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Τίτλος: Plane-by-Plane Written, Low-Loss Polymer Optical Fiber Bragg Grating Arrays for Multiparameter Sensing in a Smart Walker
Συγγραφείς: Leal, Arnaldo G. 
Frizera, Anselmo 
Theodosiou, Antreas 
Díaz, Camilo 
Jimenez, Mario 
Min, Rui 
Pontes, Maria José 
Kalli, Kyriacos 
Marques, Carlos 
Major Field of Science: Engineering and Technology
Field Category: Electrical Engineering - Electronic Engineering - Information Engineering
Λέξεις-κλειδιά: Fiber Bragg gratings;Healthcare devices;Polymer optical fibers;Smart walkers
Ημερομηνία Έκδοσης: 15-Οκτ-2019
Πηγή: IEEE Sensors Journal, 2019, vol. 19, no. 20, pp. 9221-9228
Volume: 19
Issue: 20
Start page: 9221
End page: 9228
Περιοδικό: IEEE Sensors Journal 
Περίληψη: In this paper, we report the development of fiber Bragg gratings (FBGs) arrays in polymer optical fibers (POFs), specifically cyclic transparent optical polymer (CYTOP) fibers, using a femtosecond (fs) laser. The CYTOP is almost transparent to near-ultraviolet and visible light, thus femtosecond lasers appear to be a very promising technology for the development of gratings in such fibers. Bearing this in mind, we have applied the direct write, plane-by-plane inscription method to obtain 'single-peak' FBGs in long arrays. Following this, we examine the performance of a 5-FBG array applied in a smart walker (SW) and characterized for four different functionalities of the proposed healthcare device. The polymer sensors were used to analyze 1) structural health monitoring (SHM) of the SW's mechanical structure; 2) detection of users' movement intention; 3) gait cadence estimation; and 4) detection of floor-induced vibrations for localization and mapping applications. The good results obtained in comparison to commercially available devices show the suitability of the proposed FBG-array on the instrumentation of healthcare devices, where multiple parameters can be measured using the same fiber, which leads to a compact and energy efficient system.
URI: https://hdl.handle.net/20.500.14279/18556
ISSN: 15581748
DOI: 10.1109/JSEN.2019.2921419
Rights: © IEEE
Type: Article
Affiliation: Federal University of Espirito Santo 
Cyprus University of Technology 
El Bosque University 
Universitat Politècnica de València 
University of Aveiro 
Publication Type: Peer Reviewed
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