Open Access

ARTICLE

Human Fatty Liver Monitoring Using Nano Sensor and IoMT

Srilekha Muthukaruppankaruppiah^1,*, Shanker Rajendiran Nagalingam², Priya Murugasen³, Rajesh Nandaamarnath⁴

1 Department of Electrical and Electronics Engineering, Saveetha Engineering College, Chennai, 602105, India.
2 Department of Computer Science and Engineering, Aalim Muhammed Salegh College of Engineering, Chennai, 600055, India.
3 Department of Physics, Saveetha Engineering College, Chennai, 602105, India.
4 Department of Medical Gastroentrology, SRM Medical College Hospital and Research Centre, Chennai, 603203, India.

* Corresponding Author: Srilekha Muthukaruppankaruppiah. Email:

Intelligent Automation & Soft Computing 2023, 35(2), 2309-2323. https://doi.org/10.32604/iasc.2023.029598

Received 07 March 2022; Accepted 19 April 2022; Issue published 19 July 2022

Abstract

Malfunction of human liver happens due to non-alcoholic fatty liver. Fatty liver measurement is used for grading hepatic steatosis, fibrosis and cirrhosis. The various imaging techniques for measuring fatty liver are Magnetic Resonance Imaging, Ultrasound and Computed Tomography. Imaging modalities lead to the exposure of harmful radiation of electromagnetic waves because of frequent measurement. The continuous monitoring of fatty liver is never achieved through imaging techniques. In this paper, the human fatty liver measured through a Fatty Liver Sensor (FLS). The continuous monitoring of the fatty liver is achieved through the FLS. FLS is fabricated through the screen-printing with materials such as graphene and polyacrylic. The fatty liver sensor is placed around the liver surface for continuous measuring fatty liver. The signal acquired from the fatty liver sensor is processed using blind source separation, a filtering technique removes the random noise from the acquired signal. The denoised signal is processed with tunable Q wavelet transform (TQWT), of FLS based fatty liver measurement fatty liver signals. The continuous fatty liver volume measured and analysis are performed through Long-short term memory and internet of medical things (IoMT). The experimental results are validated with ultrasound lab values.

---

Keywords

---