Comparison of Stiffness of Skin - Simulations vs Experimental
DOI:
https://doi.org/10.37591/tmet.v7i3.60Keywords:
Stiffness, Skin, Open Source Electronics, Deformation, Simulation vs ExperimentAbstract
Minimally invasive surgeries are the most elusive, yet highly demanded subset of surgeries which requires precise knowledge of the pertinent patient. Compared to conventional surgeries, minimally invasive surgeries are characterized by less pain, low risk of infection, lesser scarring, etc. In the status quo, doctors use intuition through experience to determine the parameters for surgery such as the force required to cut, size of cut, depth of cut, etc. With the onset of innovative technology that can perform operations that are too small or risky to be performed by humans, properties of skin are mandatory to be known. Therefore, there is a need for determining the stiffness of skin at varying parts of the body on-site, requiring a small, fast, mobile device that is accurate. The first phase of the work revolves around carrying out simulations by modeling the various layers of skin and applying a force. Subsequent research utilizes statistical analysis tools, which are applied to analyze skin stiffness parameters of patients undergoing the minimally invasive surgeries for different parts of the body. Open source electronics are used to experimentally identify and datalog variables such as force and displacement to calculate the stiffness of the skin. Conformation diagnoses were conducted to verify the results of the experimental values and there was close agreement between the experimental and theoretical stiffness. This process can provide a quantitative value for exact use for automatic robots for sensitive surgeries such as robotic and endoscopic operations. This research eliminates use of intuitive examination, and provides quantitative insight on the patient’s surgeries.
Cite this Article
Akarsh Kidiyur Sathish, Parichit Kumar, Codanda Devaiah Monappa et al. Comparison of Stiffness of Skin: Simulations versus Experimental. Trends in Mechanical Engineering & Technology. 2017; 7(3): 1–7p.
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