Tissue classification from electric impedance spectroscopy for haptic feedback in minimally invasive surgery

Haptic feedback is missing in teleoperated surgical robots creating a sensory disconnect from the surgeon and their patient. This thesis proposes using the electric impedance of tissues, instead of the traditionally used mechanical impedance, to develop haptic feedback for surgical robots. Electric impedance spectroscopy (EIS) and a modified surgical needle were successfully able to measure the electric impedance for gel-based phantoms, ex-vivo tissue, and freshly excised organs. Processes for fitting the electric impedance of these tissues to the double-dispersion Cole model were developed including stochastic and deterministic approaches. The tissues were classified with least square error, k-Nearest Neighbour and Na??ve Bayes using the measured electric impedance and the extracted model parameter values. The thesis culminates in applications of using EIS as part of implementing vibrotactile and force feedback applications involving sets of user trials to validate its effectiveness in identifying the tissue through haptic feedback

Haloes gone MAD: The Halo-Finder Comparison Project

[abridged] We present a detailed comparison of fundamental dark matter halo properties retrieved by a substantial number of different halo finders. These codes span a wide range of techniques including friends-of-friends (FOF), spherical-overdensity (SO) and phase-space based algorithms. We further introduce a robust (and publicly available) suite of test scenarios that allows halo finder developers to compare the performance of their codes against those presented here. This set includes mock haloes containing various levels and distributions of substructure at a range of resolutions as well as a cosmological simulation of the large-scale structure of the universe. All the halo finding codes tested could successfully recover the spatial location of our mock haloes. They further returned lists of particles (potentially) belonging to the object that led to coinciding values for the maximum of the circular velocity profile and the radius where it is reached. All the finders based in configuration space struggled to recover substructure that was located close to the centre of the host halo and the radial dependence of the mass recovered varies from finder to finder. Those finders based in phase space could resolve central substructure although they found difficulties in accurately recovering its properties. Via a resolution study we found that most of the finders could not reliably recover substructure containing fewer than 30-40 particles. However, also here the phase space finders excelled by resolving substructure down to 10-20 particles. By comparing the halo finders using a high resolution cosmological volume we found that they agree remarkably well on fundamental properties of astrophysical significance (e.g. mass, position, velocity, and peak of the rotation curve).Comment: 27 interesting pages, 20 beautiful figures, and 4 informative tables accepted for publication in MNRAS. The high-resolution version of the paper as well as all the test cases and analysis can be found at the web site http://popia.ft.uam.es/HaloesGoingMA

Evolutionary computation based on nanocomposite training: application to data classification

Research into novel materials and computation frameworks by-passing the limitations of the current paradigm, has been identified as crucial for the development of the next generation of computing technology. Within this context, evolution in materio (EiM) proposes an approach where evolutionary algorithms (EAs) are used to explore and exploit the properties of un-configured materials until they reach a state where they can perform a computational task. Following an EiM approach, this thesis demonstrates the ability of EAs to evolve dynamic nanocomposites into data classifiers. Material-based computation is treated as an optimisation problem with a hybrid search space consisting of configuration voltages creating an electric field applied to the material, and the infinite space of possible states the material can reach in response to this field. In a first set of investigations, two different algorithms, differential evolution (DE) and particle swarm optimisation (PSO), are used to evolve single-walled carbon nanotube (SWCNT) / liquid crystal (LC) composites capable of classifying artificial, two-dimensional, binary linear and non-linear separable and merged datasets at low SWCNT concentrations. The difference in search behaviour between the two algorithms is found to affect differently the composite’ state during training, which in turn affects the accuracy, consistency and generalisation of evolved solutions. SWCNT/LC processors are also able to scale to complex, real-life classification problems. Crucially, results suggest that problem complexity influences the properties of the processors. For more complex problems, networks of SWCNT structures tend to form within the composite, creating stable devices requiring no configuration voltages to classify data, and with computational capabilities that can be recovered more than several hours after training. A method of programming the dynamic composites is demonstrated, based on the reapplication of sequences of configuration voltages which have produced good quality SWCNT/LC classifiers. A second set of investigations aims at exploiting the properties presented by the dynamic nanocomposites, whilst also providing a means for evolved device encapsulation, making their use easier in out-of-the lab applications. Novel composites based on SWCNTs dispersed in one-part UV-cure epoxies are introduced. Results obtained with these composites support their choice for use in subsequent EiM research. A final discussion is concerned with evolving an electro-biological processor and a memristive processor. Overall, the work reported in the thesis suggests that dynamic nanocomposites present a number of unexpected, potentially attractive properties not found in other materials investigated in the context of EiM

Multiscale Modeling of Cardiac Electrophysiology: Adaptation to Atrial and Ventricular Rhythm Disorders and Pharmacological Treatment

Multiscale modeling of cardiac electrophysiology helps to better understand the underlying mechanisms of atrial fibrillation, acute cardiac ischemia and pharmacological treatment. For this purpose, measurement data reflecting these conditions have to be integrated into models of cardiac electrophysiology. Several methods for this model adaptation are introduced in this thesis. The resulting effects are investigated in multiscale simulations ranging from the ion channel up to the body surface

Water quality modeling of Lake Diefenbaker

Lake Diefenbaker is one of the most important sources of water in the prairie province of Saskatchewan, Canada. It is a long (181.6 km) and narrow (maximum width 6 km) reservoir formed along the South Saskatchewan River by the construction of the Gardiner and Qu'Appelle River dams in the 1960s. The reservoir has a surface elevation of 556.87 meters above sea level (full supply level) with a maximum depth of 60 m, a surface area of approximately 393 km2 and a volume of 9.03 km3. The reservoir and dams are part of a multipurpose hydraulic project, which provides water for irrigation, drinking water, eco-services, hydropower generation, aquaculture and recreation as well as for flood mitigation. Surface water quality modeling is a useful tool to simulate and predict nutrient dynamics in lakes, reservoirs, and rivers, as well as the fate and transport of sediment and toxic contaminants in freshwater environments. In this study, water quality modeling of Lake Diefenbaker was carried out in order to help understand the mixing regimes and biological processes in the aquatic environment of this strategic reservoir. Based on the study's objectives, the physical and chemical characteristics of the lake and available data, the laterally-averaged two-dimensional model CE-QUAL-W2 hydrodynamic and water quality model was deemed the best model for Lake Diefenbaker. CE-QUAL-W2 was developed by the US Army Corp of Engineers to simulate the hydrodynamics, water quality, aquatic biology and aquatic chemistry in surface waters. On the one hand, this study provided information on temperature and hydrodynamic behaviors of Lake Diefenbaker as well as sediment and nutrient transport, nutrient uptake and algal activities. On the other hand, it addressed some key and limitations in the application of water quality models. Limitations addressed include studying snow cover effects on the ice surface in winter, applying variable algal stoichiometry, using combined local/global optimization for model calibration, and running the model on High-Performance Cluster (HPC) systems

Recent Advances in Multi Robot Systems

To design a team of robots which is able to perform given tasks is a great concern of many members of robotics community. There are many problems left to be solved in order to have the fully functional robot team. Robotics community is trying hard to solve such problems (navigation, task allocation, communication, adaptation, control, ...). This book represents the contributions of the top researchers in this field and will serve as a valuable tool for professionals in this interdisciplinary field. It is focused on the challenging issues of team architectures, vehicle learning and adaptation, heterogeneous group control and cooperation, task selection, dynamic autonomy, mixed initiative, and human and robot team interaction. The book consists of 16 chapters introducing both basic research and advanced developments. Topics covered include kinematics, dynamic analysis, accuracy, optimization design, modelling, simulation and control of multi robot systems

MATLAB

A well-known statement says that the PID controller is the "bread and butter" of the control engineer. This is indeed true, from a scientific standpoint. However, nowadays, in the era of computer science, when the paper and pencil have been replaced by the keyboard and the display of computers, one may equally say that MATLAB is the "bread" in the above statement. MATLAB has became a de facto tool for the modern system engineer. This book is written for both engineering students, as well as for practicing engineers. The wide range of applications in which MATLAB is the working framework, shows that it is a powerful, comprehensive and easy-to-use environment for performing technical computations. The book includes various excellent applications in which MATLAB is employed: from pure algebraic computations to data acquisition in real-life experiments, from control strategies to image processing algorithms, from graphical user interface design for educational purposes to Simulink embedded systems

Biomedical Sensing and Imaging

This book mainly deals with recent advances in biomedical sensing and imaging. More recently, wearable/smart biosensors and devices, which facilitate diagnostics in a non-clinical setting, have become a hot topic. Combined with machine learning and artificial intelligence, they could revolutionize the biomedical diagnostic field. The aim of this book is to provide a research forum in biomedical sensing and imaging and extend the scientific frontier of this very important and significant biomedical endeavor