Microfabricated elastomer tactile sensors for robotic fingertip systems

Tactile sensing is an important aspect of robotic systems, and enables safe, dexterous robot-environment interaction. The design and implementation of tactile sensors on robots has been a topic of research over the past 30 years, and current challenges include mechanically flexible “sensing skins”, high dynamic range (DR) sensing (i.e.: high force range and fine force resolution), multi-axis sensing, and integration between the sensors and robot. This dissertation focuses on addressing some of these challenges through a novel manufacturing process that incorporates conductive and dielectric elastomers in a reusable, multilength-scale mold, and new sensor designs for multi-axis sensing that improve force range without sacrificing resolution. A single taxel was integrated into a 1 degree of freedom robotic gripper for closed-loop slip detection. Manufacturing involved casting a composite silicone rubber, polydimethylsiloxane (PDMS) filled with conductive particles such as carbon nanotubes, into a mold to produce microscale flexible features on the order of 10s of microns. Molds were produced via microfabrication of silicon wafers, but were limited in sensing area and were costly. An improved technique was developed that produced molds of acrylic using a computer numerical controlled (CNC) milling machine. This maintained the ability to produce microscale features, and increased the sensing area while reducing costs. New sensing skins had features as small as 20 microns over an area as large as a human hand. Sensor architectures capable of sensing both shear and normal force sensing with high dynamic range were produced. Using this architecture, two sensing modalities were developed: a capacitive approach and a contact resistive approach. The capacitive approach demonstrated better dynamic range, while the contact resistive approach used simpler circuitry. Using the contact resistive approach, normal force range and resolution were 8,000 mN and 1,000 mN, respectively, and shear force range and resolution were 450 mN and 100 mN, respectively. Using the capacitive approach, normal force range and resolution were 10,000 mN and 100 mN, respectively, and shear force range and resolution were 1,500 mN and 50 mN, respectively.

Intelligent system for interaction with virtual characters based on volumetric sensors

Dissertação de Mestrado, Engenharia Elétrica e Eletrónica, Instituto Superior de Engenharia, Universidade do Algarve, 2015

Platinum supported on highly-dispersed ceria on activated carbon for the total oxidation of VOCs

Catalysts consisting in platinum supported on cerium oxide highly dispersed on activated carbon, with a Pt loading of 1 wt.% and ceria loadings of 5, 10 and 20 wt.% have been prepared by impregnation method and characterized by several techniques (N2 adsorption at 77 K, ICP, XRD, H2-TPR and XPS). Their catalytic behavior has been evaluated in the total oxidation of ethanol and toluene after reduction at 473 K. The obtained results show that the prepared catalysts have better performances than platinum supported on bulk CeO2. The best catalytic performance was obtained for 10 wt.% ceria loading, likely due to an optimum synergistic interaction between highly dispersed cerium oxide and platinum particles. Pt-10Ce/C achieves total conversion of ethanol and toluene to CO2 at 433 K and 453 K, respectively, and shows no deactivation during a test for 100 h. Under humid conditions (relative humidity, RH, of 40 and 80%), the activity was only slightly influenced due to the hydrophobic character of the activated carbon support, which prevents the adsorption of water.

DESIGN AND APPLICATION OF WIRELESS PASSIVE MAGNETOELASTIC RESONANCE AND MAGNETOHARMONIC FORCE SENSORS

The objective of the work described in this dissertation is the development of new wireless passive force monitoring platforms for applications in the medical field, specifically monitoring lower limb prosthetics. The developed sensors consist of stress sensitive, magnetically soft amorphous metallic glass materials. The first technology is based on magnetoelastic resonance. Specifically, when exposed to an AC excitation field along with a constant DC bias field, the magnetoelastic material mechanically vibrates, and may reaches resonance if the field frequency matches the mechanical resonant frequency of the material. The presented work illustrates that an applied loading pins portions of the strip, effectively decreasing the strip length, which results in an increase in the frequency of the resonance. The developed technology is deployed in a prototype lower limb prosthetic sleeve for monitoring forces experienced by the distal end of the residuum. This work also reports on the development of a magnetoharmonic force sensor comprised of the same material. According to the Villari effect, an applied loading to the material results in a change in the permeability of the magnetic sensor which is visualized as an increase in the higher-order harmonic fields of the material. Specifically, by applying a constant low frequency AC field and sweeping the applied DC biasing field, the higher-order harmonic components of the magnetic response can be visualized. This sensor technology was also instrumented onto a lower limb prosthetic for proof of deployment; however, the magnetoharmonic sensor illustrated complications with sensor positioning and a necessity to tailor the interface mechanics between the sensing material and the surface being monitored. The novelty of these two technologies is in their wireless passive nature which allows for long term monitoring over the life time of a given device. Additionally, the developed technologies are low cost. Recommendations for future works include improving the system for real-time monitoring, useful for data collection outside of a clinical setting.

Microstructured polymer optical fibre sensors for opto-acoustic endoscopy

Opto-acoustic imaging is a growing field of research in recent years, providing functional imaging of physiological biomarkers, such as the oxygenation of haemoglobin. Piezo electric transducers are the industry standard detector for ultrasonics, but their limited bandwidth, susceptibility to electromagnetic interference and their inversely proportional sensitivity to size all affect the detector performance. Sensors based on polymer optical fibres (POF) are immune to electromagnetic interference, have lower acoustic impedance and a reduced Young's Modulus compared to silica fibres. Furthermore, POF enables the possibility of a wideband sensor and a size appropriate to endoscopy. Micro-structured POF (mPOF) used in an interferometric detector has been shown to be an order of magnitude more sensitive than silica fibre at 1 MHz and 3 times more sensitive at 10 MHz. We present the first opto-acoustic measurements obtained using a 4.7mm PMMA mPOF Bragg grating with a fibre diameter of 130 μm and present the lateral directivity pattern of a PMMA mPOF FBG ultrasound sensor over a frequency range of 1-50 MHz. We discuss the impact of the pattern with respect to the targeted application and draw conclusions on how to mitigate the problems encountered.

Non-invasive winding fault detection for induction machines based on stray flux magnetic sensors

Non-intrusive monitoring of health state of induction machines within industrial process and harsh environments poses a technical challenge. In the field, winding failures are a major fault accounting for over 45% of total machine failures. In the literature, many condition monitoring techniques based on different failure mechanisms and fault indicators have been developed where the machine current signature analysis (MCSA) is a very popular and effective method at this stage. However, it is extremely difficult to distinguish different types of failures and hard to obtain local information if a non-intrusive method is adopted. Typically, some sensors need to be installed inside the machines for collecting key information, which leads to disruption to the machine operation and additional costs. This paper presents a new non-invasive monitoring method based on GMRs to measure stray flux leaked from the machines. It is focused on the influence of potential winding failures on the stray magnetic flux in induction machines. Finite element analysis and experimental tests on a 1.5-kW machine are presented to validate the proposed method. With time-frequency spectrogram analysis, it is proven to be effective to detect several winding faults by referencing stray flux information. The novelty lies in the implement of GMR sensing and analysis of machine faults.

Properties of polycrystalline gas sensors based on d.c. and a.c. electrical measurements

Electrical properties of polycrystalline gas sensors are analyzed by d.c. and a.c. measurements. d.c. electrical conductivity values compared with those obtained by admittance spectroscopy methods help to obtain a detailed 'on line' analysis of conductivity-modulated gas sensors. The electrical behaviour of grain boundaries is obtained and a new design of sensors can be achieved by enhancing the activity of surface states in the detecting operation. A Schottky barrier model is used to explain the grain boundary action under the presence of surrounding gases. The height of this barrier is a function of gas concentration due to the trapping of excess charge generated by gas adsorption at the interface. A comparison between this dependence, and a plot of the real and imaginary components of the admittance versus frequency at different gas concentrations, provides information on the different parameters that play a role in the conduction mechanisms. These methods have been applied to the design of a CO sensor based on tin oxide films for domestic purposes, the characteristics of which are presented.

Energy harvesting from hydroelectric systems for remote sensors

Hydroelectric systems are well-known for large scale power generation. However, there are virtually no studies on energy harvesting with these systems to produce tens or hundreds of milliwatts. The goal of this work was to study which design parameters from large-scale systems can be applied to small-scale systems. Two types of hydro turbines were evaluated. The first one was a Pelton turbine which is suitable for high heads and low flow rates. The second one was a propeller turbine used for low heads and high flow rates. Several turbine geometries and nozzle diameters were tested for the Pelton system. For the propeller, a three-bladed turbine was tested for different heads and draft tubes. The mechanical power provided by these turbines was measured to evaluate the range of efficiencies of these systems. A small three-phase generator was developed for coupling with the turbines in order to evaluate the generated electric power. Selected turbines were used to test battery charging with hydroelectric systems and a comparison between several efficiencies of the systems was made. Keywords

Machine learning techniques for implicit interaction using mobile sensors

Interactions in mobile devices normally happen in an explicit manner, which means that they are initiated by the users. Yet, users are typically unaware that they also interact implicitly with their devices. For instance, our hand pose changes naturally when we type text messages. Whilst the touchscreen captures finger touches, hand movements during this interaction however are unused. If this implicit hand movement is observed, it can be used as additional information to support or to enhance the users’ text entry experience. This thesis investigates how implicit sensing can be used to improve existing, standard interaction technique qualities. In particular, this thesis looks into enhancing front-of-device interaction through back-of-device and hand movement implicit sensing. We propose the investigation through machine learning techniques. We look into problems on how sensor data via implicit sensing can be used to predict a certain aspect of an interaction. For instance, one of the questions that this thesis attempts to answer is whether hand movement during a touch targeting task correlates with the touch position. This is a complex relationship to understand but can be best explained through machine learning. Using machine learning as a tool, such correlation can be measured, quantified, understood and used to make predictions on future touch position. Furthermore, this thesis also evaluates the predictive power of the sensor data. We show this through a number of studies. In Chapter 5 we show that probabilistic modelling of sensor inputs and recorded touch locations can be used to predict the general area of future touches on touchscreen. In Chapter 7, using SVM classifiers, we show that data from implicit sensing from general mobile interactions is user-specific. This can be used to identify users implicitly. In Chapter 6, we also show that touch interaction errors can be detected from sensor data. In our experiment, we show that there are sufficient distinguishable patterns between normal interaction signals and signals that are strongly correlated with interaction error. In all studies, we show that performance gain can be achieved by combining sensor inputs.

Energy harvesting from hydroelectric systems for remote sensors

Hydroelectric systems are well-known for large scale power generation. However, there are virtually no studies on energy harvesting with these systems to produce tens or hundreds of milliwatts. The goal of this work was to study which design parameters from large-scale systems can be applied to small-scale systems. Two types of hydro turbines were evaluated. The first one was a Pelton turbine which is suitable for high heads and low flow rates. The second one was a propeller turbine used for low heads and high flow rates. Several turbine geometries and nozzle diameters were tested for the Pelton system. For the propeller, a three-bladed turbine was tested for different heads and draft tubes. The mechanical power provided by these turbines was measured to evaluate the range of efficiencies of these systems. A small three-phase generator was developed for coupling with the turbines in order to evaluate the generated electric power. Selected turbines were used to test battery charging with hydroelectric systems and a comparison between several efficiencies of the systems was made. Keywords

Evaluation of DUALEM, OptRx and Grassmaster II sensors for monitoring the spatial variability and the temporal stability of a Mediterranean pasture

Site-specific management (SSM) is a form of precision agriculture whereby decisions on resource application and agronomic practices are improved to better match soil and crop requirements as they vary in the field. SSM enables the identification of regions (homogeneous management zones) within the area delimited by field boundaries. These subfield regions constitute areas that have similar permanent characteristics. Traditional soil and pasture sampling and the necessary laboratory analysis are time-consuming, labour-intensive and cost prohibitive, not viable from a SSM perspective because it needs a large number of soil and pasture samples in order to achieve a good representation of soil properties, nutrient levels and pasture quality and productivity. The main objective of this work was to evaluate technologies which have potential for monitoring aspects related to spatial and temporal variability of soil nutrients and pasture green and dry matter yield (respectively, GM and DM, in kg/ha) and support to decision making for the farmer. Three types of sensors were evaluated in a 7ha pasture experimental field: an electromagnetic induction sensor (“DUALEM 1S”, which measures the soil apparent electrical conductivity, ECa), an active optical sensor ("OptRx®", which measures the NDVI, “Normalized Difference Vegetation Index”) and a capacitance probe ("GrassMaster II" which estimates plant mass). The results indicate the possibility of using a soil electrical conductivity probe as, probably, the best tool for monitoring not only some of the characteristics of the soil, but also those of the pasture, which could represent an important help in simplifying the process of sampling and support SSM decision making, in precision agriculture projects. On the other hand, the significant and very strong correlations obtained between capacitance and NDVI and between any of these parameters and the pasture productivity shows the potential of these tools for monitoring the evolution of spatial and temporal patterns of the vegetative growth of biodiverse pasture, for identifying different plant species and variability in pasture yield in Alentejo dry-land farming systems. These results are relevant for the selection of an adequate sensing system for a particular application and open new perspectives for other works that would allow the testing, calibration and validation of the sensors in a wider range of pasture production conditions, namely the extraordinary diversity of botanical species that are characteristic of the Mediterranean region at the different periods of the year.

Inertial and magnetic sensors for upper limb kinematics: modeling, calibration, sensor fusion and clinical applications

The primary aim of the research activity presented in this PhD thesis was the development of an innovative hardware and software solution for creating a unique tool for kinematics and electromyographic analysis of the human body in an ecological setting. For this purpose, innovative algorithms have been proposed regarding different aspects of inertial and magnetic data elaboration: magnetometer calibration and magnetic field mapping (Chapter 2), data calibration (Chapter 3) and sensor-fusion algorithm. Topics that may conflict with the confidentiality agreement between University of Bologna and NCS Lab will not be covered in this thesis. After developing and testing the wireless platform, research activities were focused on its clinical validation. The first clinical study aimed to evaluate the intra and interobserver reproducibility in order to evaluate three-dimensional humero-scapulo-thoracic kinematics in an outpatient setting (Chapter 4). A second study aimed to evaluate the effect of Latissimus Dorsi Tendon Transfer on shoulder kinematics and Latissimus Dorsi activation in humerus intra - extra rotations (Chapter 5). Results from both clinical studies have demonstrated the ability of the developed platform to enter into daily clinical practice, providing useful information for patients' rehabilitation.

Design and characterization of Electrochemical Sensors for Organic Bioelectronics

This Ph.D. Thesis concerns the design and characterisation of functional electrochemical interfaces in organic electronic devices for bioelectronic applications. The Thesis is structured as follows: Chapter I – Technological context that has inspired the research, introduction to Organic Bioelectronics and literature review concerning Organic Electrochemical Transistors (OECTs) for sensing applications. Chapter II – Working principle of an all-polymeric OECT and operando microscopic characterization using scanning electrochemical techniques. Chapter III – Dopamine detection with all-polymeric OECT sensors. Development of a potentiodynamic approach to address selectivity issues in the presence of interfering species and design of a needle-type, sub-micrometric OECT sensor for spatially resolved detection of biological Dopamine concentrations. Chapter IV – Development of an OECT pH sensor. Characterization of the electrochemical transducer and functionalization of the OECT gate electrode with the sensing material. Potentiodynamic and potentiostatic operation modalities are explored and the sensing performances are assessed in both cases. The final device is realized on a flexible substrate and tested in Artificial Sweat. Chapter V – Study of two-terminal, electrochemically gated sensors inspired by the OECT configuration. Design and characterization of novel functional materials showing a potentiometric transduction of the chemical signal that can be exploited in the realization of electrochemical sensors with simplified geometry for wearable applications. Chapter VI – Conclusion.

Determinazione gascromatografica di composti organici volatili e semi-volatili (VOCs e SVOCs) in poliolefine ed effetti delle condizioni di lavorazione

A relevant problem of polyolefins processing is the presence of volatile and semi-volatile compounds (VOCs and SVOCs) such as linear chains alkanes found out in final products. These VOCs can be detected by customers from the unpleasant smelt and can be an environmental issue, at the same time they can cause negative side effects during process. Since no previously standardized analytical techniques for polymeric matrix are available in bibliography, we have implemented different VOCs extraction methods and gaschromatographic analysis for quali-quantitative studies of such compounds. In literature different procedures can be found including microwave extraction (MAE) and thermo desorption (TDS) used with different purposes. TDS coupled with GC-MS are necessary for the identification of different compounds in the polymer matrix. Although the quantitative determination is complex, the results obtained from TDS/GC-MS show that by-products are mainly linear chains oligomers with even number of carbon in a C8-C22 range (for HDPE). In order to quantify these linear alkanes by-products, a more accurate GC-FID determination with internal standard has been run on MAE extracts. Regardless the type of extruder used, it is difficult to distinguish the effect of the various processes, which in any case entails having a lower-boiling substance content, lower than the corresponding virgin polymer. The two HDPEs studied can be distinguished on the basis of the quantity of analytes found, therefore the production process is mainly responsible for the amount of VOCs and SVOCs observed. The extruder technology used by Sacmi SC allows to obtain a significant reduction in VOCs compared to the conventional screw system. Thus, the result is significantly important as a lower quantity of volatile substances certainly leads to a lower migration of such materials, especially when used for food packaging.

Shoulder kinematic evaluation in patients with rotator cuff tears using inertial and magnetic sensors.

Questo progetto di tesi fa parte di un più ampio studio clinico condotto all’interno dell’azienda NCS Lab (Carpi,(MO)), in collaborazione con il Dr. Claudio Chillemi (ICOT, Latina (RM)) che mira ad eseguire un confronto tra diverse tecniche chirurgiche per la riparazione della cuffia dei rotatori. Lo studio clinico in questione durerà circa due anni: per questo motivo i dati analizzati in questo progetto di tesi provengono solo dal gruppo di pazienti acquisiti nella fase preoperatoria. Tutti i dati sono stati acquisiti utilizzando i sensori magneto-inerziali WISE (tecnologia proprietaria dell’azienda NCS Lab). Questo lavoro di tesi si propone, quindi, di valutare la ripetibilità del movimento in termini di coefficiente di correlazione multipla e di estrapolare alcuni parametri di interesse clinico come, ad esempio, i range di movimento (ROM) della scapola e dell’omero e il ritmo scapolo-omerale (SHR). Questi parametri sono stati poi caratterizzati da un punto di vista statistico al fine di valutare le differenze tra arto patologico e controlaterale. Sono state calcolate, inoltre, le prediction bands con lo scopo di descrivere le differenze tra arto patologico e controlaterale nella coordinazione scapolo-omerale dei pazienti. Per quanto riguarda la ripetibilità del movimento, i risultati ottenuti in questo lavoro di tesi mostrano che la rotazione medio-laterale è caratterizzata da un eccellente CMC sia per l'arto patologico che per il controlaterale. Inoltre, sono state riscontrate differenze significative dal punto di vista statistico tra le distribuzioni dei range di movimento dell'arto patologico e controlaterale. Tali differenze sono state trovate anche per quanto riguarda il ritmo scapolo-omerale.