Fabrication and evaluation of 3D bio-scaffold wound dressings for monitoring of chronic pH wounds using fuzzy logic analysis

Abstract

Different types of wounds, such as surgical wounds, first-degree burns, and graft sites are among acute wounds. However, chronic wounds are the ones that have a gradual onset, and the healing process is stopped in terms of factors, such as poor blood flow, local pressure, diabetes and other factors. In this study, a novel wound dress made of carboxymethyl chitosan was composed of titanium nanoparticles (TiNP) using the freeze-drying technique. The wound dress contained pH-sensitive mini-emulsion, in which time and temperature are controlled, and adjusted by pH sensors. A heater was connected to the wound temperature sensor and, as the wound temperature drops below the specified range, it automatically turned on and raised the temperature to the maximum range. The mechanical strength, and biological behavior of tissue were evaluated to find an optimized sample. The prepared wound tissue was characterized using a scanning electron microscope (SEM) and the biodegradation rate was evaluated using weight change analysis. The obtained results show that the stress-strain diagram sample containing polyvinyl alcohol (PVA) had the lowest amount and the sample with TiNP had the highest strength. The results indicate that TiNP has the highest mechanical strength compared to other samples due to its inherent antibacterial properties. Moreover, fuzzy logic modeling was used to find a linguistic model for obtained experimental data. After developing the model, the results found by the model were compared to the experimental outputs. The results show that the developed method was efficient which can be used to predict the output of given data before performing any test practically.