Design of Two-Dimensional Digital Filters Having Variable Monotonic Amplitude-Frequency Responses Using Darlington-type Gyrator Networks

This paper develops a design of two-dimensional (2D) digital filter with monotonic amplitude-frequency responses using Darlington-type gyrator networks by the application of Generalized Bilinear Transformation (GBT). The proposed design provides the stable monotonic amplitude-frequency responses and the desired cutoff frequency of the 2D digital filters. This 2D recursive digital filter design includes 2D digital low-pass, high-pass, band-pass and band-elimination filters. Design examples are given to illustrate the usefulness of the proposed technique. Index Terms— Stability, monotonic response, GBT, gyrator network. 1. Introduction Because of recent growth in the 2D signal processing activities, a significant amount of research work has been done on the 2D filter design [1] and it is seen that monotonic characteristics in frequency response of a filter is getting more popular. The filters with the monotonic characteristics are one of the best filters for the digital image, video and audio (enhancement and restoration) [2]. The filters are widely accepted in the applications of medical science, geographical science and environment, space and robotic engineering [1]. For example, medical applications are concerned with processing of chest X-Ray, cine angiogram, projection of frame axial tomography and other medical images that occurs in radiology, nuclear magnetic resonance (NMR), ultrasonic scanning and magnetic resonance imaging (MRI) etc. and the restoration and enhancement of these images are done by the 2D digital filters [3]. The design of 2D recursive filters is difficult due to the non-existence of the fundamental theorem of algebra in that the factorization of 2D polynomials into lower order polynomials and the testing for stability of a 2D transfer function (recursive) requires a large number of 54 Digital Filters computations. But, the major drawbacks of the recursive filters are their lower-order realizations and computational intensive design techniques. Several design techniques of 2D recursive filter have been reported in the literature [2], [4] – [9] and most of these designs have problems of computational complexity, stability and unable to provide variable magnitude monotonic characteristic. A design technique of 2D recursive filters have been shown which met simultaneously magnitude and group delay specifications [4], although the technique has the advantage of always ensuring the filter stability, the difficulties to be encountered are computational complexity and convergence [5]. In [6], 2D filter design as a linear programming problem has been proposed, but, this tends to require relatively long computation time. In [7], a filter design has been shown using the two specifications as the problem of minimizing the total length of modified complex errors and minimized it by an iterative procedure. Difficulties of the design obtain for two-dimensional stability testing at each iteration during the minimization procedure. One way to ensure a 2D transfer function is stable is if the denominator of the transfer function is satisfied to be a Very Strict Hurwitz Polynomial (VSHP) [8] and that can ensure a transfer function that there is no singularity in the right half of the biplane, which can make a system unstable. In [9]-[11], stable 2D recursive filters have been designed by generation of Very Strict Hurwitz Polynomial (VSHP), but it is not guaranteed to provide the stable monotonic amplitude-frequency responses. Several filter designs with monotonic amplitude frequency response has been reported [12] – [16], but to the best of our knowledge, filter design with variable monotonic amplitude frequency response is not proposed yet. In this paper, 2-D digital filters with variable monotonic amplitude frequency responses are designed starting from Darlington-type networks containing gyrators and doublyterminated RLC-networks. The extension of Darlington-synthesis to two-variable positive real functions is given in [17], [18]; but they do not contain gyrators. From the 2-D stable transfer functions so obtained, the GBT [19] is applied to obtain 2-D digital functions and their properties are studied. The designed filters are used in the image processing application. 2. THE TWO BASIC STRUCTURES CONSIDERED Two filter structures are considered for 2D digital recursive filters design and both structures are taken from Darlington-synthesis [20]. Figures 1(a) and (b) show the two structures considered in this paper. The impedances of the filters are replaced by doubly-terminated RLC filters and the overall transfer function will be of the form H ( s1 , s 2 , g )   N ï²ï® ( g )s ï² sï® ï²ï® 0 0 1 M n Nn 2 ï« ï€½0 ï¬ ï€½0   Dï« ( g )s ï¬ M d Nd (1

Implantable Micro-Device for Epilepsy Seizure Detection and Subsequent Treatment

RÉSUMÉ L’émergence des micro-dispositifs implantables est une voie prometteuse pour le traitement de troubles neurologiques. Ces systèmes biomédicaux ont été exploités comme traitements non-conventionnels sur des patients chez qui les remèdes habituels sont inefficaces. Les récents progrès qui ont été faits sur les interfaces neuronales directes ont permis aux chercheurs d’analyser l’activité EEG intracérébrale (icEEG) en temps réel pour des fins de traitements. Cette thèse présente un dispositif implantable à base de microsystèmes pouvant capter efficacement des signaux neuronaux, détecter des crises d’épilepsie et y apporter un traitement afin de l’arrêter. Les contributions principales présentées ici ont été rapportées dans cinq articles scientifiques, publiés ou acceptés pour publication dans les revues IEEE, et plusieurs autres tels que «Low Power Electronics» et «Emerging Technologies in Computing». Le microsystème proposé inclus un circuit intégré (CI) à faible consommation énergétique permettant la détection de crises d’épilepsie en temps réel. Cet CI comporte une pré-amplification initiale et un détecteur de crises d’épilepsie. Le pré-amplificateur est constitué d’une nouvelle topologie de stabilisateur d’hacheur réduisant le bruit et la puissance dissipée. Les CI fabriqués ont été testés sur des enregistrements d’icEEG provenant de sept patients épileptiques réfractaires au traitement antiépileptique. Le délai moyen de la détection d’une crise est de 13,5 secondes, soit avant le début des manifestations cliniques évidentes. La consommation totale d’énergie mesurée de cette puce est de 51 μW. Un neurostimulateur à boucle fermée (NSBF), quant à lui, détecte automatiquement les crises en se basant sur les signaux icEEG captés par des électrodes intracrâniennes et permet une rétroaction par une stimulation électrique au même endroit afin d’interrompre ces crises. La puce de détection de crises et le stimulateur électrique à base sur FPGA ont été assemblés à des électrodes afin de compléter la prothèse proposée. Ce NSBF a été validé en utilisant des enregistrements d’icEEG de dix patients souffrant d’épilepsie réfractaire. Les résultats révèlent une performance excellente pour la détection précoce de crises et pour l’auto-déclenchement subséquent d’une stimulation électrique. La consommation énergétique totale du NSBF est de 16 mW. Une autre alternative à la stimulation électrique est l’injection locale de médicaments, un traitement prometteur de l’épilepsie. Un système local de livraison de médicament basé sur un nouveau détecteur asynchrone des crises est présenté.----------ABSTRACT Emerging implantable microdevices hold great promise for the treatment of patients with neurological conditions. These biomedical systems have been exploited as unconventional treatment for the conventionally untreatable patients. Recent progress in brain-machine-interface activities has led the researchers to analyze the intracerebral EEG (icEEG) recording in real-time and deliver subsequent treatments. We present in this thesis a long-term safe and reliable low-power microsystem-based implantable device to perform efficient neural signal recording, seizure detection and subsequent treatment for epilepsy. The main contributions presented in this thesis are reported in five journal manuscripts, published or accepted for publication in IEEE Journals, and many others such as Low Power Electronics, and Emerging Technologies in Computing. The proposed microsystem includes a low-power integrated circuit (IC) intended for real-time epileptic seizure detection. This IC integrates a front-end preamplifier and epileptic seizure detector. The preamplifier is based on a new chopper stabilizer topology that reduces noise and power dissipation. The fabricated IC was tested using icEEG recordings from seven patients with drug-resistant epilepsy. The average seizure detection delay was 13.5 sec, well before the onset of clinical manifestations. The measured total power consumption of this chip is 51 µW. A closed-loop neurostimulator (CLNS) is next introduced, which is dedicated to automatically detect seizure based on icEEG recordings from intracranial electrode contacts and provide an electrical stimulation feedback to the same contacts in order to disrupt these seizures. The seizure detector chip and a dedicated FPGA-based electrical stimulator were assembled together with common recording electrodes to complete the proposed prosthesis. This CLNS was validated offline using recording from ten patients with refractory epilepsy, and showed excellent performance for early detection of seizures and subsequent self-triggering electrical stimulation. Total power consumption of the CLNS is 16 mW. Alternatively, focal drug injection is the promising treatment for epilepsy. A responsive focal drug delivery system based on a new asynchronous seizure detector is also presented. The later system with data-dependent computation reduces up to 49% power consumption compared to the previous synchronous neurostimulator

Design of two-dimensional digital filters having monotonic amplitude-frequency responses using Darlington-type gyrator networks

A design of two-dimensional (2D) digital filter with monotonic amplitude-frequency responses using Darlington-type gyrator networks by the application of Generalized Bilinear Transformation is discussed. The proposed design provides the stable monotonic amplitude-frequency responses and the desired cutoff frequency of the 2D digital filters. This 2D recursive digital filter design includes 2D digital low-pass, high-pass, band-pass and band-elimination filters. The proposed design shows that the impedances of doubly terminated RLC networks are integrated into the Darlington-type gyrator networks and the coefficients of the resultant 2D analog transfer functions are function of gyrator constant ( g ). The behavior of the filter is changed not only for the values of resistance, capacitance and inductance of the filter, but also for the value and sign of g. The proposed design uses the Generalized Bilinear Transformation to obtain the digital filter and it provides six parameters to regulate in order to design the desired digital filters. The several constraints are obtained for the monotonic amplitude-frequency responses of the filters. The ranges of g of the each type filter are defined for attaining the monotonic characteristics of the digital filter, because the g has control on the frequency response of the filter. A digital filter transformation method is proposed and the digital filters are transformed by regulating the value or sign of g. A new realization of 2D digital polynomial is given, which is suitable to implement any 2D polynomial with finite order. The performances of the designed 2D digital filters in the image processing applications are discussed and significant improvements in the reconstructed images are obtained by the filters

Subdural porous and notched mini-grid electrodes for wireless intracranial electroencephalographic recordings

BACKGROUND: Intracranial electroencephalography (EEG) studies are widely used in the presurgical evaluation of drug-refractory patients with partial epilepsy. Because chronic implantation of intracranial electrodes carries a risk of infection, hemorrhage, and edema, it is best to limit the number of electrodes used without compromising the ability to localize the epileptogenic zone (EZ). There is always a risk that an intracranial study may fail to identify the EZ because of suboptimal coverage. We present a new subdural electrode design that will allow better sampling of suspected areas of epileptogenicity with lower risk to patients. METHOD: Impedance of the proposed electrodes was characterized in vitro using electrochemical impedance spectroscopy. The appearance of the novel electrodes on magnetic resonance imaging (MRI) was tested by placing the electrodes into a gel solution (0.9% NaCl with 14 g gelatin). In vivo neural recordings were performed in male Sprague Dawley rats. Performance comparisons were made using microelectrode recordings from rat cortex and subdural/depth recordings from epileptic patients. Histological examinations of rat brain after 3-week icEEG intracerebral electroencephalography (icEEG) recordings were performed. RESULTS: The in vitro results showed minimum impedances for optimum choice of pure gold materials for electrode contacts and wire. Different attributes of the new electrodes were identified on MRI. The results of in vivo recordings demonstrated signal stability, 50% noise reduction, and up to 6 dB signal-to-noise ratio (SNR) improvement as compared to commercial electrodes. The wireless icEEG recording system demonstrated on average a 2% normalized root-mean-square (RMS) deviation. Following the long-term icEEG recording, brain histological results showed no abnormal tissue reaction in the underlying cortex. CONCLUSION: The proposed subdural electrode system features attributes that could potentially translate into better icEEG recordings and allow sampling of large of areas of epileptogenicity at lower risk to patients. Further validation for use in humans is required