ReviewSensors (Basel, Switzerland)2026
Recent Progress in Optical Frequency-Domain Reflectometry: Performance Enhancement, Emerging Applications and Machine Learning Integration.
Review in Sensors (Basel, Switzerland), 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.
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The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
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Authors and funding
10 authors.
Funding
Abstract
Optical frequency-domain reflectometry (OFDR) has become a core technology in distributed optical fiber sensing (DOFS) based on its ultra-high spatial resolution down to the sub-millimeter scale and excellent measurement sensitivity. However, its practical performance is significantly limited by various non-ideal factors, and existing reviews still lack systematic discussion on its latest research directions. This paper first introduces the fundamental principles and core error mechanisms of OFDR then summarizes key technological advances in its performance enhancement over the past five years. We further review its multi-scenario applications with a special focus on battery health monitoring and analyze the integration of machine learning in OFDR signal processing. Finally, we discuss the key challenges and future research prospects in this field.
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Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.