Design and Verification of Integrated Circuitry for Real-Time Frailty Monitoring.

In this study, a new wireless electronic circuitry to analyze weight distribution was designed and incorporated into a chair to gather data related to common human postures (sitting and standing up). These common actions have a significant impact on various motor capabilities, including gait parameters, fall risk, and information on sarcopenia. The quality of these actions lacks an absolute measurement, and currently, there is no qualitative and objective metric for it. To address this, the designed analyzer introduces variables like Smoothness and Percussion to provide more information and objectify measurements in the assessment of stand-up/sit-down actions. Both the analyzer and the proposed variables offer additional information that can objectify assessments depending on the clinical eye of the physicians.

Non-Contact Thermal and Acoustic Sensors with Embedded Artificial Intelligence for Point-of-Care Diagnostics.

This work involves exploring non-invasive sensor technologies for data collection and preprocessing, specifically focusing on novel thermal calibration methods and assessing low-cost infrared radiation sensors for facial temperature analysis. Additionally, it investigates innovative approaches to analyzing acoustic signals for quantifying coughing episodes. The research integrates diverse data capture technologies to analyze them collectively, considering their temporal evolution and physical attributes, aiming to extract statistically significant relationships among various variables for valuable insights. The study delineates two distinct aspects: cough detection employing a microphone and a neural network, and thermal sensors employing a calibration curve to refine their output values, reducing errors within a specified temperature range. Regarding control units, the initial implementation with an ESP32 transitioned to a Raspberry Pi model 3B+ due to neural network integration issues. A comprehensive testing is conducted for both fever and cough detection, ensuring robustness and accuracy in each scenario. The subsequent work involves practical experimentation and interoperability tests, validating the proof of concept for each system component. Furthermore, this work assesses the technical specifications of the prototype developed in the preceding tasks. Real-time testing is performed for each symptom to evaluate the system's effectiveness. This research contributes to the advancement of non-invasive sensor technologies, with implications for healthcare applications such as remote health monitoring and early disease detection.

Enhanced refractometer for aqueous solutions based on perfluorinated polymer optical fibres.

The use of the new CYTOP (Cyclized Transparent Optical Polymer) fibres for the inscription of optical structures and the detection of different parameters has started to gain importance in the past decade. This work presents the design, simulation and manufacture of a CYTOP-based surrounding refractive index sensor for aqueous solutions, given its high sensitivity in the range 1.315 - 1.333 (at 1550 nm wavelength). The structure is based on a bent and polished fibre (in order to increase its sensitivity), the polished area being the surface on which a diffraction grating is inscribed with a femtosecond laser. The interaction of the field propagated by the fibre with the grating causes diffraction of certain orders towards the outside, depending, among other things, on the refractive index of the fluid. In addition to a maximum sensitivity of -208.8 nm/RIU and a remarkable insensitivity to temperature, it offers a spectral fingerprint of each sensed fluid.

A Dual-Wavelength Fiber Laser Sensor with Temperature and Strain Discrimination.

This work presents a dual-wavelength C-band erbium-doped fiber laser assisted by an artificial backscatter reflector. This fiber-based reflector, inscribed by femtosecond laser direct writing, was fabricated into a single mode fiber with a length of 32 mm. The dual-wavelength laser obtained, centered at 1527.7 nm and 1530.81 nm, showed an optical signal-to-noise ratio over 46 dB when pumped at 150 mW. Another feature of this laser was that the power difference between the two channels was just 0.02 dB, regardless of the pump power, resulting in a dual emission laser with high equalization. On the other hand, an output power level and a central wavelength instability as low as 0.3 dB and 0.01 nm were measured, in this order for both channels. Moreover, the threshold pump power was 40 mW. Finally, the performance of this dual-wavelength fiber laser enhanced with a random reflector for sensing applications was studied, achieving the simultaneous measurement of strain and temperature with sensitivities around 1 pm/µÎµ and 9.29 pm/°C, respectively.

Sensing Using Light: A Key Area of Sensors.

This invited featured paper offers a Doctrinal Conception of sensing using Light (SuL) as an "umbrella" in which any sensing approach using Light Sciences and Technologies can be easily included. The key requirements of a sensing system will be quickly introduced by using a bottom-up methodology. Thanks to this, it will be possible to get a general conception of a sensor using Light techniques and know some related issues, such as its main constituted parts and types. The case in which smartness is conferred to the device is also considered. A quick "flight" over 10 significant cases using different principles, techniques, and technologies to detect diverse measurands in various sector applications is offered to illustrate this general concept. After reading this paper, any sensing approach using Light Sciences and Technologies may be easily included under the umbrella: sensing using Light or photonic sensors (PS).

Recent Advances in Biomedical Photonic Sensors: A Focus on Optical-Fibre-Based Sensing.

In this invited review, we provide an overview of the recent advances in biomedical photonic sensors within the last five years. This review is focused on works using optical-fibre technology, employing diverse optical fibres, sensing techniques, and configurations applied in several medical fields. We identified technical innovations and advancements with increased implementations of optical-fibre sensors, multiparameter sensors, and control systems in real applications. Examples of outstanding optical-fibre sensor performances for physical and biochemical parameters are covered, including diverse sensing strategies and fibre-optical probes for integration into medical instruments such as catheters, needles, or endoscopes.

Optical Fiber Sensors by Direct Laser Processing: A Review.

The consolidation of laser micro/nano processing technologies has led to a continuous increase in the complexity of optical fiber sensors. This new avenue offers novel possibilities for advanced sensing in a wide set of application sectors and, especially in the industrial and medical fields. In this review, the most important transducing structures carried out by laser processing in optical fiber are shown. The work covers different types of fiber Bragg gratings with an emphasis in the direct-write technique and their most interesting inscription configurations. Along with gratings, cladding waveguide structures in optical fibers have reached notable importance in the development of new optical fiber transducers. That is why a detailed study is made of the different laser inscription configurations that can be adopted, as well as their current applications. Microcavities manufactured in optical fibers can be used as both optical transducer and hybrid structure to reach advanced soft-matter optical sensing approaches based on optofluidic concepts. These in-fiber cavities manufactured by femtosecond laser irradiation followed by chemical etching are promising tools for biophotonic devices. Finally, the enhanced Rayleigh backscattering fibers by femtosecond laser dots inscription are also discussed, as a consequence of the new sensing possibilities they enable.

Comparative Experimental Study of a High-Temperature Raman-Based Distributed Optical Fiber Sensor with Different Special Fibers.

An experimental study of a high temperature distributed optical fiber sensor based on Raman Optical-Time-Domain-Reflectometry (ROTDR) (up to 450 °C) and optical fibers with different coatings (polyimide/carbon, copper, aluminum and gold) is presented. Analysis of the distributed temperature sensor (DTS) measurements determined the most appropriate optical fiber to be used in high temperature industrial environment over long periods of time. To demonstrate the feasibility of this DTS for an industrial application, an optical cable was designed with the appropriate optical fiber and it was hermetically sealed to provide the required mechanical resistance and isolate the fiber from environmental degradations. This cable was used to measure temperature up to 360 °C of an industrial furnace during 7 days.

Identification of Human Pathological Mitral Chordae Tendineae Using Polarization-sensitive Optical Coherence Tomography.

Defects of the mitral valve complex imply heart malfunction. The chordae tendineae (CTs) are tendinous strands connecting the mitral and tricuspid valve leaflets to the papillary muscles. These CTs are composed of organized, wavy collagen bundles, making them a strongly birefringent material. Disorder of the collagen structure due to different diseases (rheumatic, degenerative) implies the loss or reduction of tissue birefringence able to be characterized with Polarization Sensitive Optical Coherence Tomography (PS-OCT). PS-OCT is used to discriminate healthy from diseased chords, as the latter must be excised and replaced in clinical conventional interventions. PS-OCT allows to quantify birefringence reduction in human CTs affected by degenerative and rheumatic pathologies. This tissue optical property is proposed as a diagnostic marker for the identification of degradation of tendinous chords to guide intraoperative mitral valve surgery.

Proposal of Brillouin optical frequency-domain reflectometry (BOFDR).

We demonstrate a Brillouin optical frequency-domain reflectometry (BOFDR) technique, which can measure the strain and/or temperature along an optical fiber with one-end access, by detecting the spontaneous Brillouin scattering from a sinusoidally modulated pump light. Compared to the Brillouin optical frequency-domain analysis (BOFDA), we show that BOFDR measurements are free from the distorting components related to acoustic wave modulation, thus simplifying data processing.

Identification of hypermucoviscous Klebsiella pneumoniae K1, K2, K54 and K57 capsular serotypes by Raman spectroscopy.

Antimicrobial resistance poses a significant challenge in modern medicine, affecting public health. Klebsiella pneumoniae infections compound this issue due to their broad range of infections and the emergence of multiple antibiotic resistance mechanisms. Efficient detection of its capsular serotypes is crucial for immediate patient treatment, epidemiological tracking and outbreak containment. Current methods have limitations that can delay interventions and increase the risk of morbidity and mortality. Raman spectroscopy is a promising alternative to identify capsular serotypes in hypermucoviscous K. pneumoniae isolates. It provides rapid and in situ measurements with minimal sample preparation. Moreover, its combination with machine learning tools demonstrates high accuracy and reproducibility. This study analyzed the viability of combining Raman spectroscopy with one-dimensional convolutional neural networks (1-D CNN) to classify four capsular serotypes of hypermucoviscous K. pneumoniae: K1, K2, K54 and K57. Our approach involved identifying the most relevant Raman features for classification to prevent overfitting in the training models. Simplifying the dataset to essential information maintains accuracy and reduces computational costs and training time. Capsular serotypes were classified with 96 % accuracy using less than 30 Raman features out of 2400 contained in each spectrum. To validate our methodology, we expanded the dataset to include both hypermucoviscous and non-mucoid isolates and distinguished between them. This resulted in an accuracy rate of 94 %. The results obtained have significant potential for practical healthcare applications, especially for enabling the prompt prescription of the appropriate antibiotic treatment against infections.

LAM Test: A New Cognitive Marker for Early Detection in Preclinical Alzheimer's Disease.

Background: With the arrival of disease-modifying treatments, it is mandatory to find new cognitive markers that are sensitive to Alzheimer's disease (AD) pathology in preclinical stages. Objective: To determine the utility of a newly developed Learning and Associative Memory face test: LAM test. This study examined the relationship between AD cerebrospinal fluid (CSF) biomarkers and performance on LAM test, and assessed its potential clinical applicability to detect subtle changes in cognitively healthy subjects at risk for AD. Methods: We studied eighty cognitively healthy volunteers from the Valdecilla cohort. 61% were women and the mean age was 67.34 years (±6.416). All participants underwent a lumbar puncture for determination of CSF biomarkers and an extensive neuropsychological assessment, including performance on learning and associative memory indices of the LAM-test after 30 min and after 1 week, and two classic word lists to assess verbal episodic memory: the Rey Auditory Verbal Learning Test (RAVLT) and the Free and Cued Selective Reminding Test (FCSRT). We analyzed cognitive performance according to amyloid status (A+ versus A-) and to ATN model (A-T-N-; A+T-N-; A+T+N-/A+T+N+). Results: Performance on the LAM-test was significantly correlated with CSF Aß ratio. A+ participants performed worse on both learning (mean difference = 2.19, p = 0.002) and memory LAM measures than A- (mean difference = 2.19, p = 0.004). A decline in performance was observed along the Alzheimer's continuum, with significant differences between ATN groups. Conclusions: Our findings suggest that LAM test could be a useful tool for the early detection of subjects within the AD continuum, outperforming classical memory tests.

Application of remote power-by-light switching in a simplified BOTDA sensor network.

We propose and demonstrate the use of spatial multiplexing as a means to reduce the costs of distributed sensing networks. We propose a new scheme in which remote power-by-light switching is deployed to scan multiple branches of a distributed sensing network based on Brillouin Optical Time Domain Analysis (BOTDA) sensors. A proof-of-concept system is assembled with two 5-km sensor fiber branches that are alternatively monitored using a fast remotely controlled and optically powered optical switch. The multiplexed distributed sensor fibers were located 10 km away from the interrogation unit and a Raman pump is used to remotely power the switch. Furthermore, the deployed BOTDA unit uses an alternative configuration that can lead to simplified setups.

Advanced Light Source Technologies for Photodynamic Therapy of Skin Cancer Lesions.

Photodynamic therapy (PDT) is an increasingly popular dermatological treatment not only used for life-threatening skin conditions and other tumors but also for cosmetic purposes. PDT has negligible effects on underlying functional structures, enabling tissue regeneration feasibility. PDT uses a photosensitizer (PS) and visible light to create cytotoxic reactive oxygen species, which can damage cellular organelles and trigger cell death. The foundations of modern photodynamic therapy began in the late 19th and early 20th centuries, and in recent times, it has gained more attention due to the development of new sources and PSs. This review focuses on the latest advancements in light technology for PDT in treating skin cancer lesions. It discusses recent research and developments in light-emitting technologies, their potential benefits and drawbacks, and their implications for clinical practice. Finally, this review summarizes key findings and discusses their implications for the use of PDT in skin cancer treatment, highlighting the limitations of current approaches and providing insights into future research directions to improve both the efficacy and safety of PDT. This review aims to provide a comprehensive understanding of PDT for skin cancer treatment, covering various aspects ranging from the underlying mechanisms to the latest technological advancements in the field.

Delocalized Electric Field Enhancement through Near-Infrared Quasi-BIC Modes in a Hollow Cuboid Metasurface.

The two main problems of dielectric metasurfaces for sensing and spectroscopy based on electromagnetic field enhancement are that resonances are mainly localized inside the resonator volume and that experimental Q-factors are very limited. To address these issues, a novel dielectric metasurface supporting delocalized modes based on quasi-bound states in the continuum (quasi-BICs) is proposed and theoretically demonstrated. The metasurface comprises a periodic array of silicon hollow nanocuboids patterned on a glass substrate. The resonances stem from the excitation of symmetry-protected quasi-BIC modes, which are accessed by perturbing the arrangement of the nanocuboid holes. Thanks to the variation of the unit cell with a cluster of four hollow nanocuboids, polarization-insensitive, delocalized modes with ultra-high Q-factor are produced. In addition, the demonstrated electric field enhancements are very high (103-104). This work opens new research avenues in optical sensing and advanced spectroscopy, e.g., surface-enhanced Raman spectroscopy.

Polarisation-independent ultrafast laser selective etching processing in fused silica.

In fused silica, ultrafast laser assisted etching enables high chemical etching rates (>300 µm h-1) by setting a light polarisation linear and perpendicular to the beam writing direction. However, for many non-planar surfaces and 3D structures, dynamic polarisation control is difficult or not yet possible to implement. In this contribution, we identify a laser inscription regime in which high etching rates are accomplished independently of the light polarisation. In this regime (<15 pulses per µm), we measure etching rates ∼300 µm h-1 (4 hours in NaOH) including femtosecond-pulse energies corresponding to type II modifications. Few pulse inscriptions show a low degree of anisotropy as compared to higher number of pulses, thus enabling the polarisation insensitivity whose mechanisms are discussed. To demonstrate the capabilities of the processing, we fabricate curved and square-wave microchannels together with a complex 3D geometrical structure (stellated octahedron) containing an inter-plane arrangement with challenging angles (45°), which are difficult to achieve even employing dynamic polarisation control.

Automatic classification of Candida species using Raman spectroscopy and machine learning.

One of the problems that most affect hospitals is infections by pathogenic microorganisms. Rapid identification and adequate, timely treatment can avoid fatal consequences and the development of antibiotic resistance, so it is crucial to use fast, reliable, and not too laborious techniques to obtain quick results. Raman spectroscopy has proven to be a powerful tool for molecular analysis, meeting these requirements better than traditional techniques. In this work, we have used Raman spectroscopy combined with machine learning algorithms to explore the automatic identification of eleven species of the genus Candida, the most common cause of fungal infections worldwide. The Raman spectra were obtained from more than 220 different measurements of dried drops from pure cultures of each Candida species using a Raman Confocal Microscope with a 532 nm laser excitation source. After developing a spectral preprocessing methodology, a study of the quality and variability of the measured spectra at the isolate and species level, and the spectral features contributing to inter-class variations, showed the potential to discriminate between those pathogenic yeasts. Several machine learning and deep learning algorithms were trained using hyperparameter optimization techniques to find the best possible classifier for this spectral data, in terms of accuracy and lowest possible overfitting. We found that a one-dimensional Convolutional Neural Network (1-D CNN) could achieve above 80 % overall accuracy for the eleven classes spectral dataset, with good generalization capabilities.

Comparison of Mg/Ca concentration series from Patella depressa limpet shells using CF-LIBS and LA-ICP-MS.

The elemental composition of marine mollusk shells can offer valuable information about environmental conditions experienced by a mollusk during its lifespan. Previous studies have shown significant correlations between Mg/Ca concentration ratios measured on biogenic carbonate of mollusk shells and sea surface temperature (SST). Here we propose the use of Laser-Induced Breakdown Spectroscopy (LIBS) and the validation of the Calibration-Free LIBS (CF-LIBS) approach for the rapid measurement and estimation of Mg/Ca molar concentration profiles within Patella depressa Pennant, 1777 limpet shells. To achieve these objectives, results derived from CF-LIBS methodology are compared with those obtained from an established analytical technique for this purpose, such as Laser Ablation Inductively Coupled Plasma Mass Spectrometry (LA-ICP-MS). Concentration series obtained with both methodologies show defined temporal patterns and reflect the season-of-capture in each specimen. The results evidence a significant correlation (R2 = 0.63-0.81) between CF-LIBS and LA-ICP-MS Mg/Ca molar concentration profiles within four live-collected P. depressa shells. Averaged error for the molar concentration estimated with CF-LIBS was lower than 10% in every specimen. The comparison between the results obtained from two techniques used in this study has allowed us to demonstrate for the first time that Mg/Ca molar concentration measured in biogenic carbonates were accurately inferred using CF-LIBS technique. The CF-LIBS approach validation represents great potential for the rapid and large-scale paleoenvironmental and archaeological analysis of this mollusk species, which is frequently found in archaeological sites.

Normalization of laser-induced breakdown spectroscopy spectra using a plastic optical fiber light collector and acoustic sensor device.

To estimate the acoustic plasma energy in laser-induced breakdown spectroscopy (LIBS) experiments, a light collecting and acoustic sensing device based on a coil of plastic optical fiber (POF) is proposed. The speckle perturbation induced by the plasma acoustic energy was monitored using a CCD camera placed at the end of a coil of multimode POF and processed with an intraimage contrast ratio method. The results were successfully verified with the acoustic energy measured by a reference microphone. The proposed device is useful for normalizing LIBS spectra, enabling a better estimation of the sample's chemical composition.

Photonic Microfluidic Technologies for Phytoplankton Research.

Phytoplankton is a crucial component for the correct functioning of different ecosystems, climate regulation and carbon reduction. Being at least a quarter of the biomass of the world's vegetation, they produce approximately 50% of atmospheric O2 and remove nearly a third of the anthropogenic carbon released into the atmosphere through photosynthesis. In addition, they support directly or indirectly all the animals of the ocean and freshwater ecosystems, being the base of the food web. The importance of their measurement and identification has increased in the last years, becoming an essential consideration for marine management. The gold standard process used to identify and quantify phytoplankton is manual sample collection and microscopy-based identification, which is a tedious and time-consuming task and requires highly trained professionals. Microfluidic Lab-on-a-Chip technology represents a potential technical solution for environmental monitoring, for example, in situ quantifying toxic phytoplankton. Its main advantages are miniaturisation, portability, reduced reagent/sample consumption and cost reduction. In particular, photonic microfluidic chips that rely on optical sensing have emerged as powerful tools that can be used to identify and analyse phytoplankton with high specificity, sensitivity and throughput. In this review, we focus on recent advances in photonic microfluidic technologies for phytoplankton research. Different optical properties of phytoplankton, fabrication and sensing technologies will be reviewed. To conclude, current challenges and possible future directions will be discussed.