3D Hand Pose Estimation with Neural Networks

We propose the design of a real-time system to recognize and interprethand gestures. The acquisition devices are low cost 3D sensors. 3D hand pose will be segmented, characterized and track using growing neural gas (GNG) structure. The capacity of the system to obtain information with a high degree of freedom allows the encoding of many gestures and a very accurate motion capture. The use of hand pose models combined with motion information provide with GNG permits to deal with the problem of the hand motion representation. A natural interface applied to a virtual mirrorwriting system and to a system to estimate hand pose will be designed to demonstrate the validity of the system.

Learning Probabilistic Features for Robotic Navigation Using Laser Sensors

SLAM is a popular task used by robots and autonomous vehicles to build a map of an unknown environment and, at the same time, to determine their location within the map. This paper describes a SLAM-based, probabilistic robotic system able to learn the essential features of different parts of its environment. Some previous SLAM implementations had computational complexities ranging from O(Nlog(N)) to O(N2), where N is the number of map features. Unlike these methods, our approach reduces the computational complexity to O(N) by using a model to fuse the information from the sensors after applying the Bayesian paradigm. Once the training process is completed, the robot identifies and locates those areas that potentially match the sections that have been previously learned. After the training, the robot navigates and extracts a three-dimensional map of the environment using a single laser sensor. Thus, it perceives different sections of its world. In addition, in order to make our system able to be used in a low-cost robot, low-complexity algorithms that can be easily implemented on embedded processors or microcontrollers are used.

μ-MAR: Multiplane 3D Marker based Registration for depth-sensing cameras

Many applications including object reconstruction, robot guidance, and. scene mapping require the registration of multiple views from a scene to generate a complete geometric and appearance model of it. In real situations, transformations between views are unknown and it is necessary to apply expert inference to estimate them. In the last few years, the emergence of low-cost depth-sensing cameras has strengthened the research on this topic, motivating a plethora of new applications. Although they have enough resolution and accuracy for many applications, some situations may not be solved with general state-of-the-art registration methods due to the signal-to-noise ratio (SNR) and the resolution of the data provided. The problem of working with low SNR data, in general terms, may appear in any 3D system, then it is necessary to propose novel solutions in this aspect. In this paper, we propose a method, μ-MAR, able to both coarse and fine register sets of 3D points provided by low-cost depth-sensing cameras, despite it is not restricted to these sensors, into a common coordinate system. The method is able to overcome the noisy data problem by means of using a model-based solution of multiplane registration. Specifically, it iteratively registers 3D markers composed by multiple planes extracted from points of multiple views of the scene. As the markers and the object of interest are static in the scenario, the transformations obtained for the markers are applied to the object in order to reconstruct it. Experiments have been performed using synthetic and real data. The synthetic data allows a qualitative and quantitative evaluation by means of visual inspection and Hausdorff distance respectively. The real data experiments show the performance of the proposal using data acquired by a Primesense Carmine RGB-D sensor. The method has been compared to several state-of-the-art methods. The results show the good performance of the μ-MAR to register objects with high accuracy in presence of noisy data outperforming the existing methods.

Point clouds of measurements in the Dechen Cave near Iserlohn, Germany

Modeling natural phenomena from 3D information enhances our understanding of the environment. Dense 3D point clouds are increasingly used as highly detailed input datasets. In addition to the capturing techniques of point clouds with LiDAR, low-cost sensors have been released in the last few years providing access to new research fields and facilitating 3D data acquisition for a broader range of applications. This letter presents an analysis of different speleothem features using 3D point clouds acquired with the gaming device Microsoft® Kinect. We compare the Kinect sensor with terrestrial LiDAR reference measurements using the KinFu pipeline for capturing complete 3D objects (< 4m**3). The results demonstrate the suitability of the Kinect to capture flowstone walls and to derive morphometric parameters of cave features. Although the chosen capturing strategy (KinFu) reveals a high correlation (R2=0.92) of stalagmite morphometry along the vertical object axis, a systematic overestimation (22% for radii and 44% for volume) is found. The comparison of flowstone wall datasets predominantly shows low differences (mean of 1 mm with 7 mm standard deviation) of the order of the Kinect depth precision. For both objects the major differences occur at strongly varying and curved surface structures (e.g. with fine concave parts).

A cost-effectiveness analysis of two rehabilitation support services for women with breast cancer

The purpose of this research was to estimate the cost-effectiveness of two rehabilitation interventions for breast cancer survivors, each compared to a population-based, non-intervention group (n = 208). The two services included an early home-based physiotherapy intervention (DAART, n = 36) and a group-based exercise and psychosocial intervention (STRETCH, n = 31). A societal perspective was taken and costs were included as those incurred by the health care system, the survivors and community. Health outcomes included: (a) 'rehabilitated cases' based on changes in health-related quality of life between 6 and 12 months post-diagnosis, using the Functional Assessment of Cancer Therapy - Breast Cancer plus Arm Morbidity (FACT-B+4) questionnaire, and (b) quality-adjusted life years (QALYs) using utility scores from the Subjective Health Estimation (SHE) scale. Data were collected using self-reported questionnaires, medical records and program budgets. A Monte-Carlo modelling approach was used to test for uncertainty in cost and outcome estimates. The proportion of rehabilitated cases was similar across the three groups. From a societal perspective compared with the non-intervention group, the DAART intervention appeared to be the most efficient option with an incremental cost of $1344 per QALY gained, whereas the incremental cost per QALY gained from the STRETCH program was $14,478. Both DAART and STRETCH are low-cost, low-technological health promoting programs representing excellent public health investments.

An Autonomic Framework for Mobile Cloud Computing

This thesis presents the formal definition of a novel Mobile Cloud Computing (MCC) extension of the Networked Autonomic Machine (NAM) framework, a general-purpose conceptual tool which describes large-scale distributed autonomic systems. The introduction of autonomic policies in the MCC paradigm has proved to be an effective technique to increase the robustness and flexibility of MCC systems. In particular, autonomic policies based on continuous resource and connectivity monitoring help automate context-aware decisions for computation offloading. We have also provided NAM with a formalization in terms of a transformational operational semantics in order to fill the gap between its existing Java implementation NAM4J and its conceptual definition. Moreover, we have extended NAM4J by adding several components with the purpose of managing large scale autonomic distributed environments. In particular, the middleware allows for the implementation of peer-to-peer (P2P) networks of NAM nodes. Moreover, NAM mobility actions have been implemented to enable the migration of code, execution state and data. Within NAM4J, we have designed and developed a component, denoted as context bus, which is particularly useful in collaborative applications in that, if replicated on each peer, it instantiates a virtual shared channel allowing nodes to notify and get notified about context events. Regarding the autonomic policies management, we have provided NAM4J with a rule engine, whose purpose is to allow a system to autonomously determine when offloading is convenient. We have also provided NAM4J with trust and reputation management mechanisms to make the middleware suitable for applications in which such aspects are of great interest. To this purpose, we have designed and implemented a distributed framework, denoted as DARTSense, where no central server is required, as reputation values are stored and updated by participants in a subjective fashion. We have also investigated the literature regarding MCC systems. The analysis pointed out that all MCC models focus on mobile devices, and consider the Cloud as a system with unlimited resources. To contribute in filling this gap, we defined a modeling and simulation framework for the design and analysis of MCC systems, encompassing both their sides. We have also implemented a modular and reusable simulator of the model. We have applied the NAM principles to two different application scenarios. First, we have defined a hybrid P2P/cloud approach where components and protocols are autonomically configured according to specific target goals, such as cost-effectiveness, reliability and availability. Merging P2P and cloud paradigms brings together the advantages of both: high availability, provided by the Cloud presence, and low cost, by exploiting inexpensive peers resources. As an example, we have shown how the proposed approach can be used to design NAM-based collaborative storage systems based on an autonomic policy to decide how to distribute data chunks among peers and Cloud, according to cost minimization and data availability goals. As a second application, we have defined an autonomic architecture for decentralized urban participatory sensing (UPS) which bridges sensor networks and mobile systems to improve effectiveness and efficiency. The developed application allows users to retrieve and publish different types of sensed information by using the features provided by NAM4J's context bus. Trust and reputation is managed through the application of DARTSense mechanisms. Also, the application includes an autonomic policy that detects areas characterized by few contributors, and tries to recruit new providers by migrating code necessary to sensing, through NAM mobility actions.

Monitoring Infants By Automatic Video Processing

This work has, as its objective, the development of non-invasive and low-cost systems for monitoring and automatic diagnosing specific neonatal diseases by means of the analysis of suitable video signals. We focus on monitoring infants potentially at risk of diseases characterized by the presence or absence of rhythmic movements of one or more body parts. Seizures and respiratory diseases are specifically considered, but the approach is general. Seizures are defined as sudden neurological and behavioural alterations. They are age-dependent phenomena and the most common sign of central nervous system dysfunction. Neonatal seizures have onset within the 28th day of life in newborns at term and within the 44th week of conceptional age in preterm infants. Their main causes are hypoxic-ischaemic encephalopathy, intracranial haemorrhage, and sepsis. Studies indicate an incidence rate of neonatal seizures of 0.2% live births, 1.1% for preterm neonates, and 1.3% for infants weighing less than 2500 g at birth. Neonatal seizures can be classified into four main categories: clonic, tonic, myoclonic, and subtle. Seizures in newborns have to be promptly and accurately recognized in order to establish timely treatments that could avoid an increase of the underlying brain damage. Respiratory diseases related to the occurrence of apnoea episodes may be caused by cerebrovascular events. Among the wide range of causes of apnoea, besides seizures, a relevant one is Congenital Central Hypoventilation Syndrome (CCHS) \cite{Healy}. With a reported prevalence of 1 in 200,000 live births, CCHS, formerly known as Ondine's curse, is a rare life-threatening disorder characterized by a failure of the automatic control of breathing, caused by mutations in a gene classified as PHOX2B. CCHS manifests itself, in the neonatal period, with episodes of cyanosis or apnoea, especially during quiet sleep. The reported mortality rates range from 8% to 38% of newborn with genetically confirmed CCHS. Nowadays, CCHS is considered a disorder of autonomic regulation, with related risk of sudden infant death syndrome (SIDS). Currently, the standard method of diagnosis, for both diseases, is based on polysomnography, a set of sensors such as ElectroEncephaloGram (EEG) sensors, ElectroMyoGraphy (EMG) sensors, ElectroCardioGraphy (ECG) sensors, elastic belt sensors, pulse-oximeter and nasal flow-meters. This monitoring system is very expensive, time-consuming, moderately invasive and requires particularly skilled medical personnel, not always available in a Neonatal Intensive Care Unit (NICU). Therefore, automatic, real-time and non-invasive monitoring equipments able to reliably recognize these diseases would be of significant value in the NICU. A very appealing monitoring tool to automatically detect neonatal seizures or breathing disorders may be based on acquiring, through a network of sensors, e.g., a set of video cameras, the movements of the newborn's body (e.g., limbs, chest) and properly processing the relevant signals. An automatic multi-sensor system could be used to permanently monitor every patient in the NICU or specific patients at home. Furthermore, a wire-free technique may be more user-friendly and highly desirable when used with infants, in particular with newborns. This work has focused on a reliable method to estimate the periodicity in pathological movements based on the use of the Maximum Likelihood (ML) criterion. In particular, average differential luminance signals from multiple Red, Green and Blue (RGB) cameras or depth-sensor devices are extracted and the presence or absence of a significant periodicity is analysed in order to detect possible pathological conditions. The efficacy of this monitoring system has been measured on the basis of video recordings provided by the Department of Neurosciences of the University of Parma. Concerning clonic seizures, a kinematic analysis was performed to establish a relationship between neonatal seizures and human inborn pattern of quadrupedal locomotion. Moreover, we have decided to realize simulators able to replicate the symptomatic movements characteristic of the diseases under consideration. The reasons is, essentially, the opportunity to have, at any time, a 'subject' on which to test the continuously evolving detection algorithms. Finally, we have developed a smartphone App, called 'Smartphone based contactless epilepsy detector' (SmartCED), able to detect neonatal clonic seizures and warn the user about the occurrence in real-time.

Displacement sensor using channelled spectrum dispersed on a linear CCD array

A novel form of low coherence interferometric sensor is described. The channelled spectrum produced by illuminating a sensing interferometer with a broadband source is analysed directly using a CCD array. The system currently provides unambiguous measurement over a range of 1.5 mm with an accuracy of better than 6 µm.

Tactile sensing with fibre Bragg gratings and neural networks

Fibre Bragg grating sensors are usually expensive to interrogate, and part of this thesis describes a low cost interrogation system for a group of such devices which can be indefinitely scaled up for larger numbers of sensors without requiring an increasingly broadband light source. It incorporates inherent temperature correction and also uses fewer photodiodes than the number or sensors it interrogates, using neural networks to interpret the photodiode data. A novel sensing arrangement using an FBG grating encapsulated in a silicone polymer is presented. This sensor is capable of distinguishing between different surface profiles with ridges 0.5 to 1mm deep and 2mm pitch and either triangular, semicircular or square in profile. Early experiments using neural networks to distinguish between these profiles are also presented. The potential applications for tactile sensing systems incorporating fibre Bragg gratings and neural networks are explored.

Fibre Bragg grating strain sensors

The fabrication of in-fibre Bragg gratings (FBGs) and their application as sensors is reported. The strain and temperature characteristic results for a number of chirped and uniform gratings written into three different host fibres are presented. The static and dynamic temperature response of a commercially available temperature compensated grating is reported. A five sensor wavelength division multiplexed fibre Bragg grating strain measurement system with an interrogation rate of 25 Hz and resolution of 10 was constructed. The results from this system are presented. A novel chirped FBG interrogation method was implemented in both the 1.3 and 1.5 m telecommunication windows. Several single and dual strain sensor systems, employing this method, were constructed and the results obtained from each are reported and discussed. These systems are particularly suitable for the measurement of large strain. The results from a system measuring up to 12 m and with a potential measurement range of 30 m are reported. This technique is also shown to give an obtainable resolution of 20 over a measurement range of 5 000 for a dual sensor system. These systems are simple, robust, passive and easy to implement. They offer low cost, high speed and, in the case of multiple sensors, truly simultaneous interrogation. These advantages make this technique ideal for strain sensing in SMART structures. Systems based on this method have been installed in the masts of four superyachts. A system, based on this technique, is currently being developed for the measurement of acoustic waves in carbon composite panels. The results from an alternative method for interrogating uniform FBG sensors are also discussed. Interrogation of the gratings was facilitated by a specifically written asymmetric grating which had a 15 nm long linearly sloped spectral edge. This technique was employed to interrogate a single sensor over a measurement range of 6 m and two sensors over a range of 4.5 me. The results obtained indicated achievable resolutions of 47 and 38 respectively.

High birefringence fibre interrogating interferometer for optical sensing applications

The use of high birefringence fiber interrogating interferometer for optical sensing applications was discussed. The method is of low cost and permits simple adjustment of the optical path difference and has much lower sensitivity to environmental perturbation. The polarization-maintaining (PM) fiber interferometer adopted a heterodyne approach using interferometric wavelength shift detection. The study showed that the inclusion of power amplifier driving a multi-element piezoelectric stack will enable the bandwidth to be pushed up into the kHz regime.

Ultra small integrated optical fiber sensing system

This paper introduces a revolutionary way to interrogate optical fiber sensors based on fiber Bragg gratings (FBGs) and to integrate the necessary driving optoelectronic components with the sensor elements. Low-cost optoelectronic chips are used to interrogate the optical fibers, creating a portable dynamic sensing system as an alternative for the traditionally bulky and expensive fiber sensor interrogation units. The possibility to embed these laser and detector chips is demonstrated resulting in an ultra thin flexible optoelectronic package of only 40 µm, provided with an integrated planar fiber pigtail. The result is a fully embedded flexible sensing system with a thickness of only 1 mm, based on a single Vertical-Cavity Surface-Emitting Laser (VCSEL), fiber sensor and photodetector chip. Temperature, strain and electrodynamic shaking tests have been performed on our system, not limited to static read-out measurements but dynamically reconstructing full spectral information datasets.

Polarization-independent high-resolution spectral interrogation of FBGs using a BFBG-CCD array for optical sensing applications

Optical fibre strain sensors using Fibre Bragg Gratings (FBGs) are poised to play a major role in structural health monitoring in a variety of application from aerospace to civil engineering. At the heart of technology is the optoelectronic instrumentation required to convert optical signals into measurands. Users are demanding compact, lightweight, rugged and low cost solutions. This paper describes development of a new device based on a blazed FBG and CCD array that can potentially meet the above demands. We have shown that this very low cost technique may be used to interrogate a WDM array of sensor gratings with highly accurate and highly repeatable results unaffected by the polarisation state of the radiation. In this paper, we present results showing that sensors may be interrogated with an RMS error of 1.7pm, drift below 0.12pm and dynamic range of up to 65nm.

Acoustic emission detection using optical fibre sensors for aerospace applications

Structural Health Monitoring (SHM) ensures the structural health and safety of critical structures covering a wide range of application areas. This thesis presents novel, low-cost and good-performance fibre Bragg grating (FBG) based systems for detection of Acoustic Emission (AE) in aircraft structures, which is a part of SHM. Importantly a key aim, during the design of these systems, was to produce systems that were sufficiently small to install in an aircraft for lifetime monitoring. Two important techniques for monitoring high frequency AE that were developed as a part of this research were, Quadrature recombination technique and Active tracking technique. Active tracking technique was used extensively and was further developed to overcome the limitations that were observed while testing it at several test facilities and with different optical fibre sensors. This system was able to eliminate any low frequency spectrum shift due to environmental perturbation and keeps the sensor always working at optimum operation point. This is highly desirable in harsh industrial and operationally active environments. Experimental work carried out in the laboratory has proved that such systems can be used for high frequency detection and have capability to detect up to 600 kHz. However, the range of frequency depends upon the requirement and design of the interrogation system as the system can be altered accordingly for different applications. Several optical fibre configurations for wavelength detection were designed during the course of this work along with industrial partners. Fibre Bragg grating Fabry-Perot (FBG-FP) sensors have shown higher sensitivity and usability than the uniform FBGs to be used with such system. This was shown experimentally. The author is certain that further research will lead to development of a commercially marketable product and the use of active tracking systems can be extended in areas of healthcare, civil infrastructure monitoring etc. where it can be deployed. Finally, the AE detection system has been developed to aerospace requirements and was tested at NDT & Testing Technology test facility based at Airbus, Filton, UK on A350 testing panels.

Fabrication and characterisation of 45º and Ex 45º:tilted fibre gratings and their applications in fibre lasers and sensors

In this thesis, I present the studies on fabrication, spectral and polarisation characterisation of fibre gratings with tilted structures at 45º and > 45º (namely 45º- TFGs and ex 45º-TFGs throughout this thesis) and a range of novel applications with these two types of grating. One of the major contributions made in this thesis is the systematic investigation of the grating structures, inscription analysis and spectral and polarisation properties of both types of TFGs. I have inscribed 45º-TFGs in standard telecom and polarisation maintaining (PM) fibres. Two wavelength regions of interest have been explored including 1.55 µm and 1.06 µm. Detailed analysis on fabrication and characterisation of 45º-TFGs on PM fibres have also been carried out for the first time. For ex 45º- TFGs, fabrication has been investigated only on low-cost standard telecom fibre. Furthermore, thermal responses have been measured and analysed showing that both types of TFG have low responsivity to temperature change. More importantly, their refractive index (RI) responses have been characterised to verify the high responsivity to surrounding medium. Based on the unique polarisation properties, both types of TFG have been applied in fibre laser systems to improve the laser performance, which forms another major contribution of the research presented in this thesis. The integration of a 45º-TFG to the Erbium doped fibre laser (EDFL) enables single polarisation laser output at a single wavelength. When combing with ex 45º-TFGs, the EDFL can be transformed to a multi-wavelength switchable laser with single polarisation output. Furthermore, by utilising the polarisation property of the TFGs, a 45º-TFG based mode locked fibre laser is implemented. This laser can produce laser pulses at femtosecond scale and is the first application of TFG in the field of nonlinear optics. Another important contribution from the studies is the development of TFG based passive and active optical sensor systems. An ex 45º-TFG has been successfully developed into a liquid level sensor showing high sensitivity to water based solvents. Strain and twist sensors have been demonstrated via a fibre laser system using both 45°- and ex 45º-TFG with capability identifying not just the twist rate but also the direction. The sensor systems have shown the added advantage of low cost signal demodulation. In addition, load sensor applications have been demonstrated using the 45º-TFG based single polarisation EDFL and the experimental results show good agreement with the theoretical simulation.