Design of temperature insensitive <i>in vivo</i> strain sensor using multilayer single mode optical fiber

doi:10.1007/s12200-016-0537-z

Front. Optoelectron.

2016, Vol. 9

Issue (4) : 621-626 https://doi.org/10.1007/s12200-016-0537-z

RESEARCH ARTICLE

Design of temperature insensitive in vivo strain sensor using multilayer single mode optical fiber

F. MAKOUEI,S. MAKOUEI(

)

Faculty of Electrical and Computer Engineering, University of Tabriz, Tabriz 51664, Iran

Download: PDF(225 KB) HTML
Export: BibTeX | EndNote | Reference Manager | ProCite | RefWorks

Abstract

Bone strain measurement is a case of interest and demanding task for osteogenic adaption responses. In this paper, a novel biocompatible optical sensor for the bone axial strain measurement was proposed. In case modern multilayer single mode WII type optical fibers are well designed, they exhibit superior characteristics compared to conventional metal strain gauges (SGs). Furthermore, they could be strong competitors for SGs based on fiber Bragg grating (FBG) devices. In this study, mode field diameter (MFD) was selected as the indirect parameter for sensing task, which was totally a new approach. The strain sensitivity of 70.7733 pm/µε was obtained. Moreover, temperature sensitivity was –3.0031 × 10⁻⁶ pm/°C, which was negligible and removed the temperature compensation complexity for the sensor structure presented. The satisfactory property achieved for the designed sensor is as a result of multilayer fiber’s complicated structure as well as the design procedure based on evolutionary genetic algorithm (GA). In addition, the sensor demonstrated a reliable performance as its sensitivity was independent of the magnitude of the applied load.

Keywords bone strain in vivo optical strain gauge (SG) genetic algorithm (GA)

Corresponding Author(s): S. MAKOUEI

Issue Date: 29 November 2016

Cite this article:

F. MAKOUEI,S. MAKOUEI. Design of temperature insensitive in vivo strain sensor using multilayer single mode optical fiber[J]. Front. Optoelectron., 2016, 9(4): 621-626.

URL:

https://academic.hep.com.cn/foe/EN/10.1007/s12200-016-0537-z
https://academic.hep.com.cn/foe/EN/Y2016/V9/I4/621

Fig.1 Index of refraction profile for the proposed structures (WII)

Fig.2 Axial bone strain

Tab.1 Interpolated coefficient in the relation of Eq. (8)

Fig.3 Scheme of design procedure based on GA

Fig.4 MFD vs. compressive (−-) and tensile (+) strain

Tab.2 GA results for optimal values of geometrical and optical parameters

Fig.5 MFD vs. strain and temperature

Fig.6 Sensor sensitivity vs. applied strain

1	Bekker A, Cloete T J, Chinsamy-Turan A, Nurick G N, Kok S. Constant strain rate compression of bovine cortical bone on the Split-Hopkinson Pressure Bar. Materials Science and Engineering C, 2015, 46: 443–449 https://doi.org/10.1016/j.msec.2014.10.071 pmid: 25492009
2	Yang P F, Brüggemann G P, Rittweger J. What do we currently know from in vivo bone strain measurements in humans? Musculoskeletal & Neuronal Interact, 2011, 11(1): 8–20 pmid: 21364270
3	Fresvig T, Ludvigsen P, Steen H, Reikerås O. Fibre optic Bragg grating sensors: an alternative method to strain gauges for measuring deformation in bone. Medical Engineering & Physics, 2008, 30(1): 104–108 https://doi.org/10.1016/j.medengphy.2007.01.006 pmid: 17369073
4	Roriz P, Carvalho L, Frazão O, Santos J L, Simões J A. From conventional sensors to fibre optic sensors for strain and force measurements in biomechanics applications: a review. Journal of Biomechanics, 2014, 47(6): 1251–1261 https://doi.org/10.1016/j.jbiomech.2014.01.054 pmid: 24612722
5	Othonos A. Fiber Bragg gratings. Journal of Scientific Instruments, 1997, 68(12): 4309–4341 https://doi.org/10.1063/1.1148392
6	Reekie L, Dakin J P, Archambault J L, Xu M G. Discrimination between strain and temperature effects using dual-wavelength fiber grating sensors. Electronics Letters, 1994, 30(13): 1085–1087 https://doi.org/10.1049/el:19940746
7	Liu H B, Liu H Y, Peng G D, Chu P L. Strain and temperature sensor using a combination of polymer and silica fibre Bragg gratings. Optics Communications, 2003, 219(1-6): 139–142 https://doi.org/10.1016/S0030-4018(03)01313-0
8	Holland J H. Adaptation in Natural and Artificial Systems. 4th ed. Cambridge, MA: MIT Press, 1992
9	Goldberg D E. Genetic Algorithms in Search, Optimization and Machine Learning. New York: Addison-Wesley, 1989
10	Zhang X, Tian X. Analyzes of waveguide dispersion characteristics of WI- and WII-type triple-clad single-mode fibers. Optics & Laser Technology, 2003, 35(4): 237–244 https://doi.org/10.1016/S0030-3992(02)00175-5
11	Makouei S, Oskouei M S, Rostami A. Study of bending loss and mode field diameter in depressed inner core triple clad single mode optical fibers. Optics Communications, 2007, 280(1): 58–67 https://doi.org/10.1016/j.optcom.2007.07.052
12	Gatak A, Thyagarajan K. Introduction to Fiber Optics. 3rd ed. Cambridge: Cambridge University Press, 2002
13	Artiglia M, Coppa G, Di Vita P, Potenza M, Sharma A. Mode field diameter measurements in single mode optical fibers. IEEE Journal of Lightwave Technology, 1989, 7(8): 1139–1152 https://doi.org/10.1109/50.32374
14	Mishra V, Singh N, Rai D V, Tiwari U, Poddar G C, Jain S C, Mondal S K, Kapur P. Fiber Bragg grating sensor for monitoring bone decalcification. Orthopeadics & Traumatology, Surgery & Research, 2010, 96(6): 646–651 https://doi.org/10.1016/j.otsr.2010.04.010
15	Mignani A G, Baldini F. Biomedical sensors using optical fibres. Reports on Progress in Physics, 1996, 59(1): 1–28 https://doi.org/10.1088/0034-4885/59/1/001
16	Cai J, Ishikawa Y, Wada K. Strain induced bandgap and refractive index variation of silicon. Optics Express, 2013, 21(6): 7162–7170 https://doi.org/10.1364/OE.21.007162 pmid: 23546100
17	Ghosh G. Temperature dispersion of refractive indexes in some silicate fiber glasses. Photonics Technology Letters, 1994, 6(3): 431–433 https://doi.org/10.1109/68.275509
18	Ghosh G. Dispersion of temperature coefficients of birefringence in some chalcopyrite crystals. Applied Optics, 1984, 23(7): 976–978 https://doi.org/10.1364/AO.23.000976 pmid: 20424685

[1]	Yanjun ZHANG,Jinrui XU,Xinghu FU,Jinjun LIU,Yongsheng TIAN. Hybrid algorithm combining genetic algorithm with back propagation neural network for extracting the characteristics of multi-peak Brillouin scattering spectrum[J]. Front. Optoelectron., 2017, 10(1): 62-69.
[2]	Guo HE,Bingbing LI,Sihua YANG. In vivo imaging of a single erythrocyte with high-resolution photoacoustic microscopy[J]. Front. Optoelectron., 2015, 8(2): 122-127.

Viewed

Full text

Abstract

Cited

Shared

Discussed