A universal multi-parameter sensing scheme based on a self-interference micro-ring resonator (SIMRR) is proposed. Benefit from the special intensity sensing mechanism, the SIMRR allows multimode sensing in a wide range of wavelengths but immune from frequency noise. To process the multiple mode spectra that are dependent on multiple parameters, we adopt the machine learning algorithm instead of massive asymptotic solutions of resonators. Employing the proposed multi-mode sensing approach, a two-parameter SIMRR sensor is designed. Assuming that two gases have different wavelength dependence of refractive indices, the feasibility and effectiveness of the two-parameter sensing strategy are verified numerically. Moreover, the dependence of parameter estimation accuracy on the laser intensity noises is also investigated. The numerical results indicate that our scheme of multi-parameter sensing in a multimode SIMRR holds great potential for practical high-sensitive sensing platforms compared with the single-mode sensing based on whispering gallery mode (WGM) resonators.
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http://dx.doi.org/10.3390/s20030709 | DOI Listing |
ACS Sens
January 2025
State Key Laboratory of Optoelectronic Materials and Technologies, School of Electronics and Information Technology; Guangdong Province Key Laboratory of Display Material and Technology, Sun Yat-Sen University, Guangzhou 510006, China.
Gouty arthritis is one of the most common forms of inflammatory arthritis and has brought a significant burden on patients and society. Current strategies for managing gout primarily focus on long-term urate-lowering therapy. With the rapid advancement of point-of-care testing (POCT) technology, continuous monitoring of gout-related biomarkers like uric acid (UA) or inflammatory cytokines can provide rapid and personalized diagnosis for gout management.
View Article and Find Full Text PDFSci Rep
January 2025
School of Microelectronics and Communication Engineering, Chongqing University, Chongqing, 400044, China.
In this paper, a dual-parameter liquid level and refractive index (R.I.) sensor is fabricated using three pieces of bare polymer optical fibers (POFs), which can independently and simultaneously sense the liquid level and R.
View Article and Find Full Text PDFBiosens Bioelectron
March 2025
College of Information Science and Engineering, Northeastern University, Shenyang, 110819, China; Hebei Key Laboratory of Micro-Nano Precision Optical Sensing and Measurement Technology, Qinhuangdao, 066004, China.
A novel dual-parameter optical fiber biosensor based on surface plasmon resonance (SPR) for simultaneous measurement of urea and uric acid concentrations is proposed in this paper. Based on the principle of positive and negative electric combination, ZnO nanoparticles is selected as the matrix for immobilizing urease and uricase with selective recognition ability, which can also be used as a sensitizing material to increase the refractive index detection sensitivity of SPR by 22%. Then, Nafion ion exchange membrane was introduced to wrap the urea sensing area to avoid crosstalk caused by the overlap of adjacent sensing areas.
View Article and Find Full Text PDFAdv Sci (Weinh)
December 2024
State Key Laboratory of Optoelectronic Materials and Technologies, Guangdong Province Key Laboratory of Display Material and Technology, School of Electronics and Information Technology, Sun Yat-Sen University, Guangzhou, 510006, China.
The real-time monitoring of in vivo electrophysiological and biochemical signals provides critical insights into the activities of tissues and organs. As the activity and metabolic state of different sites in the muscle vary, multichannel detection is necessary to capture the functional state of the whole muscle, yet the access to the bio-information in subcutaneous space remained challenging. This work reports the development of a reconfigurable microneedle electrode array integrated system designed to achieve painless and minimally invasive monitoring of subcutaneous electromyogram (EMG), oxygen species, and pH through an array of thumbtack-shaped microneedle (TSMN) electrode.
View Article and Find Full Text PDFThis study presents a proof-of-concept demonstration of a demodulation technique using a seven-core fiber (SCF) and machine learning (ML) algorithms for multimode fiber (MMF)-based tactile sensing. By condensing high-resolution images into vectors of seven power values from the cores of the MMF, dataset size is significantly reduced compared to conventional specklegram sensors, mitigating post-processing workload. This downsampling approach, akin to machine learning pooling layers, boosts computational efficiency without compromising accuracy.
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