Lump Detection - Tactile Sensing and Displays - page 124

reduce the number of involved parameters, by introducing a dimensionless ratio D/t ,the
lump diameter to the tissue thickness.
Soft tissue shows very complex behavior, including hysteresis and viscoelasticity, which
were not considered in this study. Nevertheless, special attention was paid to modeling
accurately the nonlinearity of the tissue. In order to accomplish this, an elastomer was
mechanically tested and the experimental data used for simulations. Initially several strain
energy functions, such as, Ogden, Neo - Hookean, and Mooney - Rivlin were considered
and finally it was found that the three-term Mooney - Rivlin function concurred favorably
with the experimental data.
The assumptions made in the geometry and boundary conditions were that they did
adequately replicate the state of the tissue grasped by a typical MIS or surgical robot
grasper tool and that, in either case, the existence of a lump within the grasped tissue
affected the pressure distribution on the contact surface. Therefore, close inspection of
the pressure distribution reveals valuable information about the lump, which is useful,
particularly in developing inverse models of the problem, as well as in designing smart
endoscopic graspers. The findings of this study can be used to calculate the required
sensitivity and resolution of those sensing elements located at the contact surface, as well
as the spatial resolution of any proposed array or matrix of the sensors for this purpose. In
addition, the tactile image can be used for the visualization and enhancement of existing
2D video images.
References
1. Miyaji, K., Furuse, A., Nakajima, J. et al . (1997) The stiffness of lymph nodes containing lung carcinoma
metastases. Cancer , 80 , 1920 - 1925.
2. Barman, I. and Guha, S.K. (2006) Analysis of a new combined stretch and pressure sensor for internal
nodule palpation. Sensors and Actuators A: Physical , 125 , 210 - 216.
3. Hosseini, M., Najarian, S., Motaghinasab, S., and Dargahi, J. (2006) Detection of tumours using a com-
putational tactile sensing approach. The International Journal of Medical Robotics and Computer Assisted
Surgery , 2 , 333 - 340.
4. Wellman, P.S., Dalton, E.P., Krag, D. et al . (2001) Tactile imaging of breast masses: first clinical report.
Arch Surg , 136 , 204 - 208.
5. Wellman, P.S. and Howe, R.D. (1999) Extracting features from tactile maps. Proceedings of Medical Image
Computing and Computer-Assisted Intervention, 1999, pp. 1133 - 1142.
6. Wellman, P.S., Howe, R.D., Dewagan, N. et al . (1999) Tactile imaging: a method for documenting breast
masses. Proceedings of the First Joint, BMES/EMBS Conference, 1999 Engineering in Medicine and
Biology 21st Annual Conference and the 1999 Annual Fall Meeting of the Biomedical Engineering Society,
p. 1131.
7. Kattavenos, N., Lawrenson, B., Frank, T.G. et al . (2004) Force-sensitive tactile sensor for minimal access
surgery. Minimally Invasive Therapy & Allied Technologies , 13 , 42 - 46.
8. Gerhard A. Holzapfel. Nonlinear Solid Mechanics: A Continuum Approach for Engineering. John Wiley &
Sons Ltd., Baffins Lane, Chichester, West Sussex PO19 1UD, England, 2000.
9. ANSYS Inc. (2004) Theory Reference, ANSYS Release 9.0.002114.
10. Williams, J.G. (1973) Stress Analysis of Polymers , Longman Group Limited, London.
11. Karol, M. (2000) Constitutive modelling of abdominal organs. Journal of Biomechanics , 33 , 367 - 373.
12. ANSYS Inc. Documentation for ANSYS, Modeling Material Nonlinearities/Mixed u-p Formulation,
Release 10.