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In this review, we summarize the latest advances in the design of optical frequency-domain reflectometers (OFDRs), digital signal processing, and sensors based on special optical fibers. We discuss state-of-the-art approaches to improving metrological characteristics, such as spatial resolution, SNR, dynamic range, and the accuracy of determining back reflection coefficients. We also analyze the latest achievements in the OFDR-based sensors: the accuracy of spatial localization of the impact, the error in detecting temperatures, deformation, and other quantities, and the features of separate measurement of various physical quantities. We also pay attention to the trend of mutual integration of frequency-domain optical reflectometry methods with time-domain optical reflectometry, which provides completely new sensing possibilities. We believe that this review may be useful to engineers and scientists focused on developing a lab setup, complete measurement instrument, or sensing system with specific requirements. [ABSTRACT FROM AUTHOR]

In the contemporary era, dizziness is a prevalent ailment among patients. It can be caused by either vestibular neuritis or a stroke. Given the lack of diagnostic utility of instrumental methods in acute isolated vertigo, the differentiation of vestibular neuritis and stroke is primarily clinical. As a part of the initial differential diagnosis, the physician focuses on the characteristics of nystagmus and the results of the video head impulse test (vHIT). Instruments for accurate vHIT are costly and are often utilized exclusively in healthcare settings. The objective of this paper is to review contemporary methodologies for accurately detecting the position of pupil centers in both eyes of a patient and for precisely extracting their coordinates. Additionally, the paper describes methods for accurately determining the head rotation angle under diverse imaging and lighting conditions. Furthermore, the suitability of these methods for vHIT is being evaluated. We assume the maximum allowable error is 0.005 radians per frame to detect pupils' coordinates or 0.3 degrees per frame while detecting the head position. We found that for such conditions, the most suitable approaches for head posture detection are deep learning (including LSTM networks), search by template matching, linear regression of EMG sensor data, and optical fiber sensor usage. The most relevant approaches for pupil localization for our medical tasks are deep learning, geometric transformations, decision trees, and RASNAC. This study might assist in the identification of a number of approaches that can be employed in the future to construct a high-accuracy system for vHIT based on a smartphone or a home computer, with subsequent signal processing and initial diagnosis. [ABSTRACT FROM AUTHOR]

A new method for extracting the Brillouin frequency shift (BFS) from the Brillouin gain spectrum (BGS), the modified backward correlation method (MBWC), is presented. The possibilities of using MBWC, and MBWC in combination with the Lorentzian curve fitting (LCF) based on Levenberg–Marquardt (LM) method, are studied. The effectiveness of the new method, and its combination with LM, has been demonstrated for processing spectra with a low signal-to-noise ratio (SNR). The experiments, which were in good agreement with the performed simulation, showed that at SNR = 0 dB, the combined (MBWC + LM) method provided the BFS extraction error of less than 4 MHz, while the state-of-the-art LM algorithm extracted it with the error greater than 4.5 MHz. The advantage of correlation methods becomes more significant with the decreasing SNR: at SNR = −2 dB, the LM's error is 14.3 MHz, and that of the combined one is 8.1 MHz. [ABSTRACT FROM AUTHOR]