In-Loco Optical Spectroscopy through a Multiple Digital Lock-In on a Linear Charge-Coupled Device (CCD) Array.

Accurate and reliable measurements of optical properties are crucial for a wide range of industrial and commercial applications. However, external illumination fluctuations can often make these measurements challenging to obtain. This work proposes a new technique based on digital lock-in processing that enables the use of CCD spectrometers in optical spectroscopy applications, even in uncontrolled lighting conditions. This approach leverages digital lock-in processing, performed on each pixel of the spectrometer's CCD simultaneously, to mitigate the impact of external optical interferences. The effectiveness of this method is demonstrated by testing and recovering the spectrum of a yellow LED subjected to other light sources in outdoor conditions, corresponding to a Signal-to-Noise Ratio of -70.45 dB. Additionally, it was possible to demonstrate the method's applicability for the spectroscopic analysis of gold nanoparticles in outdoor conditions. These results suggest that the proposed technique can be helpful for a wide range of optical measurement techniques, even in challenging lighting conditions.

An Automated Machine Learning Approach for Real-Time Fault Detection and Diagnosis.

This work presents a novel Automated Machine Learning (AutoML) approach for Real-Time Fault Detection and Diagnosis (RT-FDD). The approach's particular characteristics are: it uses only data that are commonly available in industrial automation systems; it automates all ML processes without human intervention; a non-ML expert can deploy it; and it considers the behavior of cyclic sequential machines, combining discrete timed events and continuous variables as features. The capacity for fault detection is analyzed in two case studies, using data from a 3D machine simulation system with faulty and non-faulty conditions. The enhancement of the RT-FDD performance when the proposed approach is applied is proved with the Feature Importance, Confusion Matrix, and F1 Score analysis, reaching mean values of 85% and 100% in each case study. Finally, considering that faults are rare events, the sensitivity of the models to the number of faulty samples is analyzed.

Wavefront sensing using a liquid-filled photonic crystal fiber.

A novel wavefront sensor based on a microstructural array of waveguides is proposed. The method is based on the sensitivity in light-coupling efficiency to the wavefront gradient present at the entrance aperture of each waveguide in an array, and hence the amount of incident light that couples is influenced by wavefront aberrations. The concept is illustrated with wavefront measurements that have been performed using a liquid-filled photonic crystal fiber (LF-PCF) working as a coherent fiber bundle. The pros and cons of the LF-PCF based sensor are discussed.

Optimizing and Quantifying Gold Nanospheres Based on LSPR Label-Free Biosensor for Dengue Diagnosis.

The localized surface plasmon resonance (LSPR) due to light-particle interaction and its dependence on the surrounding medium have been widely manipulated for sensing applications. The sensing efficiency is governed by the refractive index-based sensitivity (ηRIS) and the full width half maximum (FWHM) of the LSPR spectra. Thereby, a sensor with high precision must possess both requisites: an effective ηRIS and a narrow FWHM of plasmon spectrum. Moreover, complex nanostructures are used for molecular sensing applications due to their good ηRIS values but without considering the wide-band nature of the LSPR spectrum, which decreases the detection limit of the plasmonic sensor. In this article, a novel, facile and label-free solution-based LSPR immunosensor was elaborated based upon LSPR features such as extinction spectrum and localized field enhancement. We used a 3D full-wave field analysis to evaluate the optical properties and to optimize the appropriate size of spherical-shaped gold nanoparticles (Au NPs). We found a change in Au NPs' radius from 5 nm to 50 nm, and an increase in spectral resonance peak depicted as a red-shift from 520 nm to 552 nm. Using this fact, important parameters that can be attributed to the LSPR sensor performance, namely the molecular sensitivity, FWHM, ηRIS, and figure of merit (FoM), were evaluated. Moreover, computational simulations were used to assess the optimized size (radius = 30 nm) of Au NPs with high FoM (2.3) and sharp FWHM (44 nm). On the evaluation of the platform as a label-free molecular sensor, Campbell's model was performed, indicating an effective peak shift in the adsorption of the dielectric layer around the Au NP surface. For practical realization, we present an LSPR sensor platform for the identification of dengue NS1 antigens. The results present the system's ability to identify dengue NS1 antigen concentrations with the limit of quantification measured to be 0.07 µg/mL (1.50 nM), evidence that the optimization approach used for the solution-based LSPR sensor provides a new paradigm for engineering immunosensor platforms.

Wavefront sensing with an axicon.

The use of a large apex-angle axicon for common-path interferometric wavefront sensing is proposed. The approach is a variant of point-diffraction interferometry bearing similarities to pyramidal wavefront sensing. A theoretical basis for wavefront sensing with an axicon is developed, and the outcomes of numerical simulations are compared to experimental results obtained with spherical and cylindrical ophthalmic trial lenses. It is confirmed that the axicon can be used for wavefront sensing, although its refraction may ultimately complicate and limit its operational range.

Absence of an integrated Stiles-Crawford function for coherent light.

The Stiles-Crawford effect that relates visibility to pupil point is typically expressed by a Gaussian function at any given wavelength of illumination. The pupil location of the maximum and the width of this function refer, respectively, to the pointing and waveguide properties of individual cone photoreceptors. In vision simulations, the function is integrated across the pupil when estimating effective retinal images, but the validity of this approach has still not been unequivocally confirmed. Indeed, aberrations and coherence properties may significantly alter not only the amplitude but also the phase distribution of the light at the retina in a way that differs fundamentally from that of the Maxwellian illumination configuration used when characterizing the effect. Here, we report on an experimental comparison of the traditionally determined Stiles-Crawford function and the equivalent for annular and half-annular apertures using extended highly coherent and incoherent sources. We show that an integrated Stiles-Crawford function is absent for coherent light but remains valid for highly incoherent light at the pupil. The results are supported by numerical evidence for coherent light propagation and are in agreement with a light-coupling understanding of retina photoreceptor waveguides.

Non-resonant third-order nonlinearity of nanometric and subnanometric silver particles in aqueous solution.

We have measured and analyzed the behavior of the nonlinear refractive index of silver spheres in water in a non-resonant femtosecond excitation regime. Two different diameter silver nanosphere (0.65 and 9 nm) suspensions were used in the experiments. Thermal and nonthermal contributions to the nonlinear properties of the samples were determined exploring a novel high sensitivity thermal managed eclipse Z-scan technique. The dependence of nonthermal third order nonlinear susceptibility of the colloid with the silver nanoparticles filling factor was described using the generalized Maxwell-Garnett model. The nanoparticle size dependence of the colloid nonlinear refractive index was observed.

Exploring adaptive optics on focus-scan for nonlinear materials characterization.

Z-scan is a well-established technique used to measure the nonlinear refractive index and absorption coefficient of thin and transparent materials. The method requires the displacement of the sample along the focus of a laser beam. Therefore, the Z-scan is not suitable for experiments where the sample cannot be axially translated. Here, we explore a deformable mirror to create controllable defocus aberrations, translating the focus of the beam through the sample, alternatively to the sample displacement. The technique is based on time behavior analysis of the light beam transmitted by the nonlinear sample, at different defocus configurations. The method is validated by measuring reference samples (CS2 and SiO2) and comparing them with the conventional Z-scan technique.

Nonresonant high-order nonlinear optical properties of silver nanoparticles in aqueous solution.

In this work we determine the third, fifth- and seventh-order nonresonant nonlinear optical properties of silver nanoparticles (9 nm average diameter) colloids in aqueous solution under high intensity excitation. The nonlinear optical response and its dependence with the nanoparticles filling factor was measured and theoretically described. We show that for low inclusion concentration, the third order nonlinearity of the colloid can be described by the generalized Maxwell-Garnett model. With the increase of the nanoparticle concentration, changes in the medium nonlinearities was observed leading to high order effects. The fifth- and seventh- order susceptibilities were obtained for highly concentrated silver nanoparticle colloid and the data was supported by a theoretical model. The conventional Z-scan technique was employed, using 80 f s laser pulses at 800 nm, in a regime of high pulse energy (microJ) and low repetition rate (1 kHz).

Height and Weight Estimation From Anthropometric Measurements Using Machine Learning Regressions.

Height and weight are measurements explored to tracking nutritional diseases, energy expenditure, clinical conditions, drug dosages, and infusion rates. Many patients are not ambulant or may be unable to communicate, and a sequence of these factors may not allow accurate estimation or measurements; in those cases, it can be estimated approximately by anthropometric means. Different groups have proposed different linear or non-linear equations which coefficients are obtained by using single or multiple linear regressions. In this paper, we present a complete study of the application of different learning models to estimate height and weight from anthropometric measurements: support vector regression, Gaussian process, and artificial neural networks. The predicted values are significantly more accurate than that obtained with conventional linear regressions. In all the cases, the predictions are non-sensitive to ethnicity, and to gender, if more than two anthropometric parameters are analyzed. The learning model analysis creates new opportunities for anthropometric applications in industry, textile technology, security, and health care.

Clustering of Self-Organizing Maps as a means to support gait kinematics analysis and symmetry evaluation.

Gait analysis is relevant for the functional diagnostic of several musculoskeletal disorders. Walking patterns can be analyzed using techniques such as video processing and inertial measurement units (IMU). In this work, a Self-Organizing Maps (SOM) algorithm is applied to reduce the complexity of kinematic features obtained by IMU sensors of a sample of 40 individuals. Our system provides a simpler data representation (2-D graphic) than conventional methods, which often applies statistical analysis. We have tested the proposed method to analyze typical and simulated limping gait pattern under well-controlled conditions. Based on kinematic parameters and symmetry-related features, SOM algorithm was able to organize the sample in groups of subjects with three different gait patterns, normal and limping with each lower limb. Moreover, our system may be used to evaluate the recovery of a patient, offering intuitive information of his walking pattern in an assessment report. However, further research with atypical-gait subjects is necessary before applying such method as a clinical tool.

Mastication Evaluation With Unsupervised Learning: Using an Inertial Sensor-Based System.

There is a direct relationship between the prevalence of musculoskeletal disorders of the temporomandibular joint and orofacial disorders. A well-elaborated analysis of the jaw movements provides relevant information for healthcare professionals to conclude their diagnosis. Different approaches have been explored to track jaw movements such that the mastication analysis is getting less subjective; however, all methods are still highly subjective, and the quality of the assessments depends much on the experience of the health professional. In this paper, an accurate and non-invasive method based on a commercial low-cost inertial sensor (MPU6050) to measure jaw movements is proposed. The jaw-movement feature values are compared to the obtained with clinical analysis, showing no statistically significant difference between both methods. Moreover, We propose to use unsupervised paradigm approaches to cluster mastication patterns of healthy subjects and simulated patients with facial trauma. Two techniques were used in this paper to instantiate the method: Kohonen's Self-Organizing Maps and K-Means Clustering. Both algorithms have excellent performances to process jaw-movements data, showing encouraging results and potential to bring a full assessment of the masticatory function. The proposed method can be applied in real-time providing relevant dynamic information for health-care professionals.

Thermally managed eclipse Z-scan.

We report a new variation of the conventional Z-scan method to characterize the third-order optical nonlinearity of photonic materials. By exploiting the combination of the eclipse Z-scan with a thermal nonlinearity management technique, we demonstrate an improvement in sensitivity and flexibility of the method to simultaneously characterize the thermal and nonthermal nonlinearity of optical materials. The method is demonstrated by measuring the nonlinear refractive index in CS(2), SiO(2) and H(2)O, standard materials, and also in a biomaterial, the amino acid Tryptophan in water solution, using a femtosecond Ti-Sapphire laser operating at 76MHz repetition rate.

Simulating human photoreceptor optics using a liquid-filled photonic crystal fiber.

We introduce a liquid-filled photonic crystal fiber to simulate a retinal cone photoreceptor mosaic and the directionality selective mechanism broadly known as the Stiles-Crawford effect. Experimental measurements are realized across the visible spectrum to study waveguide coupling and directionality at different managed waveguide parameters. The crystal fiber method is a hybrid tool between theory and a real biological sample and a valuable addition as a retina model for real eye simulations.

Analysis of individual cone-photoreceptor directionality using scanning laser ophthalmoscopy.

Scanning laser ophthalmoscopy has been used to measure individual cone-photoreceptor directionalities in the living human eye. The directionality is determined at different retinal eccentricities where it is expected that cones have diameters ranging between 5-10µm, comparable to the spot size of the incident beam. Individual cone directionality values are compared with the predicted directionalities obtained by using the waveguide model of light coupling to and from photoreceptors for the case of a focused incident beam.

Ultrasmall spot size scanning laser ophthalmoscopy.

An ultrasmall spot size scanning laser ophthalmoscope has been developed that employs an annular aberration-corrected incident beam to increase the effective numerical aperture of the eye thereby reducing the width of the probing light spot. Parafovea and foveal cone photoreceptor visibility determined from small area retinal image scans are discussed from the perspective of mode matching between the focused incident beam and the waveguide modes of individual cones. The cone visibility near the fovea centralis can be increased with the annular illumination scheme whereas the visibility of larger parafovea cones drops significantly as a consequence of poorer mode match. With further improvements of the implemented wavefront correction technology it holds promise for individual cone-photoreceptor imaging at the fovea centralis and for optical targeting of the retina with increased resolution.

Nonlinear excitation of tryptophan emission enhanced by silver nanoparticles.

We measured and analyzed the behavior of the fluorescence of tryptophan water solutions with and without silver nanoparticles, excited by one, two and three photon processes. Two different colloids with silver nanoparticles with distinct diameters (0.65 nm and 9 nm) were used in the experiments. Fluorescence quenching was observed with one and two photon excitation. However, upon three-photon excitation, significant fluorescence enhancement was observed in the colloid. In this case excitation of the amino acid is assisted by the nonlinear absorption of infrared light by the silver nanoparticles. In this paper we are proposing a new way to explore metallic nanoparticles to enhance autofluorescence of biomolecules.

Perspectives on in vitro fungal diagnosis with UV light

O aumento na incidência de infecções fúngicas e a crescente habilidade dos organismos em adquirirem resistência a tratamentos antimicrobiais tornam necessária a introdução de métodos de identificação rápida de fungos e bactérias. Em dermatologia, técnicas ópticas que exploram luz ultravioleta, como o método de Wood, apresentam-se como importantes ferramentas para o diagnóstico clínico de infecções dermatológicas. Neste trabalho são exploradas técnicas de espectroscopia óptica por fluorescência na identificação de fungos. O método aplicado utiliza diferentes fontes de luz ultravioleta (lâmpada, LED, Laser) para excitar opticamente cromóforos de alguns de fungos (in vitro). Seis espécies de fungos (Microsporum gypseum, Microsporum canis, Trichophyton schoenleinii, Trichophyton rubrum, Epidermophyton floccosum e Fusarium solani) foram investigadas. Os resultados obtidos demonstram que algumas das limitações no diagnóstico de fungos com lâmpada de Wood podem ser superadas utilizando análises espectroscópicas refinadas. A largura espectral e o comprimento de onda de pico da fluorescência emitida pelos fungos são parâmetros que podem ser usados na distinção de microorganismos de espécies diferentes. Foi verificado também que, com a excitação óptica de fungos por LEDs, a luz emitida pelos microorganismos apresenta as mesmas características espectrais da fluorescência obtida com a excitação por uma lâmpada de Wood. Os resultados aqui apresentados indicam a possibilidade do uso de LEDs e LASERs no diagnóstico clínico de infecções fúngicas.