{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,6,6]],"date-time":"2026-06-06T01:00:04Z","timestamp":1780707604257,"version":"3.54.1"},"reference-count":33,"publisher":"MDPI AG","issue":"7","license":[{"start":{"date-parts":[[2024,4,3]],"date-time":"2024-04-03T00:00:00Z","timestamp":1712102400000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0\/"}],"funder":[{"name":"Slovak Grant Agency (VEGA)","award":["1\/0113\/22"],"award-info":[{"award-number":["1\/0113\/22"]}]},{"name":"Slovak Grant Agency (VEGA)","award":["APVV-21-0217"],"award-info":[{"award-number":["APVV-21-0217"]}]},{"DOI":"10.13039\/501100005357","name":"Slovak Research and Development Agency","doi-asserted-by":"publisher","award":["1\/0113\/22"],"award-info":[{"award-number":["1\/0113\/22"]}],"id":[{"id":"10.13039\/501100005357","id-type":"DOI","asserted-by":"publisher"}]},{"DOI":"10.13039\/501100005357","name":"Slovak Research and Development Agency","doi-asserted-by":"publisher","award":["APVV-21-0217"],"award-info":[{"award-number":["APVV-21-0217"]}],"id":[{"id":"10.13039\/501100005357","id-type":"DOI","asserted-by":"publisher"}]}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["Sensors"],"abstract":"<jats:p>Many techniques have been studied for recovering information from shared media such as optical fiber that carries different types of communication, sensing, and data streaming. This article focuses on a simple method for retrieving the targeted information with the least necessary number of significant samples when using statistical population sampling. Here, the focus is on the statistical denoising and detection of the fiber Bragg grating (FBG) power spectra. The impact of the two-sided and one-sided sliding window technique is investigated. The size of the window is varied up to one-half of the symmetrical FBG power spectra bandwidth. Both, two- and one-sided small population sampling techniques were experimentally investigated. We found that the shorter sliding window delivered less processing latency, which would benefit real-time applications. The calculated detection thresholds were used for in-depth analysis of the data we obtained. It was found that the normality three-sigma rule does not need to be followed when a small population sampling is used. Experimental demonstrations and analyses also showed that novel denoising and statistical threshold detection do not depend on prior knowledge of the probability distribution functions that describe the FBG power spectra peaks and background noise. We have demonstrated that the detection thresholds\u2019 adaptability strongly depends on the mean and standard deviation values of the small population sampling.<\/jats:p>","DOI":"10.3390\/s24072285","type":"journal-article","created":{"date-parts":[[2024,4,3]],"date-time":"2024-04-03T11:01:41Z","timestamp":1712142101000},"page":"2285","update-policy":"https:\/\/doi.org\/10.3390\/mdpi_crossmark_policy","source":"Crossref","is-referenced-by-count":5,"title":["Impact of Reducing Statistically Small Population Sampling on Threshold Detection in FBG Optical Sensing"],"prefix":"10.3390","volume":"24","author":[{"ORCID":"https:\/\/orcid.org\/0000-0002-7802-6388","authenticated-orcid":false,"given":"Gabriel","family":"Cibira","sequence":"first","affiliation":[{"name":"Institute of Aurel Stodola, Faculty of Electrical Engineering and Information Technology, University of Zilina, Komenskeho 843, 03101 Liptovsky Mikulas, Slovakia"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-3176-8069","authenticated-orcid":false,"given":"Ivan","family":"Glesk","sequence":"additional","affiliation":[{"name":"Department of Multimedia and Information-Communication Technologies, Faculty of Electrical Engineering and Information Technology, University of Zilina, Univerzitna 1, 01026 Zilina, Slovakia"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Jozef","family":"Dubovan","sequence":"additional","affiliation":[{"name":"Department of Multimedia and Information-Communication Technologies, Faculty of Electrical Engineering and Information Technology, University of Zilina, Univerzitna 1, 01026 Zilina, Slovakia"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-2239-0041","authenticated-orcid":false,"given":"Daniel","family":"Benedikovi\u010d","sequence":"additional","affiliation":[{"name":"Department of Multimedia and Information-Communication Technologies, Faculty of Electrical Engineering and Information Technology, University of Zilina, Univerzitna 1, 01026 Zilina, Slovakia"}],"role":[{"vocabulary":"crossref","role":"author"}]}],"member":"1968","published-online":{"date-parts":[[2024,4,3]]},"reference":[{"key":"ref_1","doi-asserted-by":"crossref","first-page":"102371","DOI":"10.1016\/j.yofte.2020.102371","article-title":"Recognition and classification of FBG reflection spectrum under non-uniform field based on support vector machine","volume":"60","author":"Li","year":"2020","journal-title":"Opt. Fiber Technol."},{"key":"ref_2","doi-asserted-by":"crossref","first-page":"103092","DOI":"10.1016\/j.autcon.2020.103092","article-title":"Estimation of crowd flow and load on pedestrian bridges using machine learning with sensor fusion","volume":"112","author":"Mustapha","year":"2020","journal-title":"Autom. Constr."},{"key":"ref_3","doi-asserted-by":"crossref","first-page":"102805","DOI":"10.1016\/j.yofte.2021.102805","article-title":"A multi-peak detection algorithm for FBG based on WPD-HT","volume":"68","author":"Lv","year":"2022","journal-title":"Opt. Fiber Technol."},{"key":"ref_4","doi-asserted-by":"crossref","unstructured":"Yan, Q., Che, X., Li, S., Wang, G., and Liu, X. (2023). \u03c0-FBG fiber optic acoustic emission sensor for the crack detection of wind turbine blades. Sensors, 23.","DOI":"10.3390\/s23187821"},{"key":"ref_5","doi-asserted-by":"crossref","first-page":"103561","DOI":"10.1016\/j.yofte.2023.103561","article-title":"Heartbeat and respiration monitoring based on FBG sensor network","volume":"81","author":"Zhichao","year":"2023","journal-title":"Opt. Fiber Technol."},{"key":"ref_6","doi-asserted-by":"crossref","unstructured":"Liu, Q., Yu, Y., Han, B.S., and Zhou, W. (2024). An improved spectral subtraction method for eliminating additive noise in condition monitoring system using fiber Bragg grating sensors. Sensors, 24.","DOI":"10.3390\/s24020443"},{"key":"ref_7","doi-asserted-by":"crossref","unstructured":"Zhuang, Y., Han, T., Yang, Q., O\u2019Malley, R., Kumar, A., Gerald, R.E., and Huang, J. (2022). A Fiber-optic sensor-embedded and machine learning assisted smart helmet for multi-variable blunt force impact sensing in real time. Biosensors, 12.","DOI":"10.3390\/bios12121159"},{"key":"ref_8","doi-asserted-by":"crossref","first-page":"994","DOI":"10.1109\/68.681295","article-title":"Optical all-pass filters for phase response design with applications for dispersion compensation","volume":"10","author":"Madsen","year":"1998","journal-title":"IEEE Phot. Technol. Lett."},{"key":"ref_9","doi-asserted-by":"crossref","first-page":"89","DOI":"10.1007\/s11082-021-03460-3","article-title":"Efficient detection of multiple FBG wavelength peaks using matched filtering technique","volume":"54","author":"Kumar","year":"2022","journal-title":"Opt. Quantum Electron."},{"key":"ref_10","doi-asserted-by":"crossref","unstructured":"Tosi, D. (2017). Review and analysis of peak tracking techniques for fiber Bragg grating sensors. Sensors, 17.","DOI":"10.3390\/s17102368"},{"key":"ref_11","doi-asserted-by":"crossref","first-page":"9","DOI":"10.1016\/j.yofte.2019.102129","article-title":"Accurate demodulation algorithm for multi-peak FBG sensor based on invariant moments retrieval","volume":"54","author":"Guo","year":"2020","journal-title":"Opt. Fiber Technol."},{"key":"ref_12","doi-asserted-by":"crossref","unstructured":"Meshcheryakov, R., Iskhakov, A., Mamchenko, M., Romanova, M., Uvaysov, S., Amirgaliyev, Y., and Gromaszek, K. (2022). A Probabilistic approach to estimating allowed SNR values for automotive LiDARs in \u2018smart cities\u2019 under various external influences. Sensors, 22.","DOI":"10.3390\/s22020609"},{"key":"ref_13","doi-asserted-by":"crossref","first-page":"28318","DOI":"10.1109\/ACCESS.2018.2819647","article-title":"A method of fiber Bragg grating sensing signal de-noise based on compressive sensing","volume":"6","author":"Chen","year":"2018","journal-title":"IEEE Access"},{"key":"ref_14","doi-asserted-by":"crossref","first-page":"687","DOI":"10.1134\/S0020441222050268","article-title":"State-of-the-art methods for determining the frequency shift of Brillouin scattering in fiber-optic metrology and sensing","volume":"65","author":"Krivosheev","year":"2022","journal-title":"Instrum. Exp. Tech."},{"key":"ref_15","first-page":"3243","article-title":"Distributed vibration sensor based on coherent detection of Phase-OTDR","volume":"28","author":"Lu","year":"2010","journal-title":"J. Light. Technol."},{"key":"ref_16","doi-asserted-by":"crossref","first-page":"8584","DOI":"10.1364\/OE.20.008584","article-title":"Fast Brillouin optical time domain analysis for dynamic sensing","volume":"20","author":"Peled","year":"2012","journal-title":"Opt. Express"},{"key":"ref_17","doi-asserted-by":"crossref","first-page":"25988","DOI":"10.1364\/OE.23.025988","article-title":"Time-gated digital optical frequency domain reflectometry with 1.6-m spatial resolution over entire 110-km range","volume":"23","author":"Liu","year":"2015","journal-title":"Opt. Express"},{"key":"ref_18","doi-asserted-by":"crossref","first-page":"6599","DOI":"10.1109\/JLT.2023.3289538","article-title":"Fast strain measurement in OFDR with the joint algorithm of wavelength domain differential accumulation and local cross-correlation","volume":"41","author":"Bai","year":"2023","journal-title":"J. Light. Technol."},{"key":"ref_19","doi-asserted-by":"crossref","unstructured":"Anfinogentov, V., Karimov, K., Kuznetsov, A., Morozov, O.G., Nureev, I., Sakhabutdinov, A., Lipatnikov, K., Hussein, S.M.R.H., and Ali, M.H. (2021). Algorithm of FBG spectrum distortion correction for optical spectra analyzers with CCD elements. Sensors, 21.","DOI":"10.20944\/preprints202102.0586.v1"},{"key":"ref_20","doi-asserted-by":"crossref","first-page":"4045","DOI":"10.1016\/j.measurement.2013.07.029","article-title":"Extraction and processing of real time of embedded FBG sensors using a fixed filter FBG circuit and an artificial neural network","volume":"46","author":"Kahandawa","year":"2013","journal-title":"Measurement"},{"key":"ref_21","doi-asserted-by":"crossref","unstructured":"Encinas, L.S., Zimmermann, A.C., and Veiga, C.L.N. (November, January 29). Fiber Bragg grating signal processing using artificial neural networks, an extended measuring range analysis. Proceedings of the 2007 SBMO\/IEEE MTT-S International Microwave and Optoelectronics Conference, Salvador, Brazil.","DOI":"10.1109\/IMOC.2007.4404351"},{"key":"ref_22","doi-asserted-by":"crossref","unstructured":"Cibira, G. (2022, January 23\u201326). Simplified statistical thresholding techniques for dynamic bandwidth allocation in shared Super-PON. Proceedings of the 2022 ELEKTRO, Krakow, Poland.","DOI":"10.1109\/ELEKTRO53996.2022.9803343"},{"key":"ref_23","doi-asserted-by":"crossref","first-page":"2526","DOI":"10.1109\/JLT.2022.3229965","article-title":"SNR-based denoising dynamic statistical threshold detection of FBG spectral peaks","volume":"41","author":"Cibira","year":"2023","journal-title":"J. Light. Technol."},{"key":"ref_24","doi-asserted-by":"crossref","first-page":"583","DOI":"10.1111\/1467-9868.00353","article-title":"Bayesian measures of model complexity and fit","volume":"64","author":"Spiegelhalter","year":"2002","journal-title":"J. Roy. Stat. Soc. Ser. B"},{"key":"ref_25","unstructured":"Johnson, N.L., Kotz, S., and Balakrishnan, N. (1994). Continuous Univariate Distributions, John Wiley & Sons. [2nd ed.]."},{"key":"ref_26","doi-asserted-by":"crossref","unstructured":"Jacod, J., and Protter, P. (2004). Probability Essentials, Springer. [2nd ed.].","DOI":"10.1007\/978-3-642-55682-1"},{"key":"ref_27","first-page":"694","article-title":"On the problem of the most efficient tests of statistical hypotheses","volume":"231","author":"Neyman","year":"1933","journal-title":"Philos. Trans. Roy. Soc. Lond. A"},{"key":"ref_28","doi-asserted-by":"crossref","first-page":"102544","DOI":"10.1016\/j.jmp.2021.102544","article-title":"The statistics of optimal decision making: Exploring the relationship between signal detection theory and sequential analysis","volume":"103","author":"Griffith","year":"2021","journal-title":"J. Math. Psychol."},{"key":"ref_29","doi-asserted-by":"crossref","unstructured":"Jones, A.R. (2018). Probability, Statistics and Other Frightening Stuff, Routledge\u2014Taylor & Francis Group. [1st ed.].","DOI":"10.4324\/9781315160061"},{"key":"ref_30","first-page":"74","article-title":"PV cells electrical parameters measurement","volume":"7","author":"Cibira","year":"2017","journal-title":"J. Electr. Eng."},{"key":"ref_31","unstructured":"ITU-T, G. (2024, February 23). 652: Characteristics of a Single-Mode Optical Fibre and Cable. Available online: https:\/\/www.itu.int\/rec\/T-REC-G.652-201611-I\/en."},{"key":"ref_32","unstructured":"(2024, February 23). Sensing Systems. Available online: https:\/\/www.sylex.sk\/products\/sensing-systems\/interrogators\/."},{"key":"ref_33","unstructured":"(2024, February 23). Optical Spectrum Analyzer. Available online: https:\/\/cdn.tmi.yokogawa.com\/files\/uploaded\/BUAQ6370C_01EN.pdf."}],"container-title":["Sensors"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/www.mdpi.com\/1424-8220\/24\/7\/2285\/pdf","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2025,10,10]],"date-time":"2025-10-10T14:23:06Z","timestamp":1760106186000},"score":1,"resource":{"primary":{"URL":"https:\/\/www.mdpi.com\/1424-8220\/24\/7\/2285"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2024,4,3]]},"references-count":33,"journal-issue":{"issue":"7","published-online":{"date-parts":[[2024,4]]}},"alternative-id":["s24072285"],"URL":"https:\/\/doi.org\/10.3390\/s24072285","relation":{},"ISSN":["1424-8220"],"issn-type":[{"value":"1424-8220","type":"electronic"}],"subject":[],"published":{"date-parts":[[2024,4,3]]}}}