Ultrasonically actuated silicon microprobes for cardiac signal recording

In this paper, we report on ultrasonically actuated silicon thin microprobes that successfully penetrated canine cardiac tissue in vitro, and recorded the electrophysiological signals from multiple sites simultaneously within the heart wall. The penetration force--maximum force encountered by the probe during penetration--is found to reduce with increasing ultrasonic driving voltage, on both excised canine right ventricular muscle and chicken breast muscle. The rate of force decrease varies with tissue type and microprobe dimension. With ultrasonic actuation, the silicon microprobes are inserted into isolated perfused canine heart without breakage or significant buckling, under 10Vpp actuating voltage. Recordings were obtained from isolated perfused canine heart during pacing, following the induction of ventricular tachycardia, and during the transition from ventricular tachycardia to ventricular fibrillation. Local conduction velocity of 0.60 +/- 0.03 m/s was observed from the multichannel recordings from the canine right ventricular wall under epicardial pacing. The application of the ultrasonic microprobes in cardiac electrophysiology study can provide information for reconstruction of electrical wave propagation within the heart, which is important to understanding the mechanisms of cardiac arrhythmias.     

Strength characterization of silicon microprobes inneurophysiological tissues

Experimentally determined strength characteristics of thin-silicon probes in neural tissues are discussed. It is shown that by proper selection of the substrate length, width, and thickness, silicon substrates can be designed and used to penetrate a variety of biological tissues without breakage or excessive dimpling. Thin-silicon structures have a maximum fracture stress which is a factor of six larger than that of bulk silicon and are very flexible and capable of bending to angles larger than 90°. Silicon substrates 15 μm thick×30 μm wide can easily penetrate guinea pig and rat pia arachnoid layers with minimum dimpling and no breakage, while substrates 30 μm thick×80 μm wide can penetrate guinea pig and rat dura mater repeatedly without breakage. Quantitative comparison on the relative toughness of neurophysiological tissues in rat and guinea pig have also been experimentally obtained     

多基地雷达中双门限CFAR检测算法

针对多基地雷达系统,该文为解决传统集中式检测算法数据传输率大的问题,根据广义似然比检测算法和自适应匹配滤波算法,提出两种双门限恒虚警率检测器：双门限广义似然比检测器和双门限自适应匹配滤波检测器。首先各个局部雷达站将超过第1门限的局部检验统计量传送到融合中心。然后融合中心根据局部雷达站传送的数据计算融合后的全局检验统计量,并与第2门限比较,得到最终的判决结果。在各空间分集通道的信杂噪比假设相同的条件下,给出了双门限自适应匹配滤波检测器的虚警概率和检测概率的解析表达式。仿真结果表明,两种双门限检测器在低数据率传输时能够保持较好的检测性能。     

Spike detection and clustering with unsupervised wavelet optimization in extracellular neural recordings

Automatic and accurate detection of action potentials of unknown waveforms in noisy extracellular neural recordings is an important requirement for developing brain-computer interfaces. This study introduces a new, wavelet-based manifestation variable that combines the wavelet shrinkage denoising with multiscale edge detection for robustly detecting and finding the occurrence time of action potentials in noisy signals. To further improve the detection performance by eliminating the dependence of the method to the choice of the mother wavelet, we propose an unsupervised optimization for best basis selection. Moreover, another unsupervised criterion based on a correlation similarity measure was defined to update the wavelet selection during the clustering to improve the spike sorting performance. The proposed method was compared to several previously proposed methods by using a wide range of realistic simulated data as well as selected experimental recordings of intracortical signals from freely moving rats. The detection performance of the proposed method substantially surpassed previous methods for all signals tested. Moreover, updating the wavelet selection for the clustering task was shown to improve the classification performance with respect to maintaining the same wavelet as for the detection stage.     

Anti-buckling S-shaped vertical microprobes with branch springs

We propose the S-shaped vertical probes with branch springs for the wafer-level testing of IC chips. The conventional S-shaped vertical probe requires a guide structure to prevent buckling due to the large overdrive actuation involved. However, the guide structure not only increases the cost of fabrication, but it also requires a troublesome assembly procedure. In this paper, we present the S-shaped vertical probe with branch springs on the left and right sides of the main spring to prevent buckling. This probe was designed using finite-element methods and fabricated using Ni-Co electroplating. The performances of the probe for the wafer-level testing of IC chips were measured with the probe test equipments. Compared to the identical conventional S-shaped probe, the proposed probe has the overdrive (60 μm) that is 1.2 times larger and the contact force (25 mN) that is 2.5 times larger. This new S-shaped vertical probe satisfies the design requirements for a vertical probe without the guide structure and has the potential for use as a cost-effective guide-free probe card for the wafer-level testing of IC chips.     

Multisite field trial for LTE and advanced concepts

The 3GPP LTE standard is stable now in its first release (Release 8), and the question is how good its performance is in real-world scenarios. LTE is also a good base for further innovations, but it must be proven that they offer performance advantages for the price of their complexity. This article evaluates the performance of LTE Release 8 as a baseline and advanced concepts currently in discussion such as cooperative MIMO based on system-level simulations, and measurements in the laboratory and a multisite field testbed within the EASY-C project.     

Electronic music synthesis for recordings

Electronic music synthesis is a process whereby several parts or elements of a musical composition that are performed or produced as separate entities are combined to form the entire or rendered composition. Since the entire process can seldom be carried out in real time, the synthesis of music has not been a performing-type rendition; therefore, the final product takes the form of a record that can be reproduced at any given time. Electronic music synthesis includes the modification and combination of conventional and original sound sources, manual and programmed electronic music synthesizers, and digital computers.     

Voltage pulses change neural interface properties and improve unit recordings with chronically implanted microelectrodes

Current neuroprosthetic systems based on electrophysiological recording have an extended, yet finite working lifetime. Some posited lifetime-extension solutions involve improving device biocompatibility or suppressing host immune responses. Our objective was to test an alternative solution comprised of applying a voltage pulse to a microelectrode site, herein termed "rejuvenation." Previously, investigators have reported preliminary electrophysiological results by utilizing a similar voltage pulse. In this study we sought to further explore this phenomenon via two methods: 1) electrophysiology; 2) an equivalent circuit model applied to impedance spectroscopy data. The experiments were conducted via chronically implanted silicon-substrate iridium microelectrode arrays in the rat cortex. Rejuvenation voltages resulted in increased unit recording signal-to-noise ratios (10%/spl plusmn/2%), with a maximal increase of 195% from 3.74 to 11.02. Rejuvenation also reduced the electrode site impedances at 1 kHz (67%/spl plusmn/2%). Neither the impedance nor recording properties of the electrodes changed on neighboring microelectrode sites that were not rejuvenated. In the equivalent circuit model, we found a transient increase in conductivity, the majority of which corresponded to a decrease in the tissue resistance component (44%/spl plusmn/7%). These findings suggest that rejuvenation may be an intervention strategy to prolong the functional lifetime of chronically implanted microelectrodes.     

一种多基雷达接收信号相参处理的方法

常规雷达系统越来越难于探测日益迫近的空间目标和隐身目标.多基雷达已成为雷达的一个发展方向.多基雷达信息融合主要是航迹融合、点迹融合、信号级融合.文中分析了多基地雷达信号级融合--相参处理面临的问题和难于直接进行相参处理的原因,提出了一种信号相参处理的方法,仿真结果表明了该方法的有效性.     

Performance of planar multisite microprobes in recordingextracellular single-unit intracortical activity

The microprobes consist of a thin-film electrode array supported by a silicon micromachined substrate and insulated using deposited dielectrics. Microprobes with multiple recording sites spaced from 30 μm to 200 μm apart are used to record spontaneous single-unit activity from rat cerebral cortex. Additionally, a theoretical model is used to establish a basis for interpreting the multisite single-unit data. The results suggest that the microprobes (1) couple tightly to the neural tissue with relatively little disturbance to the neural system, (2) facilitate the identification of single units in multiunit records through the use of spatially-separate recording sites, and (3) can be used to detect the cell position in tissue and observe events such as the propagation of electrical activity from the soma to the dendritic tree     

Multielectrode microprobes for deep-brain stimulation fabricated with a customizable 3-D electroplating process

Although deep-brain stimulation (DBS) can be used to improve some of the severe symptoms of Parkinson's disease (e.g., Bradykinesia, rigidity, and tremors), the mechanisms by which the symptoms are eliminated are not well understood. Moreover, DBS does not prevent neurodegeneration that leads to dementia or death. In order to fully investigate DBS and to optimize its use, a comprehensive long-term stimulation study in an animal model is needed. However, since the brain region that must be stimulated, known as the subthalamic nucleus (STN), is extremely small (500 microm x 500 microm x 1 mm) and deep within the rat brain (10 mm), the stimulating probe must have geometric and mechanical properties that allow accurate positioning in the brain, while minimizing tissue damage. We have designed, fabricated, and tested a novel micromachined probe that is able to accurately stimulate the STN. The probe is designed to minimize damage to the surrounding tissue. The probe shank is coated with gold and the electrode interconnects are insulated with silicon nitride for biocompatibility. The probe has four platinum electrodes to provide a variety of spatially distributed stimuli, and is formed in a novel 3-D plating process that results in a microwire like geometry (i.e., smoothly tapering diameter) with a corresponding mechanically stable shank.     

多基地雷达自适应CFAR检测融合算法

文章针对多基地雷达的目标RCS在入射角分布起伏较大的问题,提出了基于目标入射角RCS分布未知的检测融合方法。由于目标RCS在入射电波观测角的起伏较大且未知,导致局部雷达站接收目标回波SNR（信噪比）无法确定,无法应用传统的贝叶斯方法获得最佳的融合检测性能。该方法是一种基于无信噪比信息的检测融合算法,通过传输其他雷达站接收信号的检验统计量来完成全局的CFAR检测。并且根据该方法设计了一种自适应门限的检测方法,其中本地雷达站的检测门限是基于其他雷达站接收信号的检验统计量生成。仿真结果表明,该检验方法的综合检测性能接近信噪比已知的融合检测性能。      

Model-based seizure detection for intracranial EEG recordings

This paper presents a novel model-based patient-specific method for automatic detection of seizures in the intracranial EEG recordings. The proposed method overcomes the complexities in the practical implementation of the patient-specific approach of seizure detection. The method builds a seizure model (set of basis functions) for a priori known seizure (the template seizure pattern), and uses the statistically optimal null filters as a building block for the detection of similar seizures. The process of modeling the template seizure is fully automatic. Overall, the detection method involves the segmentation of the template seizure pattern, rejection of the redundant and noisy segments, extraction of features from the segments to generate a set of models, selection of the best seizure model, and training of the classifier. The trained classifier is used to detect similar seizures in the remaining data. The resulting seizure detection method was evaluated on a total of 304 h of single-channel depth EEG recordings from 14 patients. The system performance is further compared to the Qu-Gotman patient-specific system using the same data. A significant improvement in the proposed system, in terms of specificity, is observed over the compared method.     

Processing of multichannel recordings for data-mining algorithms

Data Mining, or knowledge discovery, is the computer-assisted process of digging through and analyzing large quantity of data in order to extract meaningful knowledge. Data mining methods are used in many studies to identify phenomena quicker and better than human experts. One class of these methods was designed for dealing with time series data. However, when several channels of data are collected simultaneously, data mining algorithms encounter numerous difficulties since channels may be measured in different units, may be recorded at different sampling-rates, or may have completely different characteristics. Furthermore, as the size of these data increases, the amount of irrelevant data usually increases as well and the process becomes impractical. Hence, in such cases, the analyst must be capable of focusing on the informational parts while ignoring the noise data. These kinds of difficulties complicate the analysis of multichannel data as compared to the analysis of single-channel data. This paper presents a useful technique for preprocessing multi channel data. Our technique supplies tools for coping with all the above-mentioned difficulties, and prepares the data for further analysis (using common algorithms, especially from the data mining field). The paper is divided as follows. After the introduction (Section I) we describe the state of the art (Section II), follows by the main section-methodology (Section III) which is divided to four steps (3.2-3.5). The results are described in a separate section (Section IV). Then, a discussion and conclusions of the proposed methodology are given in (Sections V and VI). Acknowledgements and the references follow.     

Morphology-based automatic seizure detector for intracerebral EEG recordings

In this paper, a new seizure detection system aimed at assisting in a rapid review of prolonged intracerebral EEG recordings is described. It is based on quantifying the sharpness of the waveform, one of the most important electrographic EEG features utilized by experts for an accurate and reliable identification of a seizure. The waveform morphology is characterized by a measure of sharpness as defined by the slope of the half-waves. A train of abnormally sharp waves resulting from subsequent filtering are used to identify seizures. The method was optimized using 145 h of single-channel depth EEG from seven patients, and tested on another 158 h of single-channel depth EEG from another seven patients. Additionally, 725 h of depth EEG from 21 patients was utilized to assess the system performance in a multichannel configuration. Single-channel test data resulted in a sensitivity of 87% and a specificity of 71%. The multichannel test data reported a sensitivity of 81% and a specificity of 58.9%. The new system detected a wide range of seizure patterns that included rhythmic and nonrhythmic seizures of varying length, including those missed by the experts. We also compare the proposed system with a popular commercial system.     

Detection of leukocytes in contact with the vessel wall from in vivo microscope recordings using a neural network

Leukocytes play an important role in the host defense as they may travel from the blood stream into the tissue in reacting to inflammatory stimuli. The leukocyte-vessel wall interactions are studied in post capillary vessels by intravital video microscopy during in vivo animal experiments. Sequences of video images are obtained and digitized with a frame grabber. A method for automatic detection and characterization of leukocytes in the video images is developed. Individual leukocytes are detected using a neural network that is trained with synthetic leukocyte images generated using a novel stochastic model. This model makes it feasible to generate images of leukocytes with different shapes and sizes under various lighting conditions. Experiments indicate that neural networks trained with the synthetic leukocyte images perform better than networks trained with images of manually detected leukocytes. The best performing neural network trained with synthetic leukocyte images resulted in an 18% larger area under the ROC curve than the best performing neural network trained with manually detected leukocytes.     

A new optrode design for intramural optical recordings

Intramural measurements of V(m) and Ca(i)(2+) are important in the studies of cardiac arrhythmias and defibrillation. We developed a new design of an "optrode" (bundle of optical fibers) for use in intramural cardiac mapping. The optrodes are made from seven optical fibers with the fiber ends polished at 45° angle and coated with mirror surfaces. The optrodes are enclosed in smooth epoxy resin cast, which protects mirror surfaces from damage and ensures constant optrode diameter along its length. The optrodes are strong enough to be easily inserted into heart muscle, can be reused multiple times, and they may reduce artifacts in the measurements of the effects of defibrillation shocks on V(m).     

Detection, classification, and superposition resolution of actionpotentials in multiunit single-channel recordings by an on-linereal-time neural network

Determination of single-unit spike trains from multiunit recordings obtained during extracellular recording has been the focus of many studies over the last two decades. In multiunit recordings, superpositions can occur with high frequency if the firing rates of the neurons are high or correlated, making superposition resolution imperative for accurate spike train determination. In this work, a connectionist neural network (NN) was applied to the spike sorting challenge. A novel training scheme was developed which enabled the NN to resolve some superpositions using single-channel recordings. Simulated multiunit spike trains were constructed from templates and noise segments that were extracted from real extracellular recordings. The simulations were used to determine the performances of the NN and a simple matched template filter (MTF), which was used as a basis for comparison. The network performed as well as the MTF in identifying nonoverlapping spikes, and was significantly better in resolving superpositions and rejecting noise. An on-line, real-time implementation of the NN discriminator, using a high-speed digital signal processor mounted inside an IBM-PC, is now in use in six laboratories     

一种基于跟踪信息的多基雷达系统航迹起始算法

多基雷达系统(MSRS)可以大大提高目标定位性能,然而由于各个雷达站信噪比的差异,通常存在一些雷达站尚未建立目标航迹,从而不能最大程度地提高目标定位精度。因此,如何利用其它雷达站提供的目标跟踪信息,提高尚未建立目标航迹的雷达站的探测性能是一个值得研究的问题。为此,该文提出一种基于跟踪信息的航迹起始算法。首先将已经跟踪到目标的雷达站提供的目标跟踪信息,送至尚未建立目标航迹的雷达站;然后利用目标跟踪信息和目标运动模型,建立目标预测波门;最终在虚假航迹起始概率恒定的条件下,调整预测波门内的检测门限,完成目标检测和航迹起始过程。仿真实验表明,该算法可以大大提高目标检测概率和目标航迹起始概率。