Litcius/Paper detail

Wearable Fiber Bragg Grating Sensors for Physiological Signal and Body Motion Monitoring: A Review

Feng Zhang, Yupeng Hao, Aofei Tian, Zhengbao Yang, Bo Zhang, Toshio Fukuda, Chaoyang Shi

2025IEEE Transactions on Instrumentation and Measurement12 citationsDOI

Abstract

Wearable sensors play a crucial role in real-time physiological parameters and body motion monitoring, enabling early detection and prevention of potential health issues. However, conventional electrical sensors are susceptible to electromagnetic interference (EMI), limiting their application in magnetic resonance imaging, electrosurgery, and humid environments. Optical wearable devices based on Fiber Bragg Gratings (FBG) offer distinct advantages such as miniaturization, immunity to EMI, high sensitivity, and multiplexing capabilities, making them promising for healthcare applications. Nevertheless, the FBG sensor faces challenges such as susceptibility to breakage and cross-sensitivity to temperature and multiple strain signals, creating obstacles in expanding strain monitoring range, reducing monitoring errors, and improving wear resistance. This review comprehensively introduces the latest advancements, technical challenges, and potential solutions associated with wearable FBG sensing devices for detecting physiological signals and body motion, particularly emphasizing their applications in monitoring small-strain and large-strain body movements. This paper focuses on the sensing characteristics of FBG units in both soft and rigid substrate materials and tracks the advancement in sensing structure optimization for enhanced measurement capabilities. Future directions and opportunities for technological improvement in this field are also discussed.

Topics & Concepts

Fiber Bragg gratingWearable computerSIGNAL (programming language)PHOSFOSWearable technologyFiber optic sensorSignal processingMaterials scienceOptical fiberComputer scienceAcousticsPhysicsPlastic optical fiberEmbedded systemComputer hardwareTelecommunicationsDigital signal processingProgramming languageNon-Invasive Vital Sign Monitoring