Performance of a multi-electrode silicon-based dielectrophoretic cage device using four electrical contacts

A dielectrophoretic (DEP) cage [1] device was built entirely on a silicon substrate using standard CMOS processing techniques. The signal phases on multiple electrodes are controlled with only four electrical contacts, which connect to the device using three metal layers. A correlation between the particle velocities and the electric field squared gradients was made using Tracker[2], an open source program that tracks particles in video files, and COMSOL Multiphysics®, which solves the Laplace equation for the corresponding electric field squared gradients using finite element analysis.     

Automated epileptic seizure waveform detection method based on the feature of the mean slope of wavelet coefficient counts using a hidden Markov model and EEG signals

Long‐term electroencephalography (EEG) monitoring is time‐consuming, and requires experts to interpret EEG signals to detect seizures in patients. In this paper, we propose a novel automated method called adaptive slope of wavelet coefficient counts over various thresholds (ASCOT) to classify patient episodes as seizure waveforms. ASCOT involves extracting the feature matrix by calculating the mean slope of wavelet coefficient counts over various thresholds in each frequency subband. We validated our method using our own database and a public database to avoid overtuning. The experimental results show that the proposed method achieved a reliable and promising accuracy in both our own database (98.93%) and the public database (99.78%). Finally, we evaluated the performance of the method considering various window sizes. In conclusion, the proposed method achieved a reliable seizure detection performance with a short‐term window size. Therefore, our method can be utilized to interpret long‐term EEG results and detect momentary seizure waveforms in diagnostic systems.     

Analysis of Intracerebral EEG Recordings of Epileptic Spikes: Insights From a Neural Network Model

The pathophysiological interpretation of EEG signals recorded with depth electrodes [i.e., local field potentials (LFPs)] during interictal (between seizures) or ictal (during seizures) periods is fundamental in the presurgical evaluation of patients with drug-resistant epilepsy. Our objective was to explain specific shape features of interictal spikes in the hippocampus (observed in LFPs) in terms of cell- and network-related parameters of neuronal circuits that generate these events. We developed a neural network model based on “minimal” but biologically relevant neuron models interconnected through GABAergic and glutamatergic synapses that reproduce the main physiological features of the CA1 subfield. Simulated LFPs were obtained by solving the forward problem (dipole theory) from networks including a large number ($sim$3000) of cells. Insertion of appropriate parameters allowed the model to simulate events that closely resemble actual epileptic spikes. Moreover, the shape of the early fast component (``spike') and the late slow component (``negative wave') was linked to the relative contribution of glutamatergic and GABAergic synaptic currents in pyramidal cells. In addition, the model provides insights about the sensitivity of electrode localization with respect to recorded tissue volume and about the relationship between the LFP and the intracellular activity of principal cells and interneurons represented in the network.      

A patient-specific algorithm for the detection of seizure onset inlong-term EEG monitoring: possible use as a warning device

During long-term electroencephalogram (EEG) monitoring of epileptic patients, a seizure warning system would allow patients and observers to take appropriate precautions. It would also allow observers to interact with patients early during the seizure, thus revealing clinically useful information. We designed patient-specific classifiers to detect seizure onsets. After a seizure and some nonseizure data are recorded in a patient, they are used to train a classifier. In subsequent monitoring sessions, EEG patterns have to pass this classifier to determine if a seizure onset occurs. If it does, an alarm is triggered. Extreme care has been taken to ensure a low false-alarm rate, since a high false-alarm rate would render the system ineffective. Features were extracted from the time and frequency domains and a modified nearest-neighbor (NN) classifier was used. The system reached an onset detection rate of 100% with an average delay of 9.35 s after onset. The average false-alarm rate was only 0.02/h. The method was evaluated in 12 patients with a total of 47 seizures. Results indicate that the system is effective and reasonably reliable. Computation load has been kept to a minimum so that real-time processing is possible     

Modeling of vehicle dynamics from real vehicle measurements using a neural network with two-stage hybrid learning for accurate long-term prediction

This paper describes a neural network (NN) model of a real vehicle and the associated hybrid learning scheme. The NN vehicle models the actual vehicle dynamic behavior with the architecture of a real-time recurrent network. The NN was trained to predict the next state of the vehicle, given the current vehicle state, the current input steering angle of the front wheel, and the vehicle's speed. A hybrid training scheme for the network has been proposed, which consists of two phases: open-loop training for stabilization of the NN weight learning and closed-loop training for long-term prediction of the vehicle behavior. The open-loop training is necessary to avoid learning instability at initial stages. The closed-loop training then follows in such a way that the NN correctly predicts the vehicle's next state in a recursive mode. The outcome is that the model can correctly generate the vehicle trajectory, given the initial state and the steering and speed sequence of the vehicle. Furthermore, after this training procedure, it not only learns the vehicle's lateral dynamics along the trained trajectories, but can also generalize to similar trajectories. This modeling technique has been successfully applied to model the actual dynamics of a Daewoo Leganza vehicle. It is an intelligent vehicle that is fully autonomous in that steering, braking, and accelerating were all done via computer control. The training data were taken from a four-vehicle platoon demonstration in which four vehicles were automatically controlled in a convoy mode.     

Real-time location of multiple time-varying strain disturbances,acting over a 40-km fiber section, using a novel dual-Sagnacinterferometer

Updated results using a novel sensing architecture based on a Sagnac interferometer are presented and, for the first time, real-time separation and positioning of multiple disturbances has been realized. A 40-km long dual-Sagnac sensor was formed by spectral slicing of light from a single, broad-band erbium-doped-fiber super-luminescent source and wavelength division multiplexed (WDM) routing around the loop to form an inherently low loss system. Independent active phase biasing of each Sagnac was employed, allowing the use of a single optical detector. The effects of residual optical cross talk between the two Sagnacs has been accurately modeled, allowing resulting errors to be corrected. The new system has capability for narrow-band fast Fourier transform (FFT) analysis of detected disturbance signals, and hence their separation in the frequency domain. For audio-frequency excitation, an average positional resolution of 100 m over a 40-km length was achieved with a postdetection signal processing bandwidth of 8 Hz     

Fiber nonlinearity compensation of WDM-PDM 16-QAM signaling using multiple optical phase conjugations over a distributed Raman-amplified link

In this paper, multiple optical phase conjugation (OPC) devices were used along the optical link to improve the performance of an \(8\times 256\) Gbps polarization-division multiplexing 16-state quadrature amplitude modulation signaling, producing total bit rate of 2.048 Tbps. A 50-GHz spaced, eight-channel wavelength division multiplexing (WDM) communication system was considered using 912 km dispersion-unmanaged standard single-mode fiber link with backward distributed Raman pumps. The performance of a dual-pump highly nonlinear fiber-based OPC was investigated analytically using a set of eight nonlinear Schrödinger equations taking into account the effect of polarization. Simulation results were compared with the case of mid-span optical phase conjugation (MS-OPC) compensation scheme showing better performance in terms of achievable Q-factor, optimal signal launched power, and the total length of the transmission link. In 256 Gbps, single-channel scenario, a Q-factor improvement of 1.35 dB was achieved and the nonlinear threshold was increased by \(\sim \) 4 dB compared to the case of MS-OPC. Moreover, using multiple OPC led to increase the length of the transmission link by 30.7% compared with the case of MS-OPC. In 2.048 Tbps WDM system, a maximum Q-factor of 9.27 dB over the same link was obtained showing an improvement of 0.62 dB over the MS-OPC case. The simulation results were compared with published analogous experimental data showing very good agreement.     

Optimum processing gain for a hybrid direct sequence/slow frequency hopping code division multiple access cellular system over Rayleigh fading channels: the direct sequence/slow frequency hopping code division multiple access case

In this paper, the optimum value of the processing gain of a hybrid direct sequence/slow frequency hopping code division multiple access cellular system, when operating in a Rayleigh fading environment, is examined. The optimization is based on the maximization of the average spectral efficiency achieved, expressed in bits per second per Hertz, which is estimated in terms of the achievable average channel capacity (in the Shannon–Hartley theorem sense) per user during the operation over a broadcast cellular time‐varying link. The analysis leads to a simple theoretical novel closed‐form expression for the optimal processing gain that is related with the system's parameters but becomes independent of hopping frequencies assigned to each system's cell. Finally, the expression derived can be useful for the practical design of a direct sequence/slow frequency hopping code division multiple access cellular system and for an initial quantitative analysis. Numerical results are presented to illustrate the presented analysis. Copyright © 2011 John Wiley & Sons, Ltd.     

Lossless aggregation: a scheme for transmitting multiple stored VBRvideo streams over a shared communications channel without loss of imagequality

This paper introduces a new concept called lossless aggregation for the transmission of video information. It is a scheme for the delivery of variable bit-rate (VBR) video streams from a video server to a group of users over a shared channel. No data are dropped at the source during the adaptation process that reshapes the VBR video traffic to conform to the channel bit-rate characteristics. The transmission schedules of individual video streams evolve in a dynamic way that depends on their relative traffic characteristics. Receiver buffer underflow and overflow are prevented. Therefore, the data delivery process does not cause any loss of image quality. We show that very significant receiver-buffer reduction can be achieved with aggregation compared with the independent transmission of individual video streams over separate channels. Several bandwidth allocation methods for aggregation are studied extensively. The frame equalization algorithm stands out in terms of its simplicity and optimality     

Determination of intracranial tumor volumes in a rodent brain using magnetic resonance imaging, Evans blue, and histology: a comparative study

The measurement of tumor volumes is a practical and objective method of assessing the efficacy of a therapeutic agent. However, the relative accuracy of different methods of assessing tumor volume has been unclear. Using T1-weighted, gadolinium-enhanced magnetic resonance Imaging (T1-MRI), Evans Blue infusion and histology we measured intracranial tumor volumes in a rodent brain tumor model (RT2) at days 10, 16 and 18 after implantation of cells in the caudate putamen. There is a good correlation between tumor volumes comparing T1-MRI and Evans Blue (r2 = 0.99), T1-MRI and Histology (r2 = 0.98) and histology and Evans Blue (r2 = 0.93). Each of these methods is reliable in estimating tumor volumes in laboratory animals. There was significant uptake of gadolinium and Evans Blue in the tumor suggesting a wide disruption of the blood-brain barrier.     

Statistical modeling of transmission line model test structures.II. TLM test structure with four or more terminals: a novel method tocharacterize nonideal planar contacts in presence ofinhomogeneities

For pt.I see ibid., vol.37, pp.2350-2360, Nov. 1990. A modified transmission line model (redundant TLM or RTLM) test structure (with four or more terminals) and a novel data extraction method are suggested to improve the accuracy of the TLM method. Statistical modeling by both statistical simulation and the method of error propagation shows that with four terminals and independently known sheet resistances between the contacts, the errors of the extracted parameters can be reduced considerably. With the use of five or more terminals, the accuracy of the parameter extraction can also be determined by a single structure, allowing the separation of inhomogeneities within a test structure from the inhomogeneities over the wafer. Experimental data gathered by Kelvin cross-bridge resistors and by traditional and modified transmission line model structures on Al-Si-Cu/TiW/p-n Si contacts clearly show the advantage of the RTLM method over the traditional TLM method. On a wafer with small inhomogeneities, both methods gave consistent results     

4-Gb/s transmission experiment over 117 km of optical fiber using a Ti:LiNbO3external modulator

We report a single-channel optical fiber data link with the largest bit-ratexrepeater spacing product achieved to date- ∼ 0.5 Tb . km/s. The multi-gigabit per second system is the first to incorporate a Ti:LiNbO3external modulator as the data encoder.     

8-Gbit/s transmission experiment over 68 km of optical fiber using a Ti:LiNbO3external modulator

We describe the performance of an experimental 1.5-μm lightwave transmission system operating at 8 Gbit/s over 68.3 km of single-mode fiber. The dispersion penalty is limited to 1 dB through the use of external modulation and is attributable to the intrinsic information bandwidth.