Design and implementation of nano sensor for fatty liver detection and monitoring sing machine learning algorithm

Abstract

In this thesis, human fatty liver volume is measured through Nano Graphene Polyvinyl (NGP) sensor. NGP sensor acquires the scattering electromagnetic rays from fatty liver, which arises due to dielectric property of fat. Monitoring of fatty liver volume through various imaging techniques such as ultrasound MRI and CT is time consuming, leads to exposure of harmful radiation and high cost. The existing imaging techniques measures the fatty liver volume, whereas continuous monitoring is never feasible through current imaging modalities. newline newlineThe continuous monitoring of fatty liver volume through the dielectric property of fat tissues helps to understand the prognosis of fatty liver diseases such as fibrosis, cirrhosis, alcoholic hepatitis, hepatic steatosis and steatohepatitis. The above disease leads to diabetes and cardiac ailments in human. The problem of continuous monitoring of fatty liver volume is solved through proposed NGP sensor, which is fabricated through spray pyrolysis method and consist of various materials such as nano graphene, Poly acrylic acid, Methylenbisacrylamide (MBAAm), 2,2-dimethoxy-2- phenylacetophenone (DMPAP) Poly vinyl acetate. newline newlineNGP sensor is fixed on the human liver surface and acquires scattering electromagnetic signal of fats on liver. The scattering of electromagnetic signal is due to dielectric material of fat. The electromagnetic radiation due to dielectric materials of fat is acquired from fatty liver phantom of rabbit. The fatty liver radiation from human liver is acquired. The acquired fatty liver signals from phantom and human liver are analyzed with various transforms such as Discrete Wavelet Transform (DWT), Stationary Wavelet Transform (SWT), Tunable Q Wavelet Transform (TQWT) and Multi Synchro Squeezing Transform (MSST), newline