Abstract:
The use of smart healthcare systems to monitor cardiac parameters
has gained widespread popularity globally due to advancements in
technology. The Internet of Medical Things (IoMT) has become an
integral part of modern healthcare by facilitating the efficient
monitoring of vital signs through advanced sensors. Heart rate
variability (HRV) parameters, which provide valuable insights into a
patient's condition, are now a crucial aspect of healthcare
applications. Among the innovative solutions available, fiber Bragg
grating (FBG) based optical sensors have emerged as a promising
technology for continuous monitoring of various cardiac parameters.
Recent technological breakthroughs have made these sensors highly
accurate, enabling early detection and prediction of cardiac diseases,
significantly impacting lives. This article focuses on the design,
construction, and structural analysis of a passive optical FBG sensor
capable of acquiring real-time HRV parameters such as heart rate,
standard deviation of normal-to-normal intervals, root mean square
of successive differences, and percentage of successive NN intervals
differing by more than 50 ms. Additionally, advanced signal
processing algorithms and an IoT-based architectural design are
presented. An experimental study conducted in a laboratory involved
five subjects, three males and two females, and demonstrated
satisfactory performance with an error rate of less than 10%
compared to a standard HR monitor. This intelligent system can
detect arrhythmia, coronary heart disease, aortic diseases, and
strokes, thereby making a significant contribution to healthcare. The
combination of FBG sensors, IoT architecture, and advanced
technology holds immense potential for enhancing cardiac
monitoring and improving patient outcomes.
