In-fibre Bragg grating temperature sensor system for medical applications

A novel quasidistributed in-flber Bragg grating (FBG) temperature sensor system has been developed for temperature profiling in vivo in the human body for medical applications, e.g., hyperthermia treatment. This paper provides the operating principle of FBG temperature sensors and then the design of the sensor head. High-resolution detection of the wavelength-shifts induced by temperature changes are achieved using drift-compensated interferometric detection while the return signals from the FBG sensor array are demultiplexed with a simple monochromator which offers crosstalk-free wavelength-division-multiplexing (WDM). A "strain-free" probe is designed by enclosing the FBG sensor array in a protection sleeve. A four FBG sensor system is demonstrated and the experimental results are in good agreement with those obtained by traditional electrical thermocouple sensors. A resolution of 0.1°C and an accuracy of ±0.2°C over a temperature range of 30-60°C have been achieved, which meet established medical requirements.

A fast response intrinsic humidity sensor based on an etched singlemode polymer fiber Bragg grating

A simple, low cost and fast response time intrinsic relative humidity sensor system based on an etched singlemode polymer fiber Bragg (POFBG) is presented in this paper. A macro-bend linear edge filter which converts the humidity induced wavelength shift into an intensity change is used as the interrogation technique. The singlemode POFBG is etched to micro-meters in diameter to improve the response time of the humidity sensor. A response time of 4.5 s is observed for a polymer FBG with a cladding diameter of 25 μm. The overall sensor system sensitivity was 0.23 mV/%RH. The etched POFBG humidity sensor shows anexponential decrease in response time with a decrease in fiber diameter. The developed sensor might have potential applications in a wide range of applications where fast and accurate real time humidity control is required. © 2013 Elsevier B.V. All rights reserved.

Respiratory function monitoring using a real-time three-dimensional fiber-optic shaping sensing scheme based upon fiber Bragg gratings

An array of in-line curvature sensors on a garment is used to monitor the thoracic and abdominal movements of a human during respiration. The results are used to obtain volumetric changes of the human torso in agreement with a spirometer used simultaneously at the mouth. The array of 40 in-line fiber Bragg gratings is used to produce 20 curvature sensors at different locations, each sensor consisting of two fiber Bragg gratings. The 20 curvature sensors and adjoining fiber are encapsulated into a low-temperature-cured synthetic silicone. The sensors are wavelength interrogated by a commercially available system from Moog Insensys, and the wavelength changes are calibrated to recover curvature. A three-dimensional algorithm is used to generate shape changes during respiration that allow the measurement of absolute volume changes at various sections of the torso. It is shown that the sensing scheme yields a volumetric error of 6%. Comparing the volume data obtained from the spirometer with the volume estimated with the synchronous data from the shape-sensing array yielded a correlation value 0.86 with a Pearson's correlation coefficient p <0.01.

Usability of prostaglandin monotherapy eye droppers

AIM: To determine the force needed to extract a drop from a range of current prostaglandin monotherapy eye droppers and how this related to the comfortable and maximum pressure subjects could exert. METHODS: The comfortable and maximum pressure subjects could apply to an eye dropper constructed around a set of cantilevered pressure sensors and mounted above their eye was assessed in 102 subjects (mean 51.2±18.7 years), repeated three times. A load cell amplifier, mounted on a stepper motor controlled linear slide, was constructed and calibrated to test the force required to extract the first three drops from 13 multidose or unidose latanoprost medication eye droppers. RESULTS: The pressure that could be exerted on a dropper comfortably (25.9±17.7 Newtons, range 1.2-87.4) could be exceeded with effort (to 64.8±27.1 Newtons, range 19.9-157.8; F=19.045, p<0.001), and did not differ between repeats (F=0.609, p=0.545). Comfortable and maximum pressures exerted were correlated (r=0.618, p<0.001), neither were influenced strongly by age (r=0.138, p=0.168; r=-0.118, p=0237, respectively), but were lower in women than in men (F=12.757, p=0.001). The force required to expel a drop differed between dropper designs (F=22.528, p<0.001), ranging from 6.4 Newtons to 23.4 Newtons. The force needed to exert successive drops increased (F=36.373, p<0.001) and storing droppers in the fridge further increased the force required (F=7.987, p=0.009). CONCLUSIONS: Prostaglandin monotherapy droppers for glaucoma treatment vary in their resistance to extract a drop and with some a drop could not be comfortably achieved by half the population, which may affect compliance and efficacy.

A self-referenced optical intensity sensor network using POFBGs for biomedical applications

This work bridges the gap between the remote interrogation of multiple optical sensors and the advantages of using inherently biocompatible low-cost polymer optical fiber (POF)-based photonic sensing. A novel hybrid sensor network combining both silica fiber Bragg gratings (FBG) and polymer FBGs (POFBG) is analyzed. The topology is compatible with WDM networks so multiple remote sensors can be addressed providing high scalability. A central monitoring unit with virtual data processing is implemented, which could be remotely located up to units of km away. The feasibility of the proposed solution for potential medical environments and biomedical applications is shown.

Functional carbon nanotubes for photonic applications

Carbon nanomaterials are an active frontier of research in current nanotechnology. Single wall Carbon Nanotube (SWNT) is a unique material which has already found several applications in photonics, electronics, sensors and drug delivery. This thesis presents a summary of the author’s research on functionalisation of SWNTs, a study of their optical properties, and potential for an application in laser physics. The first significant result is a breakthrough in controlling the size of SWNT bundles by varying the salt concentrations in N-methyl 2-pyrrolidone (NMP) through a salting out effect. The addition of Sodium iodide leads to self-assembly of CNTs into recognizable bundles. Furthermore, a stable dispersion can be made via addition polyvinylpyrrolidone (PVP) polymer to SWNTs-NMP dispersion, which indicates a promising direction for SWNT bundle engineering in organic solvents. The second set of experiments are concerned with enhancement of photoluminescence (PL), through the formation of novel macromolecular complexes of SWNTs with polymethine dyes with emission from enhanced nanotubes in the range of dye excitation. The effect appears to originate from exciton energy transfer within the solution. Thirdly, SWNT base-saturable absorbers (SA) were developed and applied to mode locking of fibre lasers. SWNT-based SAs were applied in both composite and liquid dispersion forms and achieved stable ultrashort generation at 1000nm, 1550nm, and 1800 nm for Ytterbium, Erbium and Thulium-doped fibre laser respectively. The work presented here demonstrates several innovative approaches for development of rapid functionalised SWNT-based dispersions and composites with potential for application in various photonic devices at low cost.

Inference of helicopter airframe condition

The goal of this paper is to model normal airframe conditions for helicopters in order to detect changes. This is done by inferring the flying state using a selection of sensors and frequency bands that are best for discriminating between different states. We used non-linear state-space models (NLSSM) for modelling flight conditions based on short-time frequency analysis of the vibration data and embedded the models in a switching framework to detect transitions between states. We then created a density model (using a Gaussian mixture model) for the NLSSM innovations: this provides a model for normal operation. To validate our approach, we used data with added synthetic abnormalities which was detected as low-probability periods. The model of normality gave good indications of faults during the flight, in the form of low probabilities under the model, with high accuracy (>92 %). © 2013 IEEE.

Projected sequential Gaussian processes:a C++ tool for interpolation of large datasets with heterogeneous noise

Heterogeneous datasets arise naturally in most applications due to the use of a variety of sensors and measuring platforms. Such datasets can be heterogeneous in terms of the error characteristics and sensor models. Treating such data is most naturally accomplished using a Bayesian or model-based geostatistical approach; however, such methods generally scale rather badly with the size of dataset, and require computationally expensive Monte Carlo based inference. Recently within the machine learning and spatial statistics communities many papers have explored the potential of reduced rank representations of the covariance matrix, often referred to as projected or fixed rank approaches. In such methods the covariance function of the posterior process is represented by a reduced rank approximation which is chosen such that there is minimal information loss. In this paper a sequential Bayesian framework for inference in such projected processes is presented. The observations are considered one at a time which avoids the need for high dimensional integrals typically required in a Bayesian approach. A C++ library, gptk, which is part of the INTAMAP web service, is introduced which implements projected, sequential estimation and adds several novel features. In particular the library includes the ability to use a generic observation operator, or sensor model, to permit data fusion. It is also possible to cope with a range of observation error characteristics, including non-Gaussian observation errors. Inference for the covariance parameters is explored, including the impact of the projected process approximation on likelihood profiles. We illustrate the projected sequential method in application to synthetic and real datasets. Limitations and extensions are discussed. © 2010 Elsevier Ltd.

A compact polymer optical fibre ultrasound detector

Polymer optical fibre (POF) is a relatively new and novel technology that presents an innovative approach for ultrasonic endoscopic applications. Currently, piezo electric transducers are the typical detectors of choice, albeit possessing a limited bandwidth due to their resonant nature and a sensitivity that decreases proportionally to their size. Optical fibres provide immunity from electromagnetic interference and POF in particular boasts more suitable physical characteristics than silica optical fibre. The most important of these are lower acoustic impedance, a reduced Young's Modulus and a higher acoustic sensitivity than single-mode silica fibre at both 1 MHz and 10 MHz. POF therefore offers an interesting alternative to existing technology. Intrinsic fibre structures such as Bragg gratings and Fabry-Perot cavities may be inscribed into the fibre core using UV lasers. These gratings are a modulation of the refractive index of the fibre core and provide the advantages of high reflectivity, customisable bandwidth and point detection. We present a compact in fibre ultrasonic point detector based upon a POF Bragg grating (POFBG) sensor. We demonstrate that the detector is capable of leaving a laboratory environment by using connectorised fibre sensors and make a case for endoscopic ultrasonic detection through use of a mounting structure that better mimics the environment of an endoscopic probe. We measure the effects of water immersion upon POFBGs and analyse the ultrasonic response for 1, 5 and 10 MHz.

Effectively positioning water loss event in smart water networks

With the eye-catching advances in sensing technologies, smart water networks have been attracting immense research interest in recent years. One of the most overarching tasks in smart water network management is the reduction of water loss (such as leaks and bursts in a pipe network). In this paper, we propose an efficient scheme to position water loss event based on water network topology. The state-of-the-art approach to this problem, however, utilizes the limited topology information of the water network, that is, only one single shortest path between two sensor locations. Consequently, the accuracy of positioning water loss events is still less desirable. To resolve this problem, our scheme consists of two key ingredients: First, we design a novel graph topology-based measure, which can recursively quantify the "average distances" for all pairs of senor locations simultaneously in a water network. This measure will substantially improve the accuracy of our positioning strategy, by capturing the entire water network topology information between every two sensor locations, yet without any sacrifice of computational efficiency. Then, we devise an efficient search algorithm that combines the "average distances" with the difference in the arrival times of the pressure variations detected at sensor locations. The viable experimental evaluations on real-world test bed (WaterWiSe@SG) demonstrate that our proposed positioning scheme can identify water loss event more accurately than the best-known competitor.