Decade of advancements in light–matter interaction-based optical fiber biosensing: innovations, challenges, and future directions
Optical fiber biosensors (OFBs) have emerged as a versatile and highly sensitive technology, with various implementations such as fiber Bragg gratings, interferometric techniques, and D-shaped fibers, particularly those that leverage surface plasmon resonance effects. Classifying these sensors based on target analytes underscores their adaptability and broad range of applications. Despite significant progress, challenges such as repeatability, multiplexing, and data interpretation remain key barriers to widespread practical adoption. To address these limitations, recent innovations focus on artificial intelligence algorithms for enhanced data processing, as well as novel materials that improve sensitivity and the repeatability of functionalization. The integration of label-free detection, enabled by surface functionalization, further enhances biosensing capabilities. Moreover, the unique combination of small fiber dimensions, low sample-volume detection, and multiplexing capabilities positions OFBs as a promising alternative to existing commercial solutions. As demand for precise, real-time, and multi-analyte sensing grows, OFBs are poised to become a cornerstone technology, particularly in the context of Healthcare 5.0, where personalized and intelligent diagnostics are essential to advancing medical applications. We summarize advances in OFBs over the past decade, highlighting their functionalities and applications across multiple fields, including medical diagnostics, environmental monitoring, and industrial process control. Finally, we explore future directions for this field. Reported detection limits below 1 femtomolar (10−15 mol/L), selectivity ratios exceeding 100:1, and operational stability over 60 days illustrate ongoing progress in overcoming challenges related to sensitivity, specificity, and long-term performance. The integration of the Internet of Things will enable seamless communication with external devices. Innovations in material science can further improve sensitivity and repeatability, allowing probing in low-sample environments and supporting new designs with label-free and multiplexing capabilities. Continued progress in these areas will pave the way for large-scale production and commercialization of OFBs.
Optically active nanoparticles-embedded optical fiber for random fiber laser distributed sensor
This paper presents the development of a multifunctional photonic device using nanoparticle (NP)-doped fiber as an optical amplification medium and distributed sensing element simultaneously. The proposed system comprises a linear cavity Random Fiber Laser (RFL) in which the NP-doped fiber is used as an amplification medium due to the erbium ions in the NP composition and a distributed cavity due to the enhanced Rayleigh scattering of the fiber. In this case, the RFL is employed as a distributed sensor by means of localized changes on the optical transmission and reflection signals when temperature and strain are applied along the NP-doped fiber. The proposed RFL is analyzed in terms of stability and configurations. In this case, the RFL demonstrated a maximum output power of around 17 mW with a power stability demonstrated by 0.07 nm variations in wavelength stability tests. The RFL distributed sensor validation, and the sensor system was submitted to simultaneous variation of temperature, strain, and location of the mechanical disturbance, where the Random Forest machine learning method was employed for the simultaneous assessment of all three parameters. The results show high accuracy of the sensor system, where relative errors of 0.02%, 2.0%, and 5.3% were found for temperature, strain, and location of strain application along the laser cavity, respectively. Therefore, the proposed RFL distributed sensor is a feasible solution for dynamic monitoring of different physical parameters, which can close the gap between the distributed optical fiber sensors and applications that require lower cost and high portability.
3 × 3 interferometers for acoustic detection: Experimental analysis and comparison
This paper presents the development, application and comparison of interferometers using 3 × 3 configuration for acoustic assessment. The comparison is performed considering Michelson interferometer (MI) and Sagnac interferometer (SI) under frequency sweep from 250 Hz and 16 000 Hz. The results indicated higher signal-to-noise ratio (around 65 dB and 75 dB, for MI and SI, respectively) and sensitivity of the SI approach (4.68 ± 0.91 deg/Pa) when compared with MI (1.22 ± 0.74 deg/Pa). Then, the pulse detection tests are made in different configurations for the interferometers to verify the acoustic response of a well-known aluminum plate sample. Considering the MI, the tested configurations are both arms in the same side of the sample, arms at opposite sides of the sample and only one arm in contact with the sample. Similarly, for the SI, the configurations with the interferometer in contact and without contact with the sample are compared. In this test, both interferometers are able of detecting the resonance frequency (around 9400 Hz), where the MI configuration with one arm at each side of the sample is the one with the highest signal variation (392.10 ± 134.56 deg) among the tested configurations in MI. In addition, the SI in contact with the sample presented the highest signal variation (59.83 ± 21.10 deg) among the ones tested. Therefore, both approaches resulted in highly sensitive sensors able of detecting acoustic signals in a wide frequency range, which enable a myriad of applications in environmental sensing, acoustic emission detection for materials characterization and structural health monitoring
Stability enhancement in random fiber lasers using passive feedback and NP-doped fibers
This paper presents an experimental investigation of the spectral and power stability of a random fiber laser (RFL) based on nanoparticle (NP)-doped fiber, under three different passive optical feedback configurations: retroreflector, Faraday rotator, and fiber Bragg grating (FBG). The NP-doped fiber offers enhanced Rayleigh scattering and intrinsic gain, allowing distributed feedback and laser generation. Spectral analysis revealed that the FBG configuration presented the highest spectral stability, with a 91.25% reduction in wavelength variation compared to the retroreflector. The Faraday rotator also contributed to the spectral stability, with a 37.5% reduction. Regarding power stability, the Faraday rotator presented the best performance, with only 1.62% variation, while the FBG provided the highest output power (8.13 dBm), with a 6.1% variation. The retroreflector configuration demonstrated the worst performance in both spectral and power stability. These results confirm that the combination of NP-doped fibers and well-selected passive feedback elements allows the development of more stable and coherent RFLs, expanding their potential for application in sensing, telecommunications, and optical fiber devices.
AI-empowered, low-cost and portable optical fiber sensor system for distributed monitoring and shape reconstruction in UAV structures
This paper presents the development and application of a low-cost distributed optical fiber sensor for the continuous monitoring of force and shape in Unmanned Aerial Vehicles (UAVs) wings. The sensor system includes nanoparticle-doped optical fibers with enhanced backscattering, which lead to higher sensitivity and spatial resolution in transmission–reflection analysis (TRA) systems. The acquired optical signals are
fed into a neural network that provides the force distribution along the wing surface area. The results indicated the feasibility of the proposed system in which the RMSEs of 0.46 N, 13.1 mm and 5.2 mm were found for the estimation of force amplitude, location in x-axis and y-axis, respectively. Then, the distributed displacement sensing for wing shape reconstruction is evaluated and demonstrated a high accuracy in the 3D
shape reconstruction with relative errors as small as 0.21%. Thus, the proposed system is a solution with the combination of low-cost, high resolution and high accuracy for the first time in aircraft monitoring distributed systems. Therefore, the proposed AI-enabled sensor system provides a low-cost distributed optical fiber sensor that can be directly integrated into the control unit of UAV due to the simplicity of the signal acquisition process.
Comprehensive review of distributed acoustic sensing technology: principles, configurations, applications and emerging trends
In recent years, distributed acoustic sensing (DAS) has been a preferred choice in many practical applications due to its versatility and the possibility of using existing infrastructure. This paper presents a thorough review on DAS technology of all aspects of such sensing system. The review includes a market overview demonstrating the increasing trend in DAS market size (projected to USD 7.8 billion by 2030), focused on implementation in different fields. Then, the operation principles, fundamentals and theoretical background of the DAS systems are analyzed and compared in terms of different approaches. In addition, the myriads of DAS applications proposed in recent years are reviewed. Thereafter, current limitations and drawbacks of DAS are discussed and emerging technologies to address such drawbacks are analyzed in terms of benefits and future challenges for the next generation of DAS technology. This review paper’s unique value is to comprehensively cover all aspects of DAS technology, from its theoretical basis and first laboratory demonstrations to practical implementation covering tens of kilometers. Such review can be used as a roadmap for DAS applications and to understand the application and implementation of ϕ-OTDR systems with critical perspective of the new possibilities of the next generation of DAS systems.
POF-Based Sensor Device for Assessment of Human–Robot Interaction Forces
This article presents the development and validation of a polymer optical fiber (POF) sensor system for quantifying human–robot interaction (HRI) torque in knee exoskeletons. The device consists of a four-channel POF array embedded in a shank cuff that provides online torque signals during gait tasks. The channels were calibrated against a reference load cell, yielding dynamic force RMSE in the range 3.93–5.14 N and correlation between 0.88 and 0.94. In quasi-static interface tests with six participants, the reconstructed POF torque tracked full torque transfer through the cuff, with RMSE of 1.4–1.8 N ⋅ m for sinusoidal and triangular actuator profiles. In treadmill trials, the POF-based torque was used as a reference to assess disturbance observer (DOB) techniques. All observers reproduced the main interaction-torque patterns but showed attenuation and temporal shifts with respect to the POF reference, with RMSE between 0.8 and 1.3 N ⋅ m. These results indicate that the POF cuff delivers a consistent interaction-torque signal at the interface and can serve as a practical reference when analyzing bandwidth and robustness limitations of observer-based estimators.
Nanoparticle-doped fibers combined with machine learning methods for 3-dimensional shape reconstruction systems
The development of nanoparticle (NP) doped optical fibers provides new possibilities in distributed sensing and provides important advantages in spatially distributed system due to the tailoring of the backscattering signal, which enables the development of new approaches in shape reconstruction systems. For this reason, this paper presents the application of a distributed sensor system based on optical frequency domain reflectometry (OFDR) using the NP-doped optical fiber as the sensing medium in which there is an increase in sensitivity and spatial resolution due to the increase in backscaterred signal. The fiber is embedded in a rubber strip to increase the measurement range and the sensor robustness due to the nitrile rubber flexibility, since the rubber can provide strain transfer to the optical fiber, leading to higher strain limits, which can withstand the complex 3D loadings for the shape reconstruction. The sensor system is tested under different mechanical loadings conditions and the contribution of this work is a readily available sensing system using specialty optical fiber with high spatial resolution for 3D shape sensing approaches. The results indicate the feasibility of the proposed approach for shape sensing monitoring through a determination coefficient (R2) higher than 0.99 for all cases. In addition, the strain distribution along the fiber was also estimated for all loading conditions as well as the combination of them with an RMSE of around 1 mm considering the amplitude estimation of all loadings. The 3D shape reconstruction resulted in a mean error of around 2.0% considering all 3 axes of the cartesian plane. Therefore, the proposed sensor system is a feasible option for shape sensing with sub-centimeter spatial resolution and high accuracy using the NP-doped optical fiber as enhanced backscattered medium.
High-Resolution Distributed Optical Fiber Sensor for Multiparameter Sensing, Local Inhomogeneity Detection, and Poisson’s Ratio Estimation in Concrete Structures
The structural health monitoring (SHM) concept emerges as an important approach for the continuous assessment of civil infrastructure, directly aligning with the demands for sustainability, safety, and smart devices in modern urbanization and smart cities. Addressing these demands, this article presents the development and validation of a multiparameter distributed optical fiber sensor (DOFS) for the simultaneous measurement of temperature, longitudinal strain, and transverse strain with subcentimeter-scale spatial resolution. Based on optical frequency domain reflectometry (OFDR), the system utilizes a geometrically configured commercial fiber to act as a continuous spatial rosette. The sensor was characterized, achieving linear sensitivities of 0.1253 GHz/ μϵ and 1.251 GHz/°C, with a limit of detection of 0.1 μϵ and 0.1 ∘ C and a spatial resolution of 2.5 mm. Application tests on concrete cylinders under compressive loading demonstrated the system’s capability to decouple multiaxial strain components while inherently compensating for thermal cross-sensitivity, maintaining a stable temperature variation of 0.3 ∘ C during testing. The decomposed experimental strain profiles were validated against a numerical finite element analysis (FEA). In contrast with the idealized numerical model, the distributed sensor successfully mapped real-world localized strain concentrations and inherent material inhomogeneities, registering spatial strain variations of up to 619.22 μϵ (longitudinal) and 113.75 μϵ (transverse) near the elastic limit (160 kN). By aggregating the synchronized multitest data, the Poisson’s ratio of the concrete was estimated at 0.16. Furthermore, the system captured the complete spatiotemporal evolution of damage, precisely identifying the macroscopic rupture region. Finally, the results demonstrate that the proposed device provides a robust, single-fiber solution for 2-D strain field mapping and multiparameter SHM, filling key technological gaps for future smart infrastructure applications.
Numerical investigation of a Sagnac-based interferometer for liquid analyte sensing in the terahertz gap
Real-time chemical sensing is critical for industrial quality control and safety. However, most terahertz (THz) photonic crystal fiber (PCF) sensors remain limited to material characterization rather than practical transductors. Here, we introduce Sagnac interferometry to the terahertz domain as a transduction platform for sensing, demonstrating a numerical proof-of-concept liquid sensor using a highly birefringent porous-core photonic crystal fiber infiltrated with an ethanol–water mixture analyte as a proof-of-concept. By translating birefringence modulation into spectral shifts, our simulations show that the sensor achieves sensitivities up to 549 MHz per % v/v, with excellent polynomial correlation ( ) across a wide concentration range, when operating in the 0.56–0.70 THz band. This work establishes a versatile and straightforward interferometric platform in the THz gap, highlighting the potential of this interferometric approach for future chemical and biological applications in the terahertz range.