Data-Driven Approach for Upper Limb Fatigue Estimation Based on Wearable Sensors.

Muscle fatigue is defined as a reduced ability to maintain maximal strength during voluntary contraction. It is associated with musculoskeletal disorders that affect workers performing repetitive activities, affecting their performance and well-being. Although electromyography remains the gold standard for measuring muscle fatigue, its limitations in long-term work motivate the use of wearable devices.

Distributed temperature sensors operating at 840 nm for short-range sensing applications.

Raman-based distributed temperature sensor (RDTS) devices have grown dramatically over the past two decades, partially driving the optical sensor industry. Over nearly four decades, most academic investigations about RDTS have focused on developing distributed sensor devices operating at the wavelength of 1550 nm, given the low loss of standard single-mode fibers in this spectral region. Certainly, the wavelength of 1550 nm is ideal for long-range sensing applications.

Spatial-derivative-based compression approach for distributed temperature data.

The new generation of distributed optical sensors with improved interrogation, multiplexing, and acquisition techniques with the possibility of performing measurements with high spatial resolution over tens of kilometers of optical fiber has led to the accumulation of a vast volume of data that can present a big challenge to process and store all this data. Looking for simple solutions to this problem, we present in this paper a data compression method for distributed temperature sensors. This compression approach performs the spatial derivative of the temperature signal, constituting a simple and effective method to remove redundant information.

Increasing the power and spectral efficiencies of an OFDM-based VLC system through multi-objective optimization.

The nonlinearity induced by light-emitting diodes in visible light communication (VLC) systems presents a challenge to the parametrization of orthogonal frequency division multiplexing (OFDM). The goal of the multi-objective optimization problem presented in this study is to maximize the transmitted power (superimposed LED bias-current and signal amplification) for both conventional and constant envelope (CE) OFDM while also maximizing spectral efficiency. The bit error rate (BER) metric is used to evaluate the optimization using the non-dominated sorting genetic algorithm II.

Design and analysis of recurrent neural networks for ultrafast optical pulse nonlinear propagation.

In this work, we analyze different types of recurrent neural networks (RNNs) working under several different parameters to best model the nonlinear optical dynamics of pulse propagation. Here we studied the propagation of picosecond and femtosecond pulses under distinct initial conditions going through 13 m of a highly nonlinear fiber and demonstrated the application of two RNNs returning error metrics such as normalized root mean squared error (NRMSE) as low as 9%. Those results were further extended for a dataset outside the initial pulse conditions used on the RNN training, and the best-proposed network was still able to achieve a NRMSE below 14%.

Analysis of a photonic integrated circuit for passive optical network for 5G NR.

This work presents the performance analysis of a passive optical network (PON) proposal with photonic integrated circuits (PIC). The PON architecture was simulated on MATLAB, focusing on the main functionalities of the optical line terminal, distribution network, and network unity regarded its effects on the physical layer. We show a simulated PIC, implemented on MATLAB through its analytic transfer function equation, used to implement orthogonal frequency division multiplexing in the optical domain to enhance the current optical networks for the 5G New-Radio (NR) scenario.

Performance evaluation of a simplified power-domain NOMA for visible light communications.

The performance of a visible light communication (VLC) system based on power-domain nonorthogonal multiple access (PD-NOMA) is experimentally evaluated in this paper. The simplicity of the adopted nonorthogonal scheme is provided by the fixed power allocation method at the transmitter and the single one-tap equalization executed before the successive interference cancellation at the receiver. The experimental results proved the successful transmission of the PD-NOMA scheme with three users in VLC links of up to 2.

Soft-Sensor System for Grasp Type Recognition in Underactuated Hand Prostheses.

This paper presents the development of an intelligent soft-sensor system to add haptic perception to the underactuated hand prosthesis PrHand. Two sensors based on optical fiber were constructed, one for finger joint angles and the other for fingertips' contact force. Three sensor fabrications were tested for the angle sensor by axially rotating the sensors in four positions.

Optimizing Resources and Increasing the Coverage of Internet-of-Things (IoT) Networks: An Approach Based on LoRaWAN.

A resource optimization methodology is proposed for application in long range wide area networks (LoRaWANs). Using variable neighborhood search (VNS) and a minimum-cost spanning tree algorithm, it reduces the implementation and the maintenance costs of such low power networks. Performance evaluations were conducted in LoRaWANs with LoRa repeaters to increase coverage, in scenario where the number and the location of the repeaters are determined by the VNS metaheuristic.

Label-free plasmonic immunosensor for cortisol detection in a D-shaped optical fiber.

Measuring cortisol levels as a stress biomarker is essential in many medical conditions associated with a high risk of metabolic syndromes such as anxiety and cardiovascular diseases, among others. One technology that has a growing interest in recent years is fiber optic biosensors that enable ultrasensitive cortisol detection. Such interest is allied with progress being achieved in basic interrogation, accuracy improvements, and novel applications.

An Optimized Self-Compensated Solution for Temperature and Strain Cross-Sensitivity in FBG Interrogators Based on Edge Filter.

Optical fiber sensors based on fiber Bragg gratings (FBGs) are prone to measurement errors if the cross-sensitivity between temperature and strain is not properly considered. This paper describes a self-compensated technique for canceling the undesired influence of temperature in strain measurement. An edge-filter-based interrogator is proposed and the central peaks of two FBGs (sensor and reference) are matched with the positive and negative slopes of a Fabry-Perot interferometer that acts as an optical filter.

Stable dark pulses produced by a graphite oxide saturable absorber in a fiber laser cavity.

In this paper, we report for the first time, to the best of our knowledge, the experimental generation of dark pulses in the 1.5 µm band from a passively $Q$Q-switched fiber laser employing graphite oxide as the saturable absorber, generating tunable microsecond pulses with kHz repetition rates. The graphite oxide samples were obtained by recycling the graphite present in Li-ion batteries used in cell phones through a chemical separation and oxidation process.

Optical spectral intensity-based interrogation technique for liquid-level interferometric fiber sensors.

In this paper, we propose a new, to the best of our knowledge, technique based on the measurement and analysis of the intensity of the interference pattern as an alternative approach for interrogating liquid-level interferometric fiber sensors. This interrogation is based on calculations that can take into account a vast number of peaks and dips of an interferometric spectrum, allowing the use of such devices as distributed sensors capable of measuring longer-level ranges. Here, liquid-level measurements of up to 120 mm were experimentally obtained with high linearity and a sensitivity of $ - {0.

Fiber Bragg grating-based sensor for torque and angle measurement in a series elastic actuator's spring.

Conventional technologies to monitor torque feedback and angle in exoskeleton actuators are bulky and sensitive to misalignments, and do not allow for multiplexed operation. Fiber Bragg grating (FBG)-based sensors are a robust sensing approach that are desirable for multi-parametric monitoring. Temperature, strain, torque, and angle are widely studied in human-robot interaction.