TY - JOUR
T1 - Optimizing a viscoelastic finite element model to represent the dry, natural, and moist human finger pressing on glass
AU - Nam, Saekwang
AU - Kuchenbecker, Katherine J.
N1 - Publisher Copyright:
© 2008-2011 IEEE.
PY - 2021/4/1
Y1 - 2021/4/1
N2 - When a fingerpad presses into a hard surface, the development of the contact area depends on the pressing force and speed. Importantly, it also varies with the finger's moisture, presumably because hydration changes the tissue's material properties. Therefore, we collected data from one finger repeatedly pressing a glass plate under three moisture conditions, and we constructed a finite element model that we optimized to simulate the same three scenarios. We controlled the moisture of the subject's finger to be dry, natural, or moist and recorded 15 pressing trials in each condition. The measurements include normal force over time plus finger-contact images that are processed to yield gross contact area. We defined the axially symmetric 3D model's lumped parameters to include an SLS-Kelvin model (spring in series with parallel spring and damper) for the bulk tissue, plus an elastic epidermal layer. Particle swarm optimization was used to find the parameter values that cause the simulation to best match the trials recorded in each moisture condition. The results show that the softness of the bulk tissue reduces as the finger becomes more hydrated. The epidermis of the moist finger model is softest, while the natural finger model has the highest viscosity.
AB - When a fingerpad presses into a hard surface, the development of the contact area depends on the pressing force and speed. Importantly, it also varies with the finger's moisture, presumably because hydration changes the tissue's material properties. Therefore, we collected data from one finger repeatedly pressing a glass plate under three moisture conditions, and we constructed a finite element model that we optimized to simulate the same three scenarios. We controlled the moisture of the subject's finger to be dry, natural, or moist and recorded 15 pressing trials in each condition. The measurements include normal force over time plus finger-contact images that are processed to yield gross contact area. We defined the axially symmetric 3D model's lumped parameters to include an SLS-Kelvin model (spring in series with parallel spring and damper) for the bulk tissue, plus an elastic epidermal layer. Particle swarm optimization was used to find the parameter values that cause the simulation to best match the trials recorded in each moisture condition. The results show that the softness of the bulk tissue reduces as the finger becomes more hydrated. The epidermis of the moist finger model is softest, while the natural finger model has the highest viscosity.
KW - Fingerpad
KW - Finite element modeling
KW - Gross contact area
KW - Moisture
UR - http://www.scopus.com/inward/record.url?scp=85105879522&partnerID=8YFLogxK
U2 - 10.1109/TOH.2021.3077549
DO - 10.1109/TOH.2021.3077549
M3 - Article
C2 - 33945487
AN - SCOPUS:85105879522
SN - 1939-1412
VL - 14
SP - 303
EP - 309
JO - IEEE Transactions on Haptics
JF - IEEE Transactions on Haptics
IS - 2
M1 - 9423563
ER -