학술논문

FBG Sensor Design and Analysis for Early Detection of Cancer
Document Type
Conference
Source
2024 11th International Conference on Computing for Sustainable Global Development (INDIACom) Computing for Sustainable Global Development (INDIACom), 2024 11th International Conference on. :843-849 Feb, 2024
Subject
Bioengineering
Communication, Networking and Broadcast Technologies
Components, Circuits, Devices and Systems
Computing and Processing
Engineering Profession
General Topics for Engineers
Geoscience
Photonics and Electrooptics
Power, Energy and Industry Applications
Robotics and Control Systems
Signal Processing and Analysis
Transportation
Temperature sensors
Temperature measurement
Q-factor
Temperature
Sensitivity
Current measurement
Optical fiber networks
FBG
Fiberoptic
SMF
modulation
OptiGrating
Blood cancer
MCF-7 cells
Hela cells
Language
Abstract
Several of the current procedures for detecting cancer, such as mammography, ultrasound, MRI, and biopsy, are either expensive, painful, intrusive, or have limitations in accuracy and sensitivity. As a result, there is a need for a simple, noninvasive, and cost-effective tool for detecting cancer at an early stage. Fiber Bragg grating (FBG) sensors offer a wide range of uses in primary care and biomedical applications for intelligent sensing. Furthermore, fiber-optic FBGs have several benefits that set them apart. The most noteworthy of these applications, of course, are incredibly valuable human health indicators such as blood pressure, heart rate, and body temperature. Temperature and blood pressure vary depending on a person’s physical, involuntary, nervous, and mental state. Therefore, measuring vital parameters, especially temperature can help in the early identification of symptoms of a disease. Research suggests that temperature variation is observed in cancerous cells (breast, cervix, and blood vessels). FBGs can be utilized as thermal sensors to measure temperature changes with great sensitivity and precision. FBG sensors also face some challenges, such as low signal-to-noise ratio, cross-sensitivity, and environmental interference. Therefore, optimizing the Q factor of FBG sensors is crucial for improving their performance and reliability for cancer identification. In the current study, an optimized FBG sensor was designed and simulated. The average Q-factor obtained in 244.26.