We have developed a visually based autopilot for Micro Air Vehicles (MAV), which we have called OCTAVE (Optical altitude Control sysTem for Autonomous VEhicles). First we built a miniature MAV and an indoor test-bed. The mini-helicopter is tethered to a whirling arm and rotates around a central pole equipped with ground-truth positioning sensors for experimental evaluation. The 100-gram rotorcraft lifts itself by means of a single rotor that can also be tilted forward (pitch) to give the craft a horizontal thrust component (propulsive force). The helicopter’s eye is automatically oriented downwards over an environment composed of contrasting features randomly arranged on the floor. Here we show the feasibility of a ground avoiding system based on a low complexity opto-electronic system. The latter relies on an Elementary Motion Detector (EMD) that estimates the optic flow in the downward direction. The EMD functional structure is directly inspired by that of the fly’s EMDs, the functional scheme of which has been elucidated at our Laboratory by performing electrophysiological recordings while applying optical microstimuli to the retina. The OCTAVE autopilot makes the aircraft capable of effective terrain following at various speeds: the MAV performs reproducible manoeuvers such as smooth cruise flight over a planar ground and hill climbing. The overall processing electronics is very light-weight, which makes it highly suitable for mounting on-board micro air vehicles with an avionic payload in the order of only a few grams.

The retina is responsible of the treatment of visual information at early stages. Visual stimuli generate patterns of activity that are transmitted through its layered structure up to the ganglion cells that interface it to the optical nerve. In this trip of micrometers, information is sustained by continuous signals that interact in excitatory and inhibitory ways. This low-level processing compresses the relevant information of the images to a manageable size. The behavior of the more external layers of the biological retina has been successfully modelled within the Cellular Neural Network framework. Interactions between cells are realized on a local basic. Each cell interacts with its nearest neighbors and every cell in the same layer follows the same interconnection pattern. Intra- and inter-layer interactions are continuous in magnitude and time. The evolution of the network can be described by a set of coupled nonlinear differential equations. A mixed-signal VLSI implementation of focal-plane low-level image processing based upon this biological model constitutes a feasible and cost effective alternative to conventional digital processing in real-time applications. A CMOS Programmable Array Processor prototype chip has been designed and fabricated in a standard technology. It has been successfully tested, validating the proposed design techniques. The integrated system consists of a network of 2 coupled layers, containing 32×32 elementary processors, running at different time constants. Involved image processing algorithms can be programmed on this chip by tuning the appropriate interconnection weights, internally coded as analog but programmed via a digital interface. Propagative, active wave phenomena and retina-lake effects can be observed in this chip. Low-level image processing tasks for early vision applications can be developed based on these high-order dynamics.

This paper presents an analog CMOS implementation of a neural network based on a spinal cord model. The network is comprised by three pairs of cells, Alpha motorneurons, Interneurons and Renshaw cells, which form the basic control motor system for a single limb movement. Behaviour of each neuron is described by a differential equation, which provides it with a dynamic performance. This network is useful to control limb movements based in an antagonist pair of actuators, i.e. muscles for a human limb or electric motors or SMA fibers for machine applications. This antagonist structure has the main advantage that allows independent control of limb position and stiffness, which makes it suitable for applications where inertial load compensation is a critical factor. For the implementation of the neurons we have developed individual analog operators, like multipliers and integrators, which have been then joined to obtain the cell. The whole circuit works in current mode, and exhibits good performance in power disipation and bandwidth. The implementation of the network has been done in a 0.35um process from AMS. The layout size is 870 × 480 μm and the power dissipation is 14 mW, using a reference voltage of 3.3 volts. The applications in which this network canbe used fall in two broad cathegories. Firstly, in the development of human-machine interfaces capable to be used both in industry and in handicaped people and secondly in the development o neural controller for industrial robots, providing them with a compliance performance.

This paper describes implementation of neural network processing layers using basic current-mode operating modules. The research work has been focused on the implementation of neural networks based on the Adaptive Resonance Theory, developed by S. Grossberg and G.A. Carpenter. The ART-based neural network whose operating modules have been choosen for development is the one called MART, proposed by F. Delgado, because of its complex architecture, auto--adaptive self-learning process, able to discard unmeaningful cathegories. Our presentation starts introducing the behaviour of MART with an analysis of its structure. The development described by this research work is focused on the monochannel block included in the main signal processing part of the MART neural network. The description of the computing algorithm of the layers inside a monochannel block are also provided in order to show what operational current-mode modules are needed (multiplier, divider, square-rooter, adder, substractor, absolute value, maximum and minimum evaluator...). Descriptions at schematic and layout levels of all the processing layers are given. All of them have been designed using AMS 0.35 micron technology with a supply voltage of 3.3 volts. The modules are designed to deal with input currents in the range of 20 to 50 microamps, showing a lineal behaviour and an output error of less than 10%, which is good enough for neural signal processing systems. The maximum frecuency of operation is around 200 kHz. Simulation results are included to show that the operation performed by the hardware designed matches the behaviour described by the MART neural network. For testing purposes we show the design of a monochannel block hardware implementation restricted to five inputs and three cathegories.

Corti’s Organ is an Electro-Mechanical transducer that allows the energy coupling between acoustical stimuli and auditory nerve. Although the structure and funtionality of this organ are complex, state of the art models have been currently developed and tested. Cochlea model presented in this paper is based on the theories of Bekesy and others and concerns on the behaviour of auditory system on frequency-place domain and mechanisms of lateral inhibition. At the same time, present state of technology will permit us developing a microsystem that reproduce this phenomena applied to hearing aid prosthesis. Corti’s Organ is composed of more than 20.000 cilia excited by mean of travelling waves. These waves produce relative pressures distributed along the cochlea, exciting an specific number of cilia in a local way. Nonlinear mechanisms of local adaptation to the intensity (external cilia cells) and lateral inhibition (internal cilia cells) allow the selection of very few elements excited. These transmit a very precise intensity and frequency information. These signals are the only ones coupled to the auditory nerve. Distribution of pressure waves matches a quasilogaritmic law due to Cochlea morphology. Microsystem presented in this paper takes Bark’s law as an approximation to this behaviour consisting on grouped arbitrary elements composed of a set of selective coupled exciters (bank of filters according to Patterson’s model).These sets apply the intensity adaptation principles and lateral inhibition. Elements excited during the process generate a bioelectric signal in the same way than cilia cell. A microelectronic solution is presented for the development of an implantable prosthesis device.

We demonstrate the flexibility of a multiple-beam trapping system that enables interactive manipulation of fluid-borne colloidal structures with advanced controllability and versatility that can lead to light-powered microdevices performing multiple functions in a "lab-on-a-chip". A straightforward phase-imaging operation forms the basis for the efficient generation of arbitrarily shaped trapping beam configurations. The multiple-beam trapping pattern is a direct map of the phase variation encoded on a programmable phase-only spatial light modulator (SLM). A graphical user interface that encodes desired phase patterns onto the SLM enables interactive and independent control over the dynamics and geometry of each trapping beam. Experimental results show that the system can be used for guided assembly of particles in a plane, control of particle stacking along a beam axis, and real-time sorting of inhomogeneous mixtures of microspheres. These experiments illustrate that multiple beams generated by the system can be utilized not only for the improved synthesis of functional microstructures but also for their non-contact and parallel actuation crucial for sophisticated microfluidic-based lab-on-a-chip demonstrations in the future.

A new technique to analyze methylation patterns in several adjacent CpG sites was developed and reported here. We selected a 336bp segment of the 5’-untranslated region and the first exon of the p16Ink4a gene, which include the most densely packed CpG fragment of the islands containing 32 CpG dinucleotides, as the investigated target. The probes that include all types of methylation patterns were designed to fabricate a DNA microarray to determine the methylation patterns of seven adjacent CpG dinucleotides sites. High accuracy and reproducibility were observed in several parallel experiments. The results led us to the conclusion that the methylation oligonucleotide microarray can be applied as a novel and powerful tool to map methylation patterns and changes in multiple CpG island loci in a variety of tumors.

The basic advantage of the microfluidic systems is that they enable reducing consumption of biological material and chemicals. But another major advantage of the microfluidic systems, not widely explored so far, is that with feature sizes reduced toward the size of cells, one can easily handle and fix a single cell. The interest of single cell handling and fixing appears when one wants to study biochemical exchanges between single cells or internal biochemical reactions inside an isolated cell. This work uses the shape of the microfluidc device to control the migration and placement of single vegetal cells. Three-dimensional micro-molding and poly-dimethylsiloxane (PDMS) patterning techniques have been used to realize device prototypes. Double-height micro-molds are made of thick negative photoresist (SU8) Experiments have been undergone to optimize fluid rate flow and cell concentration regarding to right cell placement percentage. The PDMS prototypes systems confirm the good operation of the design to migrate cells, place and fix them. The placement rate, even if it is enough for statistical biochemical experiments, will be improved by the use of new material. New material will allow to get rid of air bubbles due to PDMS long-term hydrophobicity that render up to 25% settlement places unserviceable.

In this paper, we present an integrated and automated prototype system which has been developed for real-time polymerase chain reaction (PCR) analysis based on microfluidic PCR array chips. The system integrates the PCR thermal cycling and optical detection capabilities to enable real-time fluorescence imaging and image processing for data analysis. The main advantage of the system is that it provides a solution that can rapidly perform and evaluate PCR experiment simultaneously on microfluidic PCR array chips. The system has demonstrated fast and efficient on-chip real-time PCR analysis using human genomic DNA samples. The implementation of the system integration is a multi-thread Windows software with component structure which is written in Visual C++.

We propose a method for studying multi-component liquids based on recording of the dynamics of the acoustic-mechanical impedance (AMI) of a drop that dries up on the surface of a quartz resonator oscillating with ultrasound frequency. The magnitude of the AMI is an integral characteristic of the physical properties of the drop including its viscosity, composition, surface tension, moistening, and inner structure. Using liquids of different types as the example, it is shown that each liquid possesses its individual 'portrait', determined by the character of the phase transitions. In the authers’ opinion, this method can be used for the screening identification of liquids (determining the degree of consistency with the standards) in solving a number of scientific and practical problems, as well as in biology, chemistry, food and drug examination and medicine. Unique scopes of this method in medical diagnostics, vine, food and drug identification and determination of inner structure of solutions are demonstrated.

An optical biosensor based on attenuation of the light intensity during multiple reflections in a planar waveguide has been developed for water pollution monitoring. The planar waveguide consists of a 190 nanometer thick silicon nitride (Si₃N₄) core layer sandwiched between 1.5 micrometer thick silicon dioxide (SiO₂) cladding layers. Composite polyelectrolyte self-assembled membranes containing Cyclotetrachromotropylene (CTCT) as an indicator and enzymes, such as Urease or Acetylcholine Esterase (AChE) were deposited on top of silicon nitride core layer within a 4 × 6 mm sensing window. Experimental studies on the light propagation through the planar waveguide show the advantages of this method over conventional UV-visible absorption spectroscopy. It was found that the planar waveguide sensitivity is higher by several orders of magnitude than that for UV-visible absorption spectroscopy. The respective enzyme reactions as well as their inhibition by heavy metal ions were studied by monitoring the light intensity in the planar waveguide. Cadmium (Cd²⁺) and lead (Pb²⁺) ions were registered in very low concentrations down to 1 ppb with the planar waveguide transducer. The enzymes used were inhibited differently by the above pollutants, which is promising for the development of enzyme sensor arrays.

Two decades ago, the first application of surface plasmon resonance phenomenon (SPR) was presented; from then on the improvement on the sensor instrumentation is the key factor for the system accuracy, opening infinity of derived applications of the new optoelectronics sensors investigation. The high specificity surface plasmon resonance sensor presented is based on two photodiode arrays, one for referential measurement and other for the selective detection of substance. This report shows several solutions that contribute to the optimization of the design of electronic acquisition that treats weak signals in noisy electronic media. The design improvements are based on the minimization of the noise in electronic circuits versus digital signal processing limitations. This work solves the inherent problems in circuits design where photodiodes arrays and analog multiplexer are used by means of the dynamic control of the high gain amplifiers chain offsets in transimpedance classic configuration, in the good adjustment of the ADC measurement spectrum bandwidth and in the compensation in real time, with electronic circuits, of the optical noise effects, as dark currents. This optimization is reached after parameterize the process by means of the device self-calibration that will allow to improve the fidelity of the measures notably, this is essential when the variations of the plasmon sensor refraction index to detect has an order of 1e-6.

Simultaneous mapping of multiple electrical or chemical properties of neural activity facilitates understanding neurological phenomena and their underlying mechanisms. We present a track-and-hold potentiostat performing simultaneous acquisition of 16 independent channels of current ranging five orders of magnitude in dynamic range over four scales down to hundreds of picoamperes. Sampling rate ranges from DC to 200KHz. The system features programmable current gain control, configurable anti-aliasing log-domain filter, triggered current integration and provides differential output ready for asynchronous external analog-to-digital conversion over a compressed dynamic range. We present system description, circuit implementation and experimental results of real-time neurotransmitter concentration measurements from the 16-channel prototype fabricated in a 1.2 micron CMOS process.

We have develop highly sensitive and selective acoustic wave biosensor arrays with signal analysis systems to provide a fingerprint for the real-time identification and quantification of a wide array of bacterial pathogens and environmental health hazards. We have developed an unique highly sensitive dual mode acoustic wave platform prototype that, when combined with phage based selective detection elements, form a durable bacteria sensor. Arrays of these new real-time biosensors are integrated to form a biosensor array on a chip. This research and development program optimizes advanced piezoelectric aluminum nitride wide bandgap semiconductors, novel micromachining processes, advanced device structures, selective phage displays development and immobilization techniques, and system integration and signal analysis technology to develop the biosensor arrays. The dual sensor platform can be programmed to sense in a gas, vapor or liquid environment by switching between acoustic wave resonate modes. Such a dual mode sensor has tremendous implications for applications involving monitoring of pathogenic microorganisms in the clinical setting due to their ability to detect airborne pathogens. This provides a number of applications including hospital settings such as intensive care or other in-patient wards for the reduction of nosocomial infections and maintenance of sterile environments in surgical suites. Monitoring for airborn pathogen transmission in public transportation areas such as airplanes may be useful for implementation of strategies for redution of airborn transmission routes. The ability to use the same sensor in the liquid sensing mode is important for tracing the source of airborn pathogens to local liquid sources. Sensing of pathogens in saliva will be useful for sensing oral pathogens and support of decision-making strategies regarding prevention of transmission and support of treatment strategies.

Biological and chemical sensing is one of the application fields where integrated optical nanodevices can play an important role [1]. We present a Silicon Integrated Mach-Zehnder Interferometer Nanodevice using a Total Internal Refraction waveguide configuration. The induced changes due to a biomolecular interactions in the effective refractive index of the waveguide,is monitored by the measurement of the change in the properties of the propagating light. For using this device as a biosensor, the waveguides of the structure must verify two conditions: work in the monomode regime and to have a Surface Sensivity as high as possible in the sensing arm. The MZI device structure is: (i) a Si wafer with a 500 mm thickness (ii) a 2 mm thick thermal Silicon-Oxide layer with a refractive index of 1.46 (iii) a LPCVD Silicon Nitride layer of 100 nm thickness and a refractive index of 2.00, which is used as the guiding layer. To achieve monomode behavior is needed to define a rib structure, with a depth of only 3 nm, on the Silicon Nitride layer by a lithographic step. This rib structure is performed by RIE and is the most critical step in the microfabrication of the device. Over the structure a protective layer of LPCVD SiO₂ is deposited, with a 2 mm thickness and a refractive index of 1.46, which is patterned (photolithography) and etched (RIE) to define the sensing arm. The high sensivity of these devices makes them quite suitable for biosensing applications. For that, without loosing their activity the receptors biomolecules are covanlently immobilized, at nanometer scale , on the sensor area surface. Biospecific molecular recognition takes places when the complementary analyte to the receptor is flowed over the receptor using a flow system. Several biosensing applications have been performed with this device as enviromental pollutant control, immunosensing or genetic detection.

Biosensors are a very useful tool to produce drugs or to monitor chemical species through their product of reaction. The sensor is fabricated bounding on its surface specific enzymes that can accomplish the synthesis function. We studied the possibility to fabricate Si-based micro-biosensors to detect glucose in water solutions using porous Si (PS) as surface to bound the specific enzyme. We ideated and fabricated a novel biosensor structure based on a PS membrane that can be used for glucose monitoring and for drug production, by properly choosing the enzyme to immobilize in the reactor. The fabrication details of the structure, having a suspended and auto-supporting PS membrane, through surface micromachining processes, ULSI compatible, are shown. Micro channels localised below the membrane will allow the buffer solution flow through the porous matrix. Moreover, in this work we acquired the know-how on the enzyme manipulation, bonding and detection on Si-based surfaces. The enzyme that accomplish the synthesis function is the glucose oxidase. We deposited it on different substrates: PS, bulk Si and on glass. On these samples photoluminescence, absorbance and optical microscopy measurements were performed.

The importance of delivering warm, humidified air to patients ventilated through an endotracheal or tracheostomy tube is widely accepted. The use of modern artificial noses or heat and moisture exchangers made of recently developed material could be a solution to both problems of humidification and heat preservation. For this investigation, an IR optical sensor to measure weak partial pressure of water vapor has been designed and realized. This sensor is based on direct molecular absorption in the near IR corresponding to fundamental mode v₁ and it is an extrinsic and amplitude modulation type. In the quasi-linear region between 0 to 30 mbars, the calibration curve that represents the transmited power versus the water vapor partial pressure in air shows a high sensitivity with a minimum detectable of 100 μbars. The experimental setup, test procedure, theory analysis, and data processing of the optical water vapor sensor will be described in this article. The sensor has been designed to monitor water vapor in the modern artificial noses.

This paper presents an overview of the wireless monitoring and quantitative assessment of joint dynamics of ankle which has suffered from soft tissue injury, immobilization or any dysfunction with special focus on the treatment and rehabilitation applications. The inadequacy of a reliable and easy method for continuous measurement and recording of ankle movement while doing physical therapy makes the monitoring of its progress difficult. Development of a wireless ankle motion monitoring system inside the shoe provides information on several aspects of activities associated with a dysfunctional foot. The system is based on continuous wireless monitoring of signals from accelerometers and gyroscopes fixed inside the shoe. From these signals, the duration, rate, and moment of occurrence of activities associated with mobility (e.g., lying, sitting, standing, walking up and down, running, cycling, wheelchair use and general movement) and transitions (changes in angle) can be detected. Information about the movement can be obtained by the acceleration sensors, which is related to the intensity of body-segment movement. Apart from monitoring accelerations, other signals due to turning and angular movements can be obtained using the miniature gyroscope attached to the shoe.

Biometric identification based on hand veins subcutaneous network structure appears as a promising technique for personal recognition due to its robustness, low cost implementation and high users acceptability. Two of the most critical stages in these vein check identification systems are the vein pattern segmentation and matching, which extremely depend on the image acquisition process. The acquisition becomes a bottleneck in the performance of the whole system, as it represents the first stage in the recognition process. In this paper, solutions for the segmentation and matching under poor illumination conditions during the image acquisition process and low pixel camera resolution are presented. In particular, exhaustive studies will be presented in order to show that the use of the parametric black tophat transform, instead of the classical tophat mathematical morphology tool, and the utilization of homomorphic filters greatly benefit the performance of the segmentation and matching processes. Furthermore, it will be demonstrated that slight vertical and horizontal hand movements in the image acquisition can be easily corrected by using simple scaling operations. This fact makes unnecessary to fix the hand position and thus, contributes to enhance even more the non-invasive condition of these biometric systems. A first prototype for the image acquisition process has been implemented by only using a very simple CDD camera and LED diodes, obtaining infrared images of 60 people. The application of the mentioned techniques on these images, combined with some typical image processing operations like mean and median filtering, skeletonization and pruning, leads to a reliable vein based identification system, even in poor image acquisition conditions.

Pulse oximeters are used for the non-invasive monitoring of arterial blood hemoglobin oxygen saturation. This technique is based on the time variable optical attenuation by a vascular bed due to the cardiac pumping action (photoplethysmography) and the differential optical absorption of the oxy- and deoxy-hemoglobin. The photoplethysmographic (PPG) signals measured at two specific wavelengths are decomposed into its variable or pulsating component (EAC) and the constant or non-pulsating component (EDC) for deriving a parameter related to the arterial blood oxygen saturation (So₂). Previously it has been reported a signal processing algorithm for a near infrared (NIR) laser diodes based transmittance pulse oximetry system. The main difficulties in the extraction of the information from the PPG signals are the small value of the signals variation related to their constant values, and the presence of artefacts caused by macro- and micro- movements of the part under analysis. The proposed algorithm permits the numeric separation of the variable and constant parts of the signals for both wavelengths. The EDC is obtained by a low pass filtering, and EAC by a pass-band one, followed by a non-linear filtering based on histogram reduction. In the present work is exposed the analysis of the influence of processing parameters like filters cut-off frequencies and histogram reduction percentage, on the derived So₂ values. The test has been conducted both on real and simulated PPG signals. The real PPG has been recorded through experimental studies with human subjects using the NIR laser diodes based transmittance pulse oximetry system. The sources of artefacts and noise in the laser diodes PPG signals are discussed.

The increase in the incidence of pigmented skin lesions in the last decade together with the fact that early detection could allow a mortality reduction has lead to the development of spectrometric diagnostic techniques applicable to dermatology. These techniques are based on the evidence that the presence of malignant cells should somehow alter the optical characteristics of epidermis with respect to the healthy one and a different reflectance spectrum should appear. The subjectivity of the clinical observation by the specialist is, in this way, substituted by an objective technique, with the improve of the specificity and the sensitivity. The aim of this work is to obtain a skin reflectance database of both benign and malignant lesions as well as of healthy skin which permits to establish algorithms and discrimination rules for a more objective identification of different pigmented skin lesions. The measure system consists of a portable visible near infrared (600-1000 nm) spectrometer (AVS-USB200, Avantes), a tungsten halogen lamp (HL-200) and fiber optics reflection probes. The parameters of that system and their variability has been tested in steady state conditions by using neutral filters and a white reference tile. A reproducibility study of both normal and pigmented skin diffuse reflectance spectra has been carried out. After that a small scale study of selected subjects have been conducted. This study has comprised the collection of spectra from different skin pigmented lesions and the clinical evaluation of its lesions characteristics by the dermatologist. The results after the analysis of the collected data are presented.

This paper focuses on the future of RFID systems for biomedical applications. It discusses current technology, restrictions and applications and also illustrates possible future development for the technology. This report gives the reader an idea of what research has been done to date and draws some conclusions about where further development is needed. We focus mainly on actuator devices and introduce some of the concepts for RFID sensors. Radio Frequency Identification or RFID is a technology that has evolved from the development of magnetic bar code systems. Unlike magnetic bar codes, passive RFID can be used in extreme climatic conditions and unlike conventional bar coding does not require wiring or the tags to be within close proximity of the reader. In RFID technology there are two main components, they are an Interrogator and a label/transponder. The interrogator sends coded RF signals to the label in the form of radio frequency waves. The label receives this RF energy and uses it to power its circuit as well as interpreting the energy as some form of instruction. In this report we focus mainly on the label/transponder and assume that the relevant RF energy has been correctly encoded and sent.

The paper presents the method of preparation and studies of physicochemical properties of silica gels with the chemically bonded bovine serum albumin (BSA) phase. Wide-porous Z-300 silica gel was studied. Changes of physicochemical properties result in significant changes of adsorption properties and total heterogeneity as well as energetic heterogeneity of the samples. Surface properties of samples were studied by means of the complex methods such as: special technique of thermal analysis, sorptomatic method, microelemental analysis, atomic force microscopy and transform IR spectroscopy.

Blood micro-circulation in upper skin layers has been studied experimentally in real time by advanced two-channel photoplethysmography (PPG) techniques. The blood volume changes caused by micro-vessel expansion and dilution during the cardiac cycles have been detected by infrared optical contact sensors. A newly developed portable monitoring device comprising a lap-top computer was used for accumulation and processing of the bio-signals. Shapes of the PPG signals detected at different sites of the body were compared with these obtained by computer modeling.

A smart drug delivery injector microsystem is presented based on small pyrotechnics to impulse drugs to be injected to a human being. The proposal refers to a feasibility demonstration of the technology for pharmaceutical chips. These chips would be around some cm2 in section and will be able to inject a drug into de subject skin responding to an electrical signal. The product derived from this activity will be useful for astronaut's health, being able to administrate emergency doses of products (for instance cardio-tonic or hypoallegic drugs) enough to survive an emergency situation (as it can be a heart attack during EVA). The system can also be used for easy administration of drugs needed for physiological research. The usefulness of the device in terrestrial applications has no doubt, allowing remote administration of drugs to patients whose biomedical parameters are remotely monitored. The concept proposed here is new in combining the idea of pharmaceutical chip with the ultrasonic droplet technology and the use of pyrotechnics to provide energy to the drug to be injected. The proposed Drug Injector Microsystem is based on 2 main blocks:- Micropyrotechnic system: defines the ignition part based on pyrotechnic.- Microfluidic system: defines the drug injection part. This part is also divided in different critical parts: Expansion chamber, membrane or piston, drug reservoir and a needle. Different sensors are placed on the expansion chamber of microfluidic system and on the micropyrotechnic system. A complete electronic module is implemented with a PC interface to define flexible and user friendly experiences showing the smart drug delivery injector microsystem principle.

The development of tools for a multi-microrobot manipulating system prototype to handle cells and biomolecules is proposed. The system will be based on a cluster (5 to 10) of small (cm³) mobile autonomous robots. The proposed system comprises several essential subsystems such as a global positioning system to provide accurate position information of each microrobot, advanced manipulating tools and a wireless power supply unit. It also includes user interfaces as well as systems for transporting objects into and out of the working range of the robots. Additional bio-handling arms must be integrated on the robots. Actuators for the positioning and moving of cells must be compatible with their living conditions. The application of non-uniform electric fields to non-charged particles suspended in aqueous medium produces a force over the particle due to the induced dipole moment.

In this paper, a contribution is given to provide a tool to the recognition of sinusoidal signals with a particular reference to the field of pediatric hearing rehabilitation. To this purpose, a synthesis technique previously developed by the authors' is used to design a Cellular Neural Network for an Associative Memory able to compare submitted discrete-time sinusoidal signals with memorized ones. A robustness analysis of the synthesized associative memory is also developed both for noisy inputs and for parameter variations. Simulation results are then reported to illustrate the performances of the designed network.

The knowledge about mechanisms of voice production as well as the parameters obtaining, allow us to present solutions for coding, transmission and establishment of properties to distinguish between the responsible physiological mechanisms. In this work, we are interested in the evaluation of syllabic Sequences in Continuous Speech. We keep in mind this evaluation is very interesting and useful for Foniatrics and Logopaedia applications focus on the measurement and control of Speech Fluency. Moreover, we are interested in studying and evaluating sequential programming and muscular coordination. In this way, the main objective of our work is focus on the study of production mechanisms, model, evaluation methods and introduction of a reliable algorithm to catalogue and classify the phenomena of rythm and speech fluency. In this paper, we present an algorithm for syllabic analysis based on Short Time Energy concept. Firstly, the algorithm extracts the temporary syllabic intervals of speech and silence, and then compared with normality intervals. Secondly, it proceeds to feedback in real time to the patient luminous and acoustic signals indicating the degree of mismatching with the normality model. This methodology is useful to improve fluency disorder. We present an ASIC microelectronic solution for the syllabic analyser and a portable prototype to be used in a clinic level as much as individualized tool for the patient.

0.5% of the world population is suffering from a focal epilepsy. Several actual investigations showed that methods in nonlinear signal processing are important for the derivation of new feature extraction methods to enable the realisation of a portable epilepsy warning system. In this contribution we will present recent results for the pattern detection algorithm which we have proposed in previous investigations. In order to verify our first results we will present results of long time measurements. Furthermore the pattern detection algorithm has been transformed in order to run on the first realization of a possible warning device, which had been presented by Laiho et. al. A detail discussion of the results will be given in the paper.

The communicational and computational demands of neural networks are hard to satisfy in a digital technology. Temporal computing addresses this problem by iteration, but leaves a slow network. Spatial computing only became an option with the coming of modern FPGA devices. The paper provides two examples. First the balance between area and time is discussed on the realization of a modular feed-forward network. Second, the design of real-time image processing through a Cellular Neural Network is treated. In both examples, reconfiguration can be applied to provide for a natural and transparent support of learning.

In the central nervous systems of animals like pigeons and locusts, neurons were identified which signal objects approaching the animal on a direct collision course. In order to timely initiate escape behavior, these neurons must recognize a possible approach (or at least differentiate it from similar but non-threatening situations), and estimate the time-to-collision (ttc). Unraveling the neural circuitry for collision avoidance, and identifying the underlying computational principles, should thus be promising for building vision-based neuromorphic architectures, which in the near future could find applications in cars or planes. Unfortunately, a corresponding computational architecture which is able to handle real-situations (e.g. moving backgrounds, different lighting conditions) is still not available (successful collision avoidance of a robot was demonstrated only for a closed environment). Here we present two computational models for signalling impending collision. These models are parsimonious since they possess only the minimum number of computational units which are essential to reproduce corresponding biological data. Our models show robust performance in adverse situations, such as with approaching low-contrast objects, or with highly textured backgrounds. Furthermore, a condition is proposed under which the responses of our models match the so-called eta-function. We finally discuss which components need to be added to our model to convert it into a full-fledged real-world-environment collision detector.

In this paper a biologically motivated image flow processing mechanism is presented for visual exploration systems. The intention of this multi-channel topographic approach was to produce decision maps for salient feature localization and identification. As a unique biological study has recently confirmed mammalian visual systems process the world through a set of separate parallel channels and these representations are embodied in a stack of 'strata' in the retina. Beyond reflecting the biological motivations our main goal was to create an efficient algorithmic framework for real-life visual search and navigation experiments. In the course of this design the retinotopic processing scheme is embedded in an analogic Cellular Neural Network (CNN) algorithm where image flow is analyzed by temporal, spatial and spatio-temporal filters. The output of these sub-channels is then combined in a programmable configuration to form the new channel responses. In the core of the algorithm crisp or fuzzy logic strategies define the global channel interaction and result in a unique binary image flow. This processing mechanism of the algorithmic framework and the hardware architecture of the system are presented along with experimental ACE4k CNN chip results for several video flows recorded in flying vehicles.

Human vision routinely compensates for illumination field and is mostly sensitive to scene reflectance. This paper presents a biologically inspired mathematical model that estimates the illumination field of a scene and compensates for it to produce the output image that is mostly modulated by the scene reflectance. Since the illumination field is responsible for wide dynamic range variations in scenes, the present model is seen as an approach to handling wide dynamic range scenes. The model can be conveniently implemented in an analog silicon retina incorporating modified cellular neural network for the computation of the illumination field. We present several numerically obtained results on scenes with widely varying illumination conditions.

Recognizing objects of interest in real-world scenes is a principal computational goal of the primate visual system. This process involves the representation of object surfaces in the first visual areas of the neocortex. Luminance gradients are usually superimposed on object surfaces, what complicates the recovery of the surface reflectance functions on the one hand, but may provide valuable information about surface texture and surface curvature one the other hand. Consequently, there should be a way to recognize and represent luminance gradients independently from object surfaces. However, there is no corresponding theory available up to now. Here we present a two-stage architecture which is compatible with this idea. The first stage involves the detection of luminance gradients in a given intensity image, which are subsequently recovered in the second stage. By means of a novel diffusion paradigm, our architecture is capable of building representations of arbitrary sized luminance gradients from sparse local measurements of gradient evidence. Since our architecture both predicts psychophysical data on Mach bands, and successfully processes real-world scenes, it constitutes a potential computational theory on how luminance gradients are processed and represented in the first visual areas of the brain.

The user wishes to communicate with a remote partner over an insecure network. Since the user is a human being, a terminal is needed for communication. Cryptographic algorithms running on the terminal may provide authenticity for the user's messages. In this paper the problem of sending authentic messages from insecure or untrusted terminals is analyzed. In this case attackers are able to gain total control over the terminal, so the user must consider the terminal a potential attacker. Smart cards are often considered the ultimate tool for secure messaging from untrusted terminals. However, their lack of user interface enables man-in-the middle attack from the terminal. The authors assume, that user is a human being with limited memory and computational power, and also makes mistakes in his calculations. They demnostrate, that only exceptional useres are able to authenticate messages without a trusted device. Several biometric media encapsulate the content of the message and the identity of the sender, such as speech, video and handwriting. The authors suggest, that such media is far more difficult to counterfeit than plaintext. Thus, the user must rely on his other resources, like biometric ones. In the protocol proposed by the authors, the user sends messages in a biometric format, strengthened by simple algorithmic authenticators. The smart card functions as a secure time gate ensuring, that the attacker has extremely little time to counterfeit both the biometric and the algorithmic protection on the message. The authors claim, that with the proper calibration of the biometric method and the time gate of the smart card, their protocol is strong enough for practical use.

Inverted repeats may regulate genetic procceses by formation of hairpin secondary structures that block DNA polymerases. Two different DNA conformations may cor-respond to inverted repeats: either a linear double stranded helix or a cruciform struc-ture consisting of two symmetrical hairpins. Theoretical and experimental studies have shown that cruciform structures can exist in negatively supercoiled DNA, cont-rary to relaxed molecules. Cruciform formation depends on many factors, firstly, on temperature and supercoils density. Recently application of the scanning probe mic-roscopy has allowed for significant progress in cruciform structure studies. The goal of present work is computer analysis of inverted repeats in viruses, bac-teria and plasmid DNA (human immunodeficiency virus (HIV), bovine immunode-ficiency virus (BIV), bovine leukemia virus (BLV), mycobacterium tuberculosis (MTB), plasmid pUC8) and direct visualization of the cruciform structure in super-coiled DNA by atomic force microscopy (AFM). The cruciform dimensions were determined. Analysis and modeling of the most thermodynamically stable cruciform formations in viral and bacterial DNA were carried out. The complete genome sequence of HIV, BIV, BLV is ~9000 base pairs (bp), my-cobacterium tuberculosis - over 4000000 bp, pUC8 DNA - 2665 bp. Computer ana-lysis showed that two different isolates of MTB with complete genome contain 45 and 50 inverted repeats; HIV, BIV, BLV and plasmid pUC8 contain only one palin-drome which can form cruciform structure in buffer solution. Cruciform in plasmid pUC8 supercoiled DNA, was directly visualized by atomic force microscopy. Cruciform is seen as clear-cut extrusions on the DNA filaments with the lengths of the arms fully consistent with the size of the hairpins expected from a 26 bp inverted repeat in pUC8 plasmid DNA. Application of the aminomodi-fied mica allowed to obtain stable DNA images. DNA molecules on aminomica are not stretched and their contours are smooth. The geometry of cruciform depends on ionic coditions. At low ionic strength cruciform can adopt an extended conformation with the angle of ca. 180° between the hairpins arms. AFM image shows that hairpin of cruciform structure is formed by 13-14 bp. Results of search for self-complementary regions of pUC8 DNA sequence confirmed that hairpin is formed by the double 11bp sequences and a loop of 4 nucleotides.