Soft Tissue Elasticity Measurement Research Articles

Elasticity Measurement of Soft Tissues Using Hybrid Tactile and MARG-Based Displacement Sensor Systems

This paper presents a novel soft tissue elasticity measurement technique based on the fusion of Magnetic, Angular Rate, and Gravity (MARG) sensors and fixed tactile sensors. This paper is intended both as a stand-alone technology and as an extension of traditional tactile imaging of the breast to allow for accurate diagnosis of breast lesions. A series of artificial silicone materials known to imitate soft biological breast tissues is characterized using the proposed system and compared against an Instron universal testing machine to determine the system accuracy and repeatability. Comparing the characteristics of ten distinct materials, with elasticities in the range 9-90 kPa, determined by the proposed system to those from the Instron yields accuracy within 4% over the full-scale range. Interexperimental repeatability is within 1.5%. The proposed system delivers absolute elasticity of materials to within 4%, which, when combined with its lack of moving parts and low implementation cost, can significantly improve the diagnostic capability of tactile imaging in the clinical environment. By applying this technique, to determine the background elasticity of breast tissue, in conjunction with the relative lesion elasticity result from tactile arrays, the full non-invasive diagnostic potential of tactile imaging can be realized with the effect of reducing benign biopsy rates, secondary care costs, and patient stress.

Design and modeling of micro tactile sensor with three contact tips for self‐compensation of contact error in soft tissue elasticity measurement

The capability to localize diseased regions in soft tissues is essential in laparoscopic surgeries. Accordingly, surgeons need to use tactile feedback systems in order to evaluate tissue health. The purpose of this paper is to identify tissue stiffness using a new tactile sensor, whose output does not depend on the applied pushing distance or the contact angle between the sensor and the target tissue. A modification on the concept of using two linear springs with different stiffness is executed, where the current sensor design is based on using three linear springs. A detailed design procedure is carried out in order to achieve high linearity and sensitivity. The sensor measuring range is selected according to different soft‐tissue properties. In order to verify the performance of the new design, a finite element model is constructed using the ANSYS software. The results illustrate that the presented sensor can distinguish between different tissues based on their modulus of elasticity, within the specified design range. Moreover, the sensor output is independent of the applied pushing distance and the contact angle, in the range of ±8°, with a maximum error of ±4%. Furthermore, a linear I/O relationship was successfully achieved, which was the aim when considering nonlinearity analysis. © 2015 Institute of Electrical Engineers of Japan. Published by John Wiley & Sons, Inc.