated method herein are 200-1,100 percent lower than modulus values either reported and/or approximated from stiffness. This is practically significant when differences of 10-15 percent are perceptually discriminable. The re-characterized estimates are useful in comparing prior studies and designing new studies. Furthermore, this characterization methodology may help more readily bridge studies on perception with those designing technology. |
| Databáze: | OpenAIRE |
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