A smart sensing platform for the discrimination of human movement

This thesis documents the design, implementation and testing of a smart sensing platform that is able to discriminate between differences or small changes in a persons walking. The distributive tactile sensing method is used to monitor the deflection of the platform surface using just a small number of sensors and, through the use of neural networks, infer the characteristics of the object in contact with the surface. The thesis first describes the development of a mathematical model which uses a novel method to track the position of a moving load as it passes over the smart sensing surface. Experimental methods are then described for using the platform to track the position of swinging pendulum in three dimensions. It is demonstrated that the method can be extended to that of real-time measurement of balance and sway of a person during quiet standing. Current classification methods are then investigated for use in the classification of different gait patterns, in particular to identify individuals by their unique gait pattern. Based on these observations, a novel algorithm is developed that is able to discriminate between abnormal and affected gait. This algorithm, using the distributive tactile sensing method, was found to have greater accuracy than other methods investigated and was designed to be able to cope with any type of gait variation. The system developed in this thesis has applications in the area of medical diagnostics, either as an initial screening tool for detecting walking disorders or to be able to automatically detect changes in gait over time. The system could also be used as a discrete biometric identification method, for example identifying office workers as they pass over the surface.

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.

Helicopter vibration sensor selection using data visualisation

The main objective of the project is to enhance the already effective health-monitoring system (HUMS) for helicopters by analysing structural vibrations to recognise different flight conditions directly from sensor information. The goal of this paper is to develop a new method to select those sensors and frequency bands that are best for detecting changes in flight conditions. We projected frequency information to a 2-dimensional space in order to visualise flight-condition transitions using the Generative Topographic Mapping (GTM) and a variant which supports simultaneous feature selection. We created an objective measure of the separation between different flight conditions in the visualisation space by calculating the Kullback-Leibler (KL) divergence between Gaussian mixture models (GMMs) fitted to each class: the higher the KL-divergence, the better the interclass separation. To find the optimal combination of sensors, they were considered in pairs, triples and groups of four sensors. The sensor triples provided the best result in terms of KL-divergence. We also found that the use of a variational training algorithm for the GMMs gave more reliable results.

An area localization scheme for large scale underwater wireless sensor networks

In this paper, we study an area localization problem in large scale Underwater Wireless Sensor Networks (UWSNs). The limited bandwidth, the severely impaired channel and the cost of underwater equipment all makes the underwater localization problem very challenging. Exact localization is very difficult for UWSNs in deep underwater environment. We propose a Mobile DETs based efficient 3D multi-power Area Localization Scheme (3D-MALS) to address the challenging problem. In the proposed scheme, the ideas of 2D multi-power Area Localization Scheme(2D-ALS) [6] and utilizing Detachable Elevator Transceiver (DET) are used to achieve the simplicity, location accuracy, scalability and low cost performances. The DET can rise and down to broadcast its position. And it is assumed that all the underwater nodes underwater have pressure sensors and know their z coordinates. The simulation results show that our proposed scheme is very efficient. © 2009 IEEE.

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.

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.

Trajectory privacy preservation in mobile Wireless Sensor Networks

In recent years, there has been an enormous growth of location-aware devices, such as GPS embedded cell phones, mobile sensors and radio-frequency identification tags. The age of combining sensing, processing and communication in one device, gives rise to a vast number of applications leading to endless possibilities and a realization of mobile Wireless Sensor Network (mWSN) applications. As computing, sensing and communication become more ubiquitous, trajectory privacy becomes a critical piece of information and an important factor for commercial success. While on the move, sensor nodes continuously transmit data streams of sensed values and spatiotemporal information, known as ``trajectory information". If adversaries can intercept this information, they can monitor the trajectory path and capture the location of the source node. ^ This research stems from the recognition that the wide applicability of mWSNs will remain elusive unless a trajectory privacy preservation mechanism is developed. The outcome seeks to lay a firm foundation in the field of trajectory privacy preservation in mWSNs against external and internal trajectory privacy attacks. First, to prevent external attacks, we particularly investigated a context-based trajectory privacy-aware routing protocol to prevent the eavesdropping attack. Traditional shortest-path oriented routing algorithms give adversaries the possibility to locate the target node in a certain area. We designed the novel privacy-aware routing phase and utilized the trajectory dissimilarity between mobile nodes to mislead adversaries about the location where the message started its journey. Second, to detect internal attacks, we developed a software-based attestation solution to detect compromised nodes. We created the dynamic attestation node chain among neighboring nodes to examine the memory checksum of suspicious nodes. The computation time for memory traversal had been improved compared to the previous work. Finally, we revisited the trust issue in trajectory privacy preservation mechanism designs. We used Bayesian game theory to model and analyze cooperative, selfish and malicious nodes' behaviors in trajectory privacy preservation activities.^

Management of remote field instrumentation via the Internet

Supervisory Control & Data Acquisition (SCADA) systems are used by many industries because of their ability to manage sensors and control external hardware. The problem with commercially available systems is that they are restricted to a local network of users that use proprietary software. There was no Internet development guide to give remote users out of the network, control and access to SCADA data and external hardware through simple user interfaces. To solve this problem a server/client paradigm was implemented to make SCADAs available via the Internet. Two methods were applied and studied: polling of a text file as a low-end technology solution and implementing a Transmission Control Protocol (TCP/IP) socket connection. Users were allowed to login to a website and control remotely a network of pumps and valves interfaced to a SCADA. This enabled them to sample the water quality of different reservoir wells. The results were based on real time performance, stability and ease of use of the remote interface and its programming. These indicated that the most feasible server to implement is the TCP/IP connection. For the user interface, Java applets and Active X controls provide the same real time access.

A cafeína como agente modulador do ciclo atividade-repouso e memória em saguis (Callithrix jacchus)

Caffeine is the most consumed psychostimulant, with effects on attention, memory, and arousal. But when this substance is ingested near to bedtime there is a decrease on sleep, interfering on mnemonic processes. So, our ain was to investigate how the caffeine ingested near to sleep onset acts on sleep and memory in marmosets. We used 16 adult marmosets, single housed, in a 12:12h light-dark cycle. For registering locomotor activity were used two kinds of sensors. The gyroscope sensor registers activity each 30 sec and detects motion with good accuracy. Because of this we used this sensor for detecting nocturnal activity. The second sensor was based on infrared and accumulates activity each 5 min and it’s not able to detect nocturnal activity, just diurnal activity. We also used camera for registering Rest phase of one marmoset. For the cognitive task, the animals needed to learn a rewarded context (CR) when compared to a non-rewarded context CNR). This experiment comprises 5 phases: 1) Two days of habituation to apparatus; 2)Training for 8 days; 3) oral administration of caffeine (10 mg/kg) or placebo administration ±1h before sleep onset, for 8 days, with marmosets receiving placebo or caffeine; 4) retraining to apparatus and after that, placebo administration (placebo group-GP), or caffeine administration (with continuous group-GC and acute groupGA); 5) Test, for evaluating learning to CR. The sessions were filmed and each one had 8 min of duration. At 7 am started the habituation, training and test sessions, and at 3:15 pm started retraining. The results for gyroscope sensor showed that there was coincidence of 68,57% with nocturnal register of the cameras. Then, the gyroscope sensors detected nocturnal activity for all experimental groups Moreover, when compared sensor gyroscope with sensor based on infrared, was observed that both sensor presented similarity on patterns of activity curve. When we observed the effects of caffeine on Activity-Rest Cycle in GP, GA and GC, is possible to see that that gyroscope sensors and based on infrared presented only intra group differences. As behavioral results, the marmosets learned to discriminate CR when compared to CNR. Moreover, GP presented deficits on memory recall during the test, and GA increased the memory recall, when both were compared to GP. We concluded that the marmosets were able to learning the cognitive task and that the caffeine ingested near to sleep onset acts modulating memory in these animals. Moreover the gyroscope sensor can be used as alternative tool for investigating nocturnal activity. Then, the utilization of this non-invasive device allows marmosets exhibit their behavior within the laboratory conditions as natural as possible.