Optical Fibre Pressure Sensors in Medical Applications

Poeggel, Sven; Tosi, Daniele; Duraibabu, Dinesh Babu; Leen, Gabriel; McGrath, Denise; Lewis, Elfed

doi:10.3390/s150717115

Cited by 173 publications

(108 citation statements)

References 176 publications

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“…The FBG is an optical fiber that serves as a filter for a specific wavelength of light. The principle of the FBGS is to detect the reflected Bragg wavelength shift owing to changes in temperature, strain, or pressure [72], [73]. Fiber Bragg gratings are commonly used optical fiber sensors for measuring temperature and/or mechanical strain.…”

Section: Fiber Optic-based Sensorsmentioning

confidence: 99%

Ballistocardiogram signal processing: a review

Sadek

Biswas

Abdulrazak

2019

Health Inf Sci Syst

126

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There are several algorithms for analyzing and interpreting cardiorespiratory signals obtained from in-bed based sensors. In sum, these algorithms can be broadly grouped into three categories: time-domain algorithms, frequency-domain algorithms, and wavelet-domain algorithms. A summary of these algorithms is given below to highlight which category of algorithms will be used in our analysis. First, time-domain algorithms are mainly focused on detecting local maxima or local minima using a moving window, and therefore finding the interval between the dominant J-peaks of ballistocardiogram signal. However, this approach has many limitations because of the nonlinear and nonstationary behavior of the ballistocardiogram signal. The implication is that the ballistocardiogram signal does not display consistent J-peaks, which can usually be the case for overnight, in-home monitoring, particularly with frail elderly. Additionally, its accuracy will be undoubtedly affected by motion artifacts. Second, frequency-domain algorithms do not provide information about interbeat intervals. Nevertheless, they can provide information about heart rate variability. This is usually done by taking the fast Fourier transform or the inverse Fourier transform of the logarithm of the estimated spectrum, i.e., cepstrum of the signal using a sliding window. Thereafter, the dominant frequency is obtained in a particular frequency range. The limit of these algorithms is that the peak in the spectrum may get wider and multiple peaks may appear, which might cause a problem in measuring the vital signs. At last, the objective of wavelet-domain algorithms is to decompose the signal into different components, hence the component which shows an agreement with the vital signs can be selected. In other words, the selected component contains only information about the heart cycles or respiratory cycles, respectively. Interbeat intervals can be found easily by applying a simple peak detector. An empirical mode decomposition is an alternative approach to wavelet decomposition, and it is also a very suitable approach to cope with nonlinear and nonstationary signals such as cardiorespiratory signals. Apart from the above-mentioned algorithms, machine learning approaches have been implemented for measuring heartbeats. However, manual labeling of training data is a restricting property. Furthermore, the training step should be repeated whenever the data collection protocol has been changed.

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Section: Fiber Optic-based Sensorsmentioning

confidence: 99%

Ballistocardiogram signal processing: a review

Sadek

Biswas

Abdulrazak

2019

Health Inf Sci Syst

126

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“…Particularly attractive for medical diagnosis, they started to be developed as medical sensors since the 1970s [2][3][4][5][6]. The first main applications with sensing purposes focused on pH and temperature measurements but flow, pressure or blood gas analysis have also been described [7][8][9][10]. These particular remote sensors have a number of advantages compared to most ex situ optical sensors.…”

Section: Introductionmentioning

confidence: 99%

Multiplexed Remote SPR Detection of Biological Interactions through Optical Fiber Bundles

Desmet

Vindas

Meza

et al. 2020

Sensors

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The development of sensitive methods for in situ detection of biomarkers is a real challenge to bring medical diagnosis a step forward. The proof-of-concept of a remote multiplexed biomolecular interaction detection through a plasmonic optical fiber bundle is demonstrated here. The strategy relies on a fiber optic biosensor designed from a 300 µm diameter bundle composed of 6000 individual optical fibers. When appropriately etched and metallized, each optical fiber exhibits specific plasmonic properties. The surface plasmon resonance phenomenon occurring at the surface of each fiber enables to measure biomolecular interactions, through the changes of the retro-reflected light intensity due to light/plasmon coupling variations. The functionalization of the microstructured bundle by multiple protein probes was performed using new polymeric 3D-printed microcantilevers. Such soft cantilevers allow for immobilizing the probes in micro spots, without damaging the optical microstructures nor the gold layer. We show here the potential of this device to perform the multiplexed detection of two different antibodies with limits of detection down to a few tenths of nanomoles per liter. This tool, adapted for multiparametric, real-time, and label free monitoring is minimally invasive and could then provide a useful platform for in vivo targeted molecular analysis.

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“…Several types of fiber-optic pressure sensors for medical applications have been developed, as reviewed by Poeggel et al 4 and Roriz et al 4,5 . These sensors frequently comprise a sealed gas cavity with a diaphragm.…”

Section: Introductionmentioning

confidence: 99%

3D printed micro-scale fiber optic probe for intravascular pressure sensing

Poduval

Coote

Mosse

et al. 2018

Biosensing and Nanomedicine XI

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Small form-factor invasive pressure sensors are widely used in minimally invasive surgery, for example to guide decision making in coronary stenting procedures. Current fiber-optic sensors can have high manufacturing complexities and costs, which severely constrains their adoption outside of niche fields. A particular challenge is the ability to rapidly prototype and iterate upon sensor designs to optimize performance for different applications and medical devices. Here, we present a new sensor fabrication method, which involves two-photon polymerization printing and integration of the printed structure onto the end-face of a single-mode optical fiber. The active elements of the sensor were a pressure-sensitive diaphragm and an intermediate temperature-sensitive spacer that was insensitive to changes in external pressure. Deflection of the diaphragm and thermal expansion the spacer relative to the fiber end-face were monitored using phase-resolved lowcoherence interferometry. Pressure changes of 0.38 mmHg were detectable in the range of 760 to 1060 mmHg (absolute pressure), while a temperature changes of 0.023 °C were detectable in the range 25 to 47 °C using this fiber optic sensor. This method will enable the fabrication of a wide range of fiber-optic sensors with pressure and temperature sensitivities suitable for guiding minimally invasive surgery.

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Optical Fibre Pressure Sensors in Medical Applications

Cited by 173 publications

References 176 publications

Ballistocardiogram signal processing: a review

Ballistocardiogram signal processing: a review

Multiplexed Remote SPR Detection of Biological Interactions through Optical Fiber Bundles

3D printed micro-scale fiber optic probe for intravascular pressure sensing

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