Yoshimoto S, Kuroda Y, Oshiro O, Yoshimoto S, Kuroda Y, Oshiro O, Yoshimoto S, Oshiro O, Kuroda Y. Estimation of Object Elasticity by Capturing Fingernail Images During Haptic Palpation.
IEEE TRANSACTIONS ON HAPTICS 2018;
11:204-211. [PMID:
29911979 DOI:
10.1109/toh.2018.2803053]
[Citation(s) in RCA: 1] [Impact Index Per Article: 0.2] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 06/08/2023]
Abstract
In this study, we present a system that performs natural-touch-based elasticity estimation for an object by using a depth camera. To estimate elasticity, which is defined as an object's Young's modulus, a strain-stress curve is obtained from fingernail images during haptic palpation. From a color image, the proposed system detects a fingernail and extracts 10 feature values related to the contact force; then, it estimates the force using a multiple regression model. Deformation of the object was estimated from the finger's three-dimensional position obtained from both color and depth images. Then, a strain-stress curve was determined using the force and deformation data. Evaluation experiments were designed to obtain the strain-stress curves of five objects from 10 participants; then, the estimation performance was investigated. The results show that the reliable range of sensing was within Young's modulus values of 0.12-5.6 MPa and the precision of the measurement was 55 percent of the estimated elasticity.
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