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The results presented here show for the first time the experimental demonstration of the fabrication of lossy mode resonance (LMR) devices based on perovskite coatings deposited on planar waveguides. Perovskite thin films have been obtained by means of the spin coating technique and their presence was confirmed by ellipsometry, scanning electron microscopy, and X-ray diffraction testing. The LMRs can be generated in a wide wavelength range and the experimental results agree with the theoretical simulations. Overall, this study highlights the potential of perovskite thin films for the development of novel LMR-based devices that can be used for environmental monitoring, industrial sensing, and gas detection, among other applications.

Multiple mode resonance shifts in tilted fiber Bragg gratings (TFBGs) are used to simultaneously measure the thickness and the refractive index of TiO2 thin films formed by Atomic Layer Deposition (ALD) on optical fibers. This is achieved by comparing the experimental wavelength shifts of 8 TFBG resonances during the deposition process with simulated shifts from a range of thicknesses (T) and values of the real part of the refractive index (n). The minimization of an error function computed for each (n, T) pair then provides a solution for the thickness and refractive index of the deposited film and, a posteriori, to verify the deposition rate throughout the process from the time evolution of the wavelength shift data. Validations of the results were carried out with a conventional ellipsometer on flat witness samples deposited simultaneously with the fiber and with scanning electron measurements on cut pieces of the fiber itself. The final values obtained by the TFBG (n = 2.25, final thickness of 185 nm) were both within 4% of the validation measurements. This approach provides a method to measure the formation of nanoscale dielectric coatings on fibers in situ for applications that require precise thicknesses and refractive indices, such as the optical fiber sensor field. Furthermore, the TFBG can also be used as a process monitor for deposition on other substrates for deposition methods that produce uniform coatings on dissimilar shaped substrates, such as ALD.

Abstract In this work, measuring capabilities of a Sagnac Interferometer-based Distributed Optical Fiber Sensor (DOFS) system are demonstrated by comparing its results to a conventional amplitude-based Distributed Acoustic Sensing (DAS) system. Through a set of three different experiments, it was demonstrated that both sensing systems can detect and locate dynamical deformation along the fiber, in addition to determining its frequency components. The coherent amplitude-based DAS presented a lower background noise. In contrast, even though the Sagnac interferometry-based system presented low-frequency noise in the measurements, it is less susceptible to harmonic distortion for higher amplitude deformations since its sensing principles rely on the measurement of the accumulated phase rather than the amplitude of the backscattered signal purely. Accordingly, the Sagnac interferometry-based system arises as a promising and rather accessible topology for a DOFS implementation.

Abstract This paper describes the automation of a forearm prosthesis using the signal collected by a Fiber Bragg Grating (FBG) sensor. The FBG sensor is applied to one subject's forearm to measure the deformation as a result of the index and middle fingers when moved individually. It is possible to control a one joint model prosthesis allied to a compliant hand mechanism through signal analyses. Each finger movement has its features, such as its amplitude, which opens the possibility of using those to control different parts of the prosthesis, joint rotation by the middle finger, and compliant hand movement by the index finger. This paper presents results regarding prosthesis assembling, Hypertext Transfer Protocol (HTTP) communication latency between prosthesis and computer and tests with pre-acquired and processed FBG signal data. The prosthesis wrist rotation movement is related to the middle finger signal, and its compliant mechanism actuation is due to index finger signal. The communication between prosthesis and the computer had a mean latency of 140 ms and a standard deviation of 18 ms. The results demonstrate the potential for using the sensor system and automated prosthesis in other applications involving real-time forearm sensing, multi-finger signal analysis, and prosthetic movement.

Machine learning (ML) and deep learning (DL) have achieved great success in different tasks. These include computer vision, image segmentation, natural language processing, predicting classification, evaluating time series, and predicting values based on a series of variables. As artificial intelligence progresses, new techniques are being applied to areas like optical spectroscopy and its uses in specific fields, such as the agrifood industry. The performance of ML and DL techniques generally improves with the amount of data available. However, it is not always possible to obtain all the necessary data for creating a robust dataset. In the particular case of agrifood applications, dataset collection is generally constrained to specific periods. Weather conditions can also reduce the possibility to cover the entire range of classifications with the consequent generation of imbalanced datasets. To address this issue, data augmentation (DA) techniques are employed to expand the dataset by adding slightly modified copies of existing data. This leads to a dataset that includes values from laboratory tests, as well as a collection of synthetic data based on the real data. This review work will present the application of DA techniques to optical spectroscopy datasets obtained from real agrifood industry applications. The reviewed methods will describe the use of simple DA techniques, such as duplicating samples with slight changes, as well as the utilization of more complex algorithms based on deep learning generative adversarial networks (GANs), and semi-supervised generative adversarial networks (SGANs).

The use of planar waveguides has recently shown great success in the field of optical sensors based on the Lossy Mode Resonance (LMR) phenomenon. The properties of Graphene Oxide (GO) have been widely exploited in various sectors of science and technology, with promising results for gas sensing applications. This work combines both, the LMR-based sensing technology on planar waveguides and the use of a GO thin film as a sensitive coating, to monitor ethanol, water, and acetone. Experimental results on the fabrication and performance of the sensor are presented. The obtained results showed a sensitivity of 3.1, 2.0, and 0.6 pm/ppm for ethanol, water, and acetone respectively, with a linearity factor R2 > 0.95 in all cases.

Pollution in cities induces harmful effects on human health, which continuously increases the global demand of gas sensors for air quality control and monitoring. In the same manner, the industrial sector requests new gas sensors for their productive processes. Moreover, the association between exhaled gases and a wide range of diseases or health conditions opens the door for new diagnostic applications. The large number of applications for gas sensors has permitted the development of multiple sensing technologies. Among them, optical fiber gas sensors enable their utilization in remote locations, confined spaces or hostile environments as well as corrosive or explosive atmospheres. Particularly, Lossy Mode Resonance (LMR)-based optical fiber sensors employ the traditional metal oxides used for gas sensing purposes for the generation of the resonances. Some research has been conducted on the development of LMR-based optical fiber gas sensors; however, they have not been fully exploited yet and offer optimal possibilities for improvement. This review gives the reader a complete overview of the works focused on the utilization of LMR-based optical fiber sensors for gas sensing applications, summarizing the materials used for the development of these sensors as well as the fabrication procedures and the performance of these devices.

A comprehensive review of optical biosensors for the detection of biomarkers associated with rheumatoid arthritis (RA) is presented here, including microRNAs (miRNAs), C-reactive protein (CRP), rheumatoid factor (RF), anti-citrullinated protein antibodies (ACPA), interleukin-6 (IL-6) and histidine, which are biomarkers that enable RA detection and/or monitoring. An overview of the different optical biosensors (based on fluorescence, plasmon resonances, interferometry, surface-enhanced Raman spectroscopy (SERS) among other optical techniques) used to detect these biomarkers is given, describing their performance and main characteristics (limit of detection (LOD) and dynamic range), as well as the connection between the respective biomarker and rheumatoid arthritis. It has been observed that the relationship between the corresponding biomarker and rheumatoid arthritis tends to be obviated most of the time when explaining the mechanism of the optical biosensor, which forces the researcher to look for further information about the biomarker. This review work attempts to establish a clear association between optical sensors and rheumatoid arthritis biomarkers as well as to be an easy-to-use tool for the researchers working in this field.

This work presents a first approach to the utilization of Lossy Mode Resonance (LMR) based optical fiber sensors for gas detection. The optical sensor is based on a SnO2 thin-film fabricated onto the core of cladding removed multimode fibers (MMF). The time response of the device to four different gases (NH3, NO, CO2 and O2) was monitored obtaining the best sensitivity for NO whereas the response to NH3 revealed the best repeatability.

Optical fiber sensors (OFS) have attracted increasing attention due to their benefits over [...]