A prediction of bone remodeling thanks to a mechanical signal on cells - Predizione del rimodellamento osseo a partire da un segnale meccanico sulle cellule

This text wants to explore the process of bone remodeling. The idea supported is that the signal, the cells acquire and which suggest them to change in their architectural conformation, is the potential difference on the free boundaries surfaces of collagen fibers. These ones represent the bone in the nanoscale. This work has as subject a multiscale model. Lots of studies have been made to try to discover the relationship between a macroscopic external bone load and the cellular scale. The tree first simulations have been a longitudinal, a flexion and a transversal compression force on a full longitudinal fiber 0-0 sample. The results showed first the great difference between a fully longitudinal stress and a flexion stress. Secondly a decrease in the potential difference has been observed in the transversal force configuration, suggesting that such a signal could be taken as the one, who leads the bone remodeling. To also exclude that the obtained results was not to attribute to a piezoelectric collagen effect and not to a mechanical load, different coupling analyses have been developed. Such analyses show this effect is really less important than the one the mechanical load is responsible of. At this point the work had to explore how bone remodeling could develop. The analyses involved different geometry and fibers percentage. Moreover at the beginning the model was to manually implement. The author, after an initial improvement of it, provided to implement a standalone version thanks to integration between Comsol Multiphysic, Matlab and Excel.

Analog Signal Acquisition and Conditioning for Near-Field Capacitive Communication and Active Combined EEG-EIT Monitoring

The work of the present thesis is focused on the implementation of microelectronic voltage sensing devices, with the purpose of transmitting and extracting analog information between devices of different nature at short distances or upon contact. Initally, chip-to-chip communication has been studied, and circuitry for 3D capacitive coupling has been implemented. Such circuits allow the communication between dies fabricated in different technologies. Due to their novelty, they are not standardized and currently not supported by standard CAD tools. In order to overcome such burden, a novel approach for the characterization of such communicating links has been proposed. This results in shorter design times and increased accuracy. Communication between an integrated circuit (IC) and a probe card has been extensively studied as well. Today wafer probing is a costly test procedure with many drawbacks, which could be overcome by a different communication approach such as capacitive coupling. For this reason wireless wafer probing has been investigated as an alternative approach to standard on-contact wafer probing. Interfaces between integrated circuits and biological systems have also been investigated. Active electrodes for simultaneous electroencephalography (EEG) and electrical impedance tomography (EIT) have been implemented for the first time in a 0.35 um process. Number of wires has been minimized by sharing the analog outputs and supply on a single wire, thus implementing electrodes that require only 4 wires for their operation. Minimization of wires reduces the cable weight and thus limits the patient's discomfort. The physical channel for communication between an IC and a biological medium is represented by the electrode itself. As this is a very crucial point for biopotential acquisitions, large efforts have been carried in order to investigate the different electrode technologies and geometries and an electromagnetic model is presented in order to characterize the properties of the electrode to skin interface.

Ultra-low power WSNs: distributed signal processing and dynamic resource management

This thesis presents several data processing and compression techniques capable of addressing the strict requirements of wireless sensor networks. After introducing a general overview of sensor networks, the energy problem is introduced, dividing the different energy reduction approaches according to the different subsystem they try to optimize. To manage the complexity brought by these techniques, a quick overview of the most common middlewares for WSNs is given, describing in detail SPINE2, a framework for data processing in the node environment. The focus is then shifted on the in-network aggregation techniques, used to reduce data sent by the network nodes trying to prolong the network lifetime as long as possible. Among the several techniques, the most promising approach is the Compressive Sensing (CS). To investigate this technique, a practical implementation of the algorithm is compared against a simpler aggregation scheme, deriving a mixed algorithm able to successfully reduce the power consumption. The analysis moves from compression implemented on single nodes to CS for signal ensembles, trying to exploit the correlations among sensors and nodes to improve compression and reconstruction quality. The two main techniques for signal ensembles, Distributed CS (DCS) and Kronecker CS (KCS), are introduced and compared against a common set of data gathered by real deployments. The best trade-off between reconstruction quality and power consumption is then investigated. The usage of CS is also addressed when the signal of interest is sampled at a Sub-Nyquist rate, evaluating the reconstruction performance. Finally the group sparsity CS (GS-CS) is compared to another well-known technique for reconstruction of signals from an highly sub-sampled version. These two frameworks are compared again against a real data-set and an insightful analysis of the trade-off between reconstruction quality and lifetime is given.

Efficient ultrasonic signal processing techniques for aided medical diagnostics

Ultrasound imaging is widely used in medical diagnostics as it is the fastest, least invasive, and least expensive imaging modality. However, ultrasound images are intrinsically difficult to be interpreted. In this scenario, Computer Aided Detection (CAD) systems can be used to support physicians during diagnosis providing them a second opinion. This thesis discusses efficient ultrasound processing techniques for computer aided medical diagnostics, focusing on two major topics: (i) Ultrasound Tissue Characterization (UTC), aimed at characterizing and differentiating between healthy and diseased tissue; (ii) Ultrasound Image Segmentation (UIS), aimed at detecting the boundaries of anatomical structures to automatically measure organ dimensions and compute clinically relevant functional indices. Research on UTC produced a CAD tool for Prostate Cancer detection to improve the biopsy protocol. In particular, this thesis contributes with: (i) the development of a robust classification system; (ii) the exploitation of parallel computing on GPU for real-time performance; (iii) the introduction of both an innovative Semi-Supervised Learning algorithm and a novel supervised/semi-supervised learning scheme for CAD system training that improve system performance reducing data collection effort and avoiding collected data wasting. The tool provides physicians a risk map highlighting suspect tissue areas, allowing them to perform a lesion-directed biopsy. Clinical validation demonstrated the system validity as a diagnostic support tool and its effectiveness at reducing the number of biopsy cores requested for an accurate diagnosis. For UIS the research developed a heart disease diagnostic tool based on Real-Time 3D Echocardiography. Thesis contributions to this application are: (i) the development of an automated GPU based level-set segmentation framework for 3D images; (ii) the application of this framework to the myocardium segmentation. Experimental results showed the high efficiency and flexibility of the proposed framework. Its effectiveness as a tool for quantitative analysis of 3D cardiac morphology and function was demonstrated through clinical validation.

Diagnosis and Fault detection in Electrical Machines and Drives based on Advanced Signal Processing Techniques

In the present thesis, a new methodology of diagnosis based on advanced use of time-frequency technique analysis is presented. More precisely, a new fault index that allows tracking individual fault components in a single frequency band is defined. More in detail, a frequency sliding is applied to the signals being analyzed (currents, voltages, vibration signals), so that each single fault frequency component is shifted into a prefixed single frequency band. Then, the discrete Wavelet Transform is applied to the resulting signal to extract the fault signature in the frequency band that has been chosen. Once the state of the machine has been qualitatively diagnosed, a quantitative evaluation of the fault degree is necessary. For this purpose, a fault index based on the energy calculation of approximation and/or detail signals resulting from wavelet decomposition has been introduced to quantify the fault extend. The main advantages of the developed new method over existing Diagnosis techniques are the following: - Capability of monitoring the fault evolution continuously over time under any transient operating condition; - Speed/slip measurement or estimation is not required; - Higher accuracy in filtering frequency components around the fundamental in case of rotor faults; - Reduction in the likelihood of false indications by avoiding confusion with other fault harmonics (the contribution of the most relevant fault frequency components under speed-varying conditions are clamped in a single frequency band); - Low memory requirement due to low sampling frequency; - Reduction in the latency of time processing (no requirement of repeated sampling operation).

Sparse Signal Representation of Ultrasonic Signals for Structural Health Monitoring Applications

Assessment of the integrity of structural components is of great importance for aerospace systems, land and marine transportation, civil infrastructures and other biological and mechanical applications. Guided waves (GWs) based inspections are an attractive mean for structural health monitoring. In this thesis, the study and development of techniques for GW ultrasound signal analysis and compression in the context of non-destructive testing of structures will be presented. In guided wave inspections, it is necessary to address the problem of the dispersion compensation. A signal processing approach based on frequency warping was adopted. Such operator maps the frequencies axis through a function derived by the group velocity of the test material and it is used to remove the dependence on the travelled distance from the acquired signals. Such processing strategy was fruitfully applied for impact location and damage localization tasks in composite and aluminum panels. It has been shown that, basing on this processing tool, low power embedded system for GW structural monitoring can be implemented. Finally, a new procedure based on Compressive Sensing has been developed and applied for data reduction. Such procedure has also a beneficial effect in enhancing the accuracy of structural defects localization. This algorithm uses the convolutive model of the propagation of ultrasonic guided waves which takes advantage of a sparse signal representation in the warped frequency domain. The recovery from the compressed samples is based on an alternating minimization procedure which achieves both an accurate reconstruction of the ultrasonic signal and a precise estimation of waves time of flight. Such information is used to feed hyperbolic or elliptic localization procedures, for accurate impact or damage localization.

Bottle microresonators for applications in quantum optics and all-optical signal processing

This thesis reports on the experimental realization, characterization and application of a novel microresonator design. The so-called “bottle microresonator” sustains whispering-gallery modes in which light fields are confined near the surface of the micron-sized silica structure by continuous total internal reflection. While whispering-gallery mode resonators in general exhibit outstanding properties in terms of both temporal and spatial confinement of light fields, their monolithic design makes tuning of their resonance frequency difficult. This impedes their use, e.g., in cavity quantum electrodynamics (CQED) experiments, which investigate the interaction of single quantum mechanical emitters of predetermined resonance frequency with a cavity mode. In contrast, the highly prolate shape of the bottle microresonators gives rise to a customizable mode structure, enabling full tunability. The thesis is organized as follows: In chapter I, I give a brief overview of different types of optical microresonators. Important quantities, such as the quality factor Q and the mode volume V, which characterize the temporal and spatial confinement of the light field are introduced. In chapter II, a wave equation calculation of the modes of a bottle microresonator is presented. The intensity distribution of different bottle modes is derived and their mode volume is calculated. A brief description of light propagation in ultra-thin optical fibers, which are used to couple light into and out of bottle modes, is given as well. The chapter concludes with a presentation of the fabrication techniques of both structures. Chapter III presents experimental results on highly efficient, nearly lossless coupling of light into bottle modes as well as their spatial and spectral characterization. Ultra-high intrinsic quality factors exceeding 360 million as well as full tunability are demonstrated. In chapter IV, the bottle microresonator in add-drop configuration, i.e., with two ultra-thin fibers coupled to one bottle mode, is discussed. The highly efficient, nearly lossless coupling characteristics of each fiber combined with the resonator's high intrinsic quality factor, enable resonant power transfers between both fibers with efficiencies exceeding 90%. Moreover, the favorable ratio of absorption and the nonlinear refractive index of silica yields optical Kerr bistability at record low powers on the order of 50 µW. Combined with the add-drop configuration, this allows one to route optical signals between the outputs of both ultra-thin fibers, simply by varying the input power, thereby enabling applications in all-optical signal processing. Finally, in chapter V, I discuss the potential of the bottle microresonator for CQED experiments with single atoms. Its Q/V-ratio, which determines the ratio of the atom-cavity coupling rate to the dissipative rates of the subsystems, aligns with the values obtained for state-of-the-art CQED microresonators. In combination with its full tunability and the possibility of highly efficient light transfer to and from the bottle mode, this makes the bottle microresonator a unique tool for quantum optics applications.

Antigen-dependent induction of a CD40 signal in peripheral B cells

Monoclonal antibodies have emerged as one of the most promising therapeutics in oncology over the last decades. The generation of fully human tumorantigen-specific antibodies suitable for anti-tumor therapy is laborious and difficult to achieve. Autoreactive B cells expressing those antibodies are detectable in cancer patients and represent a suitable source for human antibodies. However, the isolation and cultivation of this cell type is challenging. A novel method was established to identify antigen-specific B cells. The method is based on the conversion of the antigen independent CD40 signal into an antigen-specific one. For that, the artificial fusion proteins ABCos1 and ABCos2 (Antigen-specific B cell co-stimulator) were generated, which consist of an extracellular association-domain derived from the constant region of the human immunoglobulin (Ig) G1, a transmembrane fragment and an intracellular signal transducer domain derived of the cytoplasmic domain of the human CD40 receptor. By the association with endogenous Ig molecules the heterodimeric complex allows the antigen-specific stimulation of both the BCR and CD40. In this work the ability of the ABCos constructs to associate with endogenous IgG molecules was shown. Moreover, crosslinking of ABCos stimulates the activation of NF-κB in HEK293-lucNifty and induces proliferation in B cells. The stimulation of ABCos in transfected B cells results in an activation pattern different from that induced by the conventional CD40 signal. ABCos activated B cells show a mainly IgG isotype specific activation of memory B cells and are characterized by high proliferation and the differentiation into plasma cells. To validate the approach a model system was conducted: B cells were transfected with IVT-RNA encoding for anti-Plac1 B cell receptor (antigen-specific BCR), ABCos or both. The stimulation with the BCR specific Plac1 peptide induces proliferation only in the cotransfected B cell population. Moreover, we tested the method in human IgG+ memory B cells from CMV infected blood donors, in which the stimulation of ABCos transfected B cells with a CMV peptide induces antigen-specific expansion. These findings show that challenging ABCos transfected B cells with a specific antigen results in the activation and expansion of antigen-specific B cells and not only allows the identification but also cultivation of these B cells. The described method will help to identify antigen-specific B cells and can be used to characterize (tumor) autoantigen-specific B cells and allows the generation of fully human antibodies that can be used as diagnostic tool as well as in cancer therapy.

Implementation of a VLSI amplifier interfaced with biomedical sensors for ultra wide band data transmission

This thesis presents a CMOS Amplifier with High Common Mode rejection designed in UMC 130nm technology. The goal is to achieve a high amplification factor for a wide range of biological signals (with frequencies in the range of 10Hz-1KHz) and to reject the common-mode noise signal. It is here presented a Data Acquisition System, composed of a Delta-Sigma-like Modulator and an antenna, that is the core of a portable low-complexity radio system; the amplifier is designed in order to interface the data acquisition system with a sensor that acquires the electrical signal. The Modulator asynchronously acquires and samples human muscle activity, by sending a Quasi-Digital pattern that encodes the acquired signal. There is only a minor loss of information translating the muscle activity using this pattern, compared to an encoding technique which uses astandard digital signal via Impulse-Radio Ultra-Wide Band (IR-UWB). The biological signals, needed for Electromyographic analysis, have an amplitude of 10-100μV and need to be highly amplified and separated from the overwhelming 50mV common mode noise signal. Various tests of the firmness of the concept are presented, as well the proof that the design works even with different sensors, such as Radiation measurement for Dosimetry studies.

Progettazione ed implementazione di un dispositivo portabile per l'acquisizione ed il filtraggio di segnali biomedici

The use of wearable devices for the monitoring of biological potentials is an ever-growing area of research. Wearable devices for the monitoring of vital signs such as heart-rate, respiratory rate, cardiac output and blood oxygenation are necessary in determining the overall health of a patient and allowing earlier detection of adverse events such as heart attacks and strokes and earlier diagnosis of disease. This thesis describes a bio-potential acquisition embedded system designed with an innovative analog front-end, showing the performance in EMG and ECG applications and the comparison between different noise reduction algorithms. We demonstrate that the proposed system is able to acquire bio-potentials with a signal quality equivalent to state of the art bench-top biomedical devices and can be therefore used for monitoring purpose, with the advantages of a low-cost low-power wearable device.

Diagnostic performance and accuracy of 3-D spoiled gradient-dual-echo MRI with water- and fat-signal separation in liver-fat quantification: comparison to liver biopsy

To prospectively evaluate a 3-dimensional spoiled gradient-dual-echo (3D SPGR-DE) magnetic resonance imaging (MRI) sequence for the qualitative and quantitative analysis of liver fat content (LFC) in patients with the suspicion of fatty liver disease using histopathology as the standard of reference.

Recurrent non-melanoma skin cancer: remission of field cancerization after conversion from calcineurin inhibitor- to proliferation signal inhibitor-based immunosuppression in a cardiac transplant recipient

Non-melanoma skin cancers (NMSCs) are the most common malignancies after solid organ transplantation. Their incidence increases with time after transplantation. Calcineurin-inhibitors (CNIs) and azathioprine are known as skin neoplasia-initiating and -enhancing immunosuppressants. In contrast, increasing clinical experience suggests a relevant antiproliferative effect of mammalian target of rapamycin inhibitors, also named proliferation signal inhibitors (PSIs). We report the case of a cardiac allograft recipient with an impressive and consolidated reduction of recurrent NMSC, observed after conversion from CNI-therapy to a PSI-based protocol.

Effect of selective dorsal rhizotomy on gait in children with bilateral spastic paresis: kinematic and EMG-pattern changes

Selective dorsal rhizotomy (SDR) is an effective treatment for reducing spasticity and improving gait in children with spastic cerebral palsy. Data concerning muscle activity changes after SDR treatment are limited.