Dynamic range enhancement for the sensing signals of peak-saturated fiber Bragg grating spectra.

Fiber Bragg grating (FBG) sensors applying time-delay interrogators with wavelength swept lasers (WSLs) are popular for their great potentials in high sensing resolution and power budget. In these systems, well-calibrated WSLs with reduced wavelength nonlinearity and jitter are critical for the sensing performance. However, high-performance WSLs are expensive and could significantly increase the cost of the systems. The overall cost may be reduced by maximally sharing each WSL with multiple sensing FBGs through mechanisms like power splitting, which distribute the WSL signal into multiple independently operated serial FBG chains. Under such scenarios, the sensing processing unit (SPU) of each serial FBG chain must be synchronized with the WSL for correctly estimating the FBGs' respective spectra from the signal return time delays. We previously propose a self-synchronized scheme relying on the dual-polarity spectrum signal, which reduces the synchronization labor. The dual-polarity signal has a wider dynamic range, which may limit the system response speed or accuracy, considering the amplifiers' responses or the analog-to-digital converters' (ADCs') quantization noise. In this Letter, we apply peak-saturated FBG spectra for the sensors to increase the receivers' equivalent dynamic range. The flattop waveforms of the saturated peaks result in uncertainty for the peak positions. An artificial neutral network (ANN)-based method is further studied to enhance the peak detection accuracy. We show an ∼88% receiver dynamic range improvement with an inaccuracy reduction of about a half compared to the filter-and-maximum-readout (FMR) method.

Implicit HbA1c Achieving 87% Accuracy within 90 Days in Non-Invasive Fasting Blood Glucose Measurements Using Photoplethysmography.

To reduce the error induced by overfitting or underfitting in predicting non-invasive fasting blood glucose (NIBG) levels using photoplethysmography (PPG) data alone, we previously demonstrated that incorporating HbA1c led to a notable 10% improvement in NIBG prediction accuracy (the ratio in zone A of Clarke's error grid). However, this enhancement came at the cost of requiring an additional HbA1c measurement, thus being unfriendly to users. In this study, the enhanced HbA1c NIBG deep learning model (blood glucose level predicted from PPG and HbA1c) was trained with 1494 measurements, and we replaced the HbA1c measurement (explicit HbA1c) with "implicit HbA1c" which is reversely derived from pretested PPG and finger-pricked blood glucose levels. The implicit HbA1c is then evaluated across intervals up to 90 days since the pretest, achieving an impressive 87% accuracy, while the remaining 13% falls near the CEG zone A boundary. The implicit HbA1c approach exhibits a remarkable 16% improvement over the explicit HbA1c method by covering personal correction items automatically. This improvement not only refines the accuracy of the model but also enhances the practicality of the previously proposed model that relied on an HbA1c input. The nonparametric Wilcoxon paired test conducted on the percentage error of implicit and explicit HbA1c prediction results reveals a substantial difference, with a p-value of 2.75 × 10-7.

Hybrid Vibration and UV Fluorescence Technology for Rapid Imaging and Guidance for Manual Removal of Fish Bones from Fish Floss.

The objective of the proposed human-machine cooperation (HMC) workstation is to both rapidly detect calcium-based fish bones in masses of minced fish floss and visually guide operators in approaching and removing the detected fish bones by hand based on the detection of fingernails or plastic-based gloves. Because vibration is a separation mechanism that can prevent absorption or scattering in thick fish floss for UV fluorescence detection, the design of the HMC workstation included a vibration unit together with an optical box and display screens. The system was tested with commonly used fish (swordfish, salmon, tuna, and cod) representing various cooking conditions (raw meat, steam-cooked meat, and fish floss), their bones, and contaminating materials such as derived from gloves made of various types of plastic (polyvinylchloride, emulsion, and rubber) commonly used in the removal of fish bones. These aspects were each investigated using the spectrum analyzer and the optical box to obtain and analyze the fluorescence spectra and images. The filter was mounted on a charge-coupled device, and its transmission-wavelength window was based on the characteristic band for fish bones observed in the spectra. Gray-level AI algorithm was utilized to generate white marker rectangles. The vibration unit supports two mechanisms of air and downstream separation to improve the imaging screening of fish bones inside the considerable flow of fish floss. Notably, under 310 nm ultraviolet B (UVB) excitation, the fluorescence peaks of the raw fillets, steam-cooked meat, and fish floss were observed at for bands at longer wavelengths (500-600 nm), whereas those of the calcium and plastic materials occurred in shorter wavelength bands (400-500 nm). Perfect accuracy of 100% was achieved with the detection of 20 fish bones in 2 kg of fish floss, and the long test time of around 10-12 min results from the manual removal of these fish bones.

Inflammation-Responsive Nanovalves of Polymer-Conjugated Dextran on a Hole Array of Silicon Substrate for Controlled Antibiotic Release.

Poly(methacrylic acid) (PMAA) brushes were tethered on a silicon surface possessing a 500-nm hole array via atom transfer radical polymerization after the modification of the halogen group. Dextran-biotin (DB) was sequentially immobilized on the PMAA chains to obtain a P(MAA-DB) brush surrounding the hole edges on the silicon surface. After loading antibiotics inside the holes, biphenyl-4,4'-diboronic acid (BDA) was used to cross-link the P(MAA-DB) chains through the formation of boronate esters to cap the hole and block the release of the antibiotics. The boronate esters were disassociated with reactive oxygen species (ROS) to open the holes and release the antibiotics, thus indicating a reversible association. The total amount of drug inside the chip was approximately 52.4 µg cm-2, which could be released at a rate of approximately 1.6 µg h-1 cm-2 at a ROS concentration of 10 nM. The P(MAA-DB) brush-modified chip was biocompatible without significant toxicity toward L929 cells during the antibiotic release. The inflammation-triggered antibiotic release system based on a subcutaneous implant chip not only exhibits excellent efficacy against bacteria but also excellent biocompatibility, recyclability, and sensitivity, which can be easily extended to other drug delivery systems for numerous biomedical applications without phagocytosis- and metabolism-related issues.

An Optical Smartphone-Based Inspection Platform for Identification of Diseased Orchids.

Infections of orchids by the Odontoglossum ringspot virus or Cymbidium mosaic virus cause orchid disfiguration and are a substantial source of economic loss for orchid farms. Although immunoassays can identify these infections, immunoassays are expensive, time consuming, and labor consuming and limited to sampling-based testing methods. This study proposes a noncontact inspection platform that uses a spectrometer and Android smartphone. When orchid leaves are illuminated with a handheld optical probe, the Android app based on the Internet of Things and artificial intelligence can display the measured florescence spectrum and determine the infection status within 3 s by using an algorithm hosted on a remote server. The algorithm was trained on optical data and the results of polymerase chain reaction assays. The testing accuracy of the algorithm was 89%. The area under the receiver operating characteristic curve was 91%; thus, the platform with the algorithm was accurate and convenient for infection screening in orchids.

Hybrid Fiber-Optic Sensing Integrating Brillouin Optical Time-Domain Analysis and Fiber Bragg Grating for Long-Range Two-Parameter Measurement.

Distributed fiber sensing (DFS) can provide real-time signals and warnings. The entire length of fiber optic cable can act as a sensing element, but the accuracy is sometimes limited. On the other hand, point-to-point fiber sensing (PPFS) is usually implemented using one or more fiber Bragg gratings (FBGs) at specific positions along with the fiber for the monitoring of specific parameters (temperature, strain, pressure, and so on). However, the cost becomes expensive when the number of FBGs increases. A hybrid fiber sensing scheme is thus proposed, combining the advantages of DFS and PPFS. It is based on a Brillouin optical time-domain analysis (BOTDA) fiber system with additional FBGs embedded at certain positions where it is necessary to detect specific parameters. The hybrid fiber sensing system has the advantages of full sensing coverage at essential locations that need to be carefully monitored. In our work, the test results showed that the proposed system could achieve a sensing distance of 16 km with the single-mode fiber with a 2 m spatial resolution. For FBG parameter measurements, the temperature variation was 52 °C, from 25 °C to 77 °C, with a temperature sensitivity of 23 pm/°C, and the strain was from 0 to 400 µÎµ, with a strain sensitivity of 0.975 pm/µÎµ, respectively, using two FBGs.

Accurate Peak Detection for Optical Sensing with Reduced Sampling Rate and Calculation Complexity.

Fiber Bragg gratings (FBGs) are widely applied in optical sensing systems due to their advantages including being simple to use, high sensitivity, and having great potential for integration into optical communication systems. A common method used for FBG sensing systems is wavelength interrogation. The performance of interrogation based sensing systems is significantly determined by the accuracy of the wavelength peak detection processing. Direct maximum value readout (DMVR) is the simplest peak detection method. However, the detection accuracy of DMVR is sensitive to noise and the sampling resolution. Many modified peak detection methods, such as filtering and curve fitting schemes, have been studied in recent decades. Though these methods are less sensitive to noise and have better sensing accuracy at lower sampling resolutions, they also confer increased processing complexity. As massive sensors may be deployed for applications such as the Internet of things (IoT) and artificial intelligence (AI), lower levels of processing complexity are required. In this paper, an efficient scheme applying a three-point peak detection estimator is proposed and studied, which shows a performance that is close to the curve fitting methods along with reduced complexity. A proof-of-concept experiment for temperature sensing is performed. 34% accuracy improvement compared to the DMVR is demonstrated.

Generation of Augmented Capillary Network Optical Coherence Tomography Image Data of Human Skin for Deep Learning and Capillary Segmentation.

The segmentation of capillaries in human skin in full-field optical coherence tomography (FF-OCT) images plays a vital role in clinical applications. Recent advances in deep learning techniques have demonstrated a state-of-the-art level of accuracy for the task of automatic medical image segmentation. However, a gigantic amount of annotated data is required for the successful training of deep learning models, which demands a great deal of effort and is costly. To overcome this fundamental problem, an automatic simulation algorithm to generate OCT-like skin image data with augmented capillary networks (ACNs) in a three-dimensional volume (which we called the ACN data) is presented. This algorithm simultaneously acquires augmented FF-OCT and corresponding ground truth images of capillary structures, in which potential functions are introduced to conduct the capillary pathways, and the two-dimensional Gaussian function is utilized to mimic the brightness reflected by capillary blood flow seen in real OCT data. To assess the quality of the ACN data, a U-Net deep learning model was trained by the ACN data and then tested on real in vivo FF-OCT human skin images for capillary segmentation. With properly designed data binarization for predicted image frames, the testing result of real FF-OCT data with respect to the ground truth achieved high scores in performance metrics. This demonstrates that the proposed algorithm is capable of generating ACN data that can imitate real FF-OCT skin images of capillary networks for use in research and deep learning, and that the model for capillary segmentation could be of wide benefit in clinical and biomedical applications.

Fiber Bragg grating sensing system with wavelength-swept-laser distribution and self-synchronization.

Fiber Bragg gratings (FBGs) with various interrogation schemes to estimate the FBG's spectrum shift have been widely used in fiber sensing systems. Wavelength swept laser (WSL) based interrogation architectures have been proposed to offer rapid and high-quality sensing performance. However, for getting higher sensing accuracy, the demands for high-performance WSL may push the system cost. Under these considerations, a WSL distribution architecture allowing multiple sensing processing units (SPUs) to share the WSL is studied in this Letter. A self-synchronization scheme is proposed to enable flexible SPU deployment with no concerns for the clock calibration. The proposed system is experimentally studied. Temperature estimation error of ∼2.5∘C and ∼0.5∘C with sensitivities of 0.13°C/ms and 0.14°C/ms, respectively, for the high and small temperature ranges are demonstrated.

Multi-point temperature sensing using a linear-cavity lasing system.

A multi-point fiber sensing system formed from a linear cavity laser is proposed. Various optical sensing systems have been investigated, for example, using fiber Bragg grating (FBG) and Brillouin scattering for multi-point sensing. This paper focuses on a simple sensing system by using multi-wavelength lasing with parallel cavities and a semiconductor optical amplifier (SOA). First, optical nonlinearity in amplification of the SOA is discussed to clarify the effects of gain saturation and four-wave mixing on the proposed multi-channel sensing system. And then lasing conditions in the linear cavity laser consisting of an SOA, an arrayed waveguide grating (AWG), and FBGs are theoretically investigated. The multi-wavelength lasing power is found to be limited mainly by gain saturation in the SOA. The lasing power for the eight-channel system is evaluated to be -8.5 dBm when the total loss in the linear cavity is 10 dB. The lasing power can be increased by 3 dB when the channel number is decreased to four. Next, multi-wavelength lasing in the cavity consisting of an SOA, an AWG, a loop mirror, and fiber mirror reflectors is experimentally demonstrated up to eight channels. Finally, two-channel temperature sensing ranging from 13°C to 76°C is experimentally confirmed by using two FBGs as the sensing elements with an AWG having 100-GHz bandwidth.

Investigation on iterative multiuser detection physical layer network coding in two-way relay free-space optical links with turbulences and pointing errors.

Physical layer network coding (PNC) improves the throughput in wireless networks by enabling two nodes to exchange information using a minimum number of time slots. The PNC technique is proposed for two-way relay channel free space optical (TWR-FSO) communications with the aim of maximizing the utilization of network resources. The multipair TWR-FSO is considered in this paper, where a single antenna on each pair seeks to communicate via a common receiver aperture at the relay. Therefore, chip interleaving is adopted as a technique to separate the different transmitted signals at the relay node to perform PNC mapping. Accordingly, this scheme relies on the iterative multiuser technique for detection of users at the receiver. The bit error rate (BER) performance of the proposed system is examined under the combined influences of atmospheric loss, turbulence-induced channel fading, and pointing errors (PEs). By adopting the joint PNC mapping with interleaving and multiuser detection techniques, the BER results show that the proposed scheme can achieve a significant performance improvement against the degrading effects of turbulences and PEs. It is also demonstrated that a larger number of simultaneous users can be supported with this new scheme in establishing a communication link between multiple pairs of nodes in two time slots, thereby improving the channel capacity.

Effects of aperture averaging and beam width on a partially coherent Gaussian beam over free-space optical links with turbulence and pointing errors.

Joint effects of aperture averaging and beam width on the performance of free-space optical communication links, under the impairments of atmospheric loss, turbulence, and pointing errors (PEs), are investigated from an information theory perspective. The propagation of a spatially partially coherent Gaussian-beam wave through a random turbulent medium is characterized, taking into account the diverging and focusing properties of the optical beam as well as the scintillation and beam wander effects. Results show that a noticeable improvement in the average channel capacity can be achieved with an enlarged receiver aperture in the moderate-to-strong turbulence regime, even without knowledge of the channel state information. In particular, it is observed that the optimum beam width can be reduced to improve the channel capacity, albeit the presence of scintillation and PEs, given that either one or both of these adverse effects are least dominant. We show that, under strong turbulence conditions, the beam width increases linearly with the Rytov variance for a relatively smaller PE loss but changes exponentially with steeper increments for higher PE losses. Our findings conclude that the optimal beam width is dependent on the combined effects of turbulence and PEs, and this parameter should be adjusted according to the varying atmospheric channel conditions. Therefore, we demonstrate that the maximum channel capacity is best achieved through the introduction of a larger receiver aperture and a beam-width optimization technique.

Post-impact fatigue damage monitoring using fiber Bragg grating sensors.

It has been shown that impact damage to composite materials can be revealed by embedded Fiber Bragg Gratings (FBG) as a broadening and splitting of the latter's characteristic narrow peak reflected spectrum. The current work further subjected the impact damaged composite to cyclic loading and found that the FBG spectrum gradually submerged into a rise of background intensity as internal damages progressed. By skipping the impact, directing the impact to positions away from the FBG and examining the extracted fibers, we concluded that the above change is not a result of deterioration/damage of the sensor. It is caused solely by the damages initiated in the composite by the impact and aggravated by fatigue loading. Evolution of the grating spectrum may therefore be used to monitor qualitatively the development of the incurred damages.

Highly efficient femtosecond pulse stretching by tailoring cavity dispersion in erbium fiber lasers with an intracavity short-pass edge filter.

We demonstrate highly efficient pulse stretching in Er(3+)-doped femtosecond mode-locked fiber lasers by tailoring cavity dispersion using an intracavity short-pass edge filter. The cavity dispersion is preset at around zero to obtain the shortest pulsewidth. When the cutoff wavelength of the short-pass edge filter is thermo-optically tuned to overlap the constituting spectral components of mode-locked pulses, large negative waveguide dispersion is introduced by the steep cutoff slope and the total cavity dispersion is moved to normal dispersion regime to broaden the pulsewidth. The time-bandwidth product of the mode-locked pulse increases with the decreasing temperature at the optical liquid surrounding the short-pass edge filter. Pulse stretch ratio of 3.53 (623.8 fs/176.8 fs) can be efficiently achieved under a temperature variation of 4 °C.

Influence of depressed-index outer ring on evanescent tunneling loss in tapered double-cladding fibers.

A tapered fiber with a depressed-index outer ring is fabricated and dispersion engineered to generate a widely tunable (1250-1650 nm) fundamental-mode leakage loss with a high cutoff slope (-1.2 dB/nm) and a high attenuation for stop band (>50 dB) by modification of both waveguide and material dispersions. The higher cutoff slope is achieved with a larger cross angle between the two refractive index dispersion curves of the tapered fiber and surrounding optical liquids through the use of depressed-index outer ring structures in double-cladding fibers.

Fiber-bragg-grating-based dispersion-compensated and gain-flattened raman fiber Amplifier.

In this paper, we propose a novel signal/pump double-pass Raman fiber amplifier using fiber Brag gratings (FBGs). In order to compensate the dispersion slop mismatch among channels in lightwave system, FBGs embedded in different positions along dispersion compensated fiber are used to control the travel length of each WDM signal. Gain equalization can be achieved by optimizing the reflectivity of each FBG. Maximum output power variation among channels is less than +/-0.5 dB after appropriate optimization. Finally, a wavelength division multiplexing (WDM) system using 40-Gb/s x 8 ch non return-to-zero (NRZ) signal transmission in a 100-km transmission fiber is simulated to confirm the system performance. Using proposed dispersion compensation method, it may lead to 2 dB improvement in Q value. Such kind of RFA may find vast applications in WDM system where dispersion management is a crucial issue.