Work

Human Body-Related Disease Diagnosis Systems Using CMOS Image Sensors: A Systematic Review

Year: 2021

Type: review

Abstract: According to the Center for Disease Control and Prevention (CDC), the average human life expectancy is 78.8 years. Specifically, 3.2 million deaths are reported yearly due to heart disease, cancer, Alzheimer's disease, diabetes, and COVID-19. Diagnosing the disease is mandatory in the current way of living to avoid unfortunate deaths and maintain average life expectancy. CMOS image sensor (CIS) became a prominent technology in assisting the monitoring and clinical diagnosis devices to treat diseases in the medical domain. To address the significance of CMOS image 'sensors' usage in disease diagnosis systems, this paper focuses on the CIS incorporated disease diagnosis systems related to vital organs of the human body like the heart, lungs, brain, eyes, intestines, bones, skin, blood, and bacteria cells causing diseases. This literature survey's main objective is to evaluate the 'systems' capabilities and highlight the most potent ones with advantages, disadvantages, and accuracy, that are used in disease diagnosis. This systematic review used PRISMA workflow for study selection methodology, and the parameter-based evaluation is performed on disease diagnosis systems related to the human body's organs. The corresponding CIS models used in systems are mapped organ-wise, and the data collected over the last decade are tabulated.

Source: Sensors

DOI: 10.3390/s21062098

Authors: Suparshya Babu Sukhavasi, Susrutha Babu Sukhavasi, Khaled Elleithy, Shakour Abuzneid, Abdelrahman Elleithy

Institutions: University of Bridgeport, William Paterson University

Language: English

Topic: CCD and CMOS Imaging Sensors

Subfield: Electrical and Electronic Engineering

Field: Engineering

Domain: Physical Sciences

SDG: Good health and well-being

Open Access status: gold

Estimated APC paid: $2,376