Soft Tissue Compliance Detection in Minimally Invasive Surgery: Dynamic Measurement with Piezoelectric Sensor Based on Vibration Absorber Concept
Abstract
Recent research in the medical field has increasingly focused on tissue repair, tumor detection, and associated therapeutic techniques. A significant challenge in Minimally Invasive Surgery (MIS) is the loss of direct tactile sensation by surgeons, as they cannot physically feel the organs they operate on. Tactile feedback enhances patient safety by tissue differentiation and reducing inadvertent damage risks. Addressing this challenge, this study introduces a novel tactile sensor designed for compliance detection to enhance tactile feedback in MIS. The sensor operates on a 2-Degree-of-Freedom (2-DOF) vibration absorber system, utilizing a piezoelectric actuator with a calibrated stiffness of 188 N/m. It interprets tissue stiffness regarding a spring constant, Ko, and measures changes in soft tissue stiffness by analyzing variations in the vibration absorber frequency, specifically at the frequency which causes the first mass to exhibit zero amplitude. The effectiveness of this sensor was evaluated through tests on polydimethylsiloxane (PDMS) specimens, which were engineered to replicate varying stiffness found in human organ tissues. Young's modulus of these specimens was determined using a universal testing machine, showing a range from 10.12 to 226.89 kPa. Additionally, the sensor was applied to measure the stiffness of various chicken tissues – liver, heart, breast, and gizzard with respective Young's moduli being 1.97, 9.47, 19.55, and 96.36 kPa. This sensor successfully differentiated between tissue types non-invasively, without requiring substantial deformation or penetration of the tissues. Given its piezoelectric nature, the sensor also holds significant potential for miniaturization through Micro-Electro-Mechanical Systems technology (MEMS), broadening its applicability in surgical environments.
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DOI: https://doi.org/10.18196/jrc.v5i5.22895
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Journal of Robotics and Control (JRC)
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