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2009 14th National Biomedical Engineering Meeting最新文献

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Estimation of state transition matrix in the Kalman filter based inverse ECG solution with the help of training sets 基于训练集的卡尔曼滤波心电反解状态转移矩阵估计
Pub Date : 2009-05-20 DOI: 10.1109/BIYOMUT.2009.5130254
Umit Aydin, Y. Serinağaoğlu
At this study the main motivation is to solve inverse problem of ECG with Kalman filter. In order to obtain feasible solutions determination of the state transition matrix (STM) correctly is vital. In literature the STM is usually found by using the test data itself which is not a realistic scenario. The major goal of this study is to determine STM without using test data. For that purpose a two stage method is suggested. At the first step the probability density function (pdf) is calculated using training sets and then this pdf is used to find Bayes-MAP solution which uses only spatial information. At the second step, the Bayes-MAP solution is used to find STM and later on, that STM is used in Kalman filter to obtain final results. It is seen that the results obtained with this method are better then normal Bayes-MAP results and the errors are within acceptable limits. So it is concluded that the usage of Bayes-MAP solutions in STM determination is a serious alternative for STM estimation.
本研究的主要目的是利用卡尔曼滤波解决心电信号的逆问题。为了得到可行的解,正确确定状态转移矩阵至关重要。在文献中,STM通常是通过使用测试数据本身来发现的,这不是一个现实的场景。本研究的主要目的是在不使用测试数据的情况下确定STM。为此,建议采用两阶段方法。首先使用训练集计算概率密度函数(pdf),然后使用该pdf找到仅使用空间信息的Bayes-MAP解。第二步,使用Bayes-MAP解找到STM,然后将STM用于卡尔曼滤波,得到最终结果。结果表明,该方法得到的结果优于普通的Bayes-MAP结果,误差在可接受的范围内。因此,在STM确定中使用Bayes-MAP解是STM估计的重要替代方案。
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引用次数: 1
Extraction of the liver vessels from the abdomen CTA images by Hessian-based vessel filter 基于hessian的血管滤波从腹部CTA图像中提取肝脏血管
Pub Date : 2009-05-20 DOI: 10.1109/BIYOMUT.2009.5130311
H. Dogan, O. Dicle, C. Guzelis
Prior to the liver transplantation and tumor resection operations, the extraction of the vessel system which specifies the segments of the liver, from the Computed Tomography Angiography (CTA) images is an important organ segmentation task. In this paper, the computer experiment results on the application of the Hessian based vessel filter for the extraction of the liver vessels and the labeling of the main vessels are presented.
在肝移植和肿瘤切除手术之前,从ct血管造影(CTA)图像中提取指定肝脏各部分的血管系统是一项重要的器官分割任务。本文给出了基于Hessian的血管过滤器在肝脏血管提取和主要血管标记中的计算机实验结果。
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引用次数: 2
Examining the relevance with sleep stages of time domain features of EEG, EOG, and chin EMG signals 研究脑电图、眼电图和颏肌电图信号的时域特征与睡眠阶段的相关性
Pub Date : 2009-05-20 DOI: 10.1109/BIYOMUT.2009.5130256
S. Gune, K. Polat, M. Dursun, Ş. Yosunkaya
Sleep staging has an important role in determining sleep disorders such as sleepiness, human fatigue etc. Sleep staging is generally done according to Rechtschaffen and Kales standard (RKS) using EEG signal obtained from PSG signals taken from patient subjects who come with any sleep disorders. Sleep stages are generally divided into three stages including awake, REM and N-REM (stage 1, stage 2, and stage 3). In this study, time domain features of EEG, EOG of right and left eyes, and chin EMG signals belonging to sleep stages were investigated and correlation between these time domain features and sleep stages was calculated. The used time domain features are mean value, standard deviation, peak value, skewness, kurtosis, and shape factor belonging to EEG, EOG of right and left eyes, and chin EMG signals. In experimental studies, PSG recordings of 3 subjects were taken and average recording time of 6.22 h, total recording time was 18.67 h. When investigated correlation coefficients, it is seen that skewness feature in time domain features of EEG signal, standard deviation feature in time domain features of EOG signals belonging to right and left eyes, and mean value feature in time domain features of chin EMG signal were more correlated with sleep stages than other features. Consequently, a feature vector can be constituted combining features determined from time domain features of EEG, EOG belonging to right and left eyes, and chin EMG signals. This obtained feature vector can be easily used in distinguishing sleep stages.
睡眠阶段在决定睡眠障碍(如嗜睡、人体疲劳等)方面起着重要作用。睡眠分期通常根据Rechtschaffen和Kales标准(RKS)进行,使用从患有任何睡眠障碍的患者受试者的PSG信号中获得的脑电图信号。睡眠阶段一般分为清醒、快速眼动和n -快速眼动三个阶段(第一阶段、第二阶段和第三阶段)。本研究研究了属于睡眠阶段的EEG、左右眼EOG和颏肌电信号的时域特征,并计算了这些时域特征与睡眠阶段的相关性。所使用的时域特征是EEG、左右眼EOG和颏肌电信号的均值、标准差、峰值、偏度、峰度和形状因子。在实验研究中,采集了3名被试的PSG记录,平均记录时间为6.22 h,总记录时间为18.67 h。在研究相关系数时,发现脑电信号时域特征的偏态特征、右眼和左眼EEG信号时域特征的标准差特征以及颏肌电信号时域特征的均值特征与睡眠阶段的相关性大于其他特征。由此,将EEG、左右眼EOG和颏肌电信号的时域特征组合成特征向量。得到的特征向量可以很容易地用于睡眠阶段的区分。
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引用次数: 11
Design and fabrication of a chaotic mixer for BioMEMS applications 生物机械系统混沌混频器的设计与制造
Pub Date : 2009-05-20 DOI: 10.1109/BIYOMUT.2009.5130268
G. Yilmaz, E. Bayraktar, H. Kulah
Since fabrication of microchips by MEMS technology has emerged, microchips that can interact with biological samples like virus, bacteria, DNA has been developed. Considering the advantages such as cost, dimension and compatibility with IC fabrication, these chips have found specific application areas. Microfluids and microfluidics constitute one of the major research areas of this emerging field, BioMEMS. Micro mixers have become an important component of BioMEMS which are designed for microfluidics applications. Fluids demonstrate two types of flow regime, laminar and turbulent. Turbulent flow is more advantageous than laminar flow when mixing is considered. Creating turbulent flow within microchannels, commonly used in BioMEMS devices, is a challenging task as scaling into the micro domain causes fluids to mix solely by diffusion. This study presents a method for mixing in micro environment based on chaotic advection. The proposed micro mixer makes use of the turbulent flow induced by bubbles which are created by thermal actuation based on joule heating principle on gold electrodes.
随着利用MEMS技术制造微芯片的出现,可以与病毒、细菌、DNA等生物样品相互作用的微芯片已经被开发出来。考虑到成本、尺寸和与集成电路制造的兼容性等优势,这些芯片已经找到了特定的应用领域。微流体和微流体构成了生物医学领域这个新兴领域的主要研究领域之一。微混合器已成为生物医学系统的重要组成部分,它是为微流体应用而设计的。流体表现出两种流动形式,层流和湍流。当考虑混合时,湍流比层流更有利。通常用于BioMEMS设备的微通道内产生湍流是一项具有挑战性的任务,因为缩放到微域会导致流体仅通过扩散混合。提出了一种基于混沌平流的微环境混合方法。本文提出的微型混合器利用了基于焦耳加热原理的热致动在金电极上产生气泡所引起的湍流。
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引用次数: 0
Improvement of mechanical performances by plasma polymerisation technique for composite biomaterials 等离子体聚合技术对复合生物材料力学性能的改善
Pub Date : 2009-05-20 DOI: 10.1109/BIYOMUT.2009.5130313
Tuba Durmaz, S. Erkut, Dilek Cokeliler
In recent years, fibers are used for improving mechanical strength of acrylic-based resin which used for construction of protheses frequently. Improvement of the fiber- matrix interfase is a very important approach at redevelopment of mechanical properties. In this study, glass fibers are modified by radiofrequency (RF) plasma technique with using different monomers. Silane based monomer glisitoxypropyltrimethiloxysilane and amine based ethylenediamine (EDA)are polimerized on the glass fibers in plasma environment for application of two different approaches (hydrophobic/hydrophobic). Surface modification application is optimized with increasing power and exposure time parameters, which are used for low vacuum RF glow discharge. The change of surface properties for glass fibers are characterized by measurement of static contact angle and bending strain of fiber-acrylic composites are measured with 3 point bending device. While the cost of bending strain of the composites, which is prepared by virgin glass fibers, is 127.9±9 MPa, the maximum mechanical strength has been obtained at amine based plasma polymerization technique (150.2±4 MPa). The mechanical strenght is improved according to the working parameters that are used in silane based plasma polymerisation technique (141.2±7 MPa, power: 40W, Exposure Time: 30 min) It's proved with contact angle measurement that gaining less hydrofobic property to the surface is an appropriate approach.
近年来,纤维被广泛用于提高丙烯酸基树脂的机械强度,丙烯酸基树脂经常用于假体的建造。改善纤维基界面是提高材料力学性能的重要途径。本研究采用射频等离子体技术,采用不同的单体对玻璃纤维进行改性。以硅烷基单体glisitoxypropyltrimethiloxysilane和胺基乙二胺(EDA)为材料,在等离子体环境下在玻璃纤维上进行了疏水/疏水两种不同途径的聚合。随着功率和曝光时间参数的增加,优化了表面改性应用,用于低真空射频辉光放电。通过静态接触角的测量来表征玻璃纤维表面性能的变化,并利用三点弯曲装置测量了纤维-丙烯酸复合材料的弯曲应变。由原始玻璃纤维制备的复合材料的弯曲应变成本为127.9±9 MPa,而胺基等离子体聚合技术获得的最大机械强度为150.2±4 MPa。根据硅烷基等离子体聚合技术的工作参数(141.2±7 MPa,功率:40W,曝光时间:30 min),提高了材料的机械强度,并通过接触角测量证明了减少表面的疏水性是一种合适的方法。
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引用次数: 1
Design and Implementation of Electrospinning System 静电纺丝系统的设计与实现
Pub Date : 2009-05-20 DOI: 10.1109/BIYOMUT.2009.5130365
Mustafa Doğan, Okan Karatay, Dilek Cokeliler, I. Kocum
Various methods for fabricating nanoscale polymeric fibers are investigated at large, e.g. tissue engineering . Electrospinning is the most versatile process among them. Materials such as polymer, composites and metal nanofibres have been fabricated with electrospinning techniques. It is important that many parameters and post, pre-processes should be investigated thoroughly to be able to optimize the method. Characteristics of the electrostatic field, and polymer solution constitute the main design criteria. The proposed experimental setup has been implemented with newly designed high voltage power suply which can be adjusted resiliently in frequency and power amplitude.
各种制造纳米级聚合物纤维的方法被广泛研究,例如组织工程。静电纺丝是其中用途最广的一种工艺。聚合物、复合材料和金属纳米纤维等材料已经用静电纺丝技术制造出来。重要的是,许多参数和后,预处理应彻底调查,以便能够优化方法。静电场和聚合物溶液的特性构成了主要的设计准则。实验装置采用新设计的可弹性调节频率和功率幅值的高压电源。
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引用次数: 1
Detection of BIS stage levels via fuzzy clustering approach 利用模糊聚类方法检测BIS阶段水平
Pub Date : 2009-05-20 DOI: 10.1109/BIYOMUT.2009.5130356
Gözde Ulutagay, E. Nasibov
In this study, FCM (Fuzzy c-Means) and FN-DBSCAN (Fuzzy Neighborhood DBSCAN) based algorithms are handled in order to use clustering methods in the determination of the stage values of BIS series data. The FN-DBSCAN algorithm is advantageous in such a way that it integrates the speed of the well-known DBSCAN (Density Based Spatial Clustering of Applications with Noise) and the robustness of the NRFJP (Noise-Robust Fuzzy Joint Points) algorithms. Such a property provides an advantage also in the detection of stable interval epochs. As a result of the computational experiments, we can conclude that FN-DBSCAN-based algorithm gives more realistic results than the FCM-based algorithm to recognize the stable duration intervals and the BIS stages in the measurement series.
本研究采用FCM (Fuzzy c-Means)和FN-DBSCAN (Fuzzy邻域DBSCAN)算法,利用聚类方法确定BIS序列数据的阶段值。FN-DBSCAN算法的优势在于它集成了著名的DBSCAN(基于噪声的应用的密度空间聚类)的速度和NRFJP(噪声-鲁棒模糊连接点)算法的鲁棒性。这种性质也为稳定区间期的探测提供了优势。计算实验结果表明,基于fn - dbscan的算法在识别测量序列中的稳定持续时间间隔和BIS阶段方面比基于fcm的算法更加真实。
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引用次数: 1
Preparation and characterization of chitosan containing acrylic bone cement formulations 壳聚糖丙烯酸骨水泥配方的制备与表征
Pub Date : 2009-05-20 DOI: 10.1109/BIYOMUT.2009.5130382
T. Endogan, A. Kiziltay, N. Hasirci
Bone cements are used in orthopaedic surgery and dentistry, and the commonly used commercial ones are prepared from poly (methylmethacrylate) (PMMA). In orthopaedic surgery bone cements are used as filling agents for the treatment of damaged tissues and they are used to stabilize the prosthesis by providing the mechanical interlock between bone and metal during the use of metal prothesis and to provide the homogeneous distribution of applied load. In this study, bone cements compositions were prepared by using two different PMMA (microspheres prepared by suspension polymerization and ground and sieved PMMA particles). Compositions were prepared by addition of hydroxyapatite (HA) as inorganic load carrying substance, and barium sulphate (BaSO4) as opacifier. To increase biocompatibility of the prepared bone cements, natural polymer chitosan was added. It was observed that addition of chitosan had a positive effect on mechanical properties.
骨水泥用于骨科手术和牙科,常用的商用骨水泥由聚甲基丙烯酸甲酯(PMMA)制备。在骨科手术中,骨水泥被用作治疗受损组织的填充剂,在金属假体使用过程中,它们通过提供骨和金属之间的机械联锁来稳定假体,并提供施加载荷的均匀分布。在本研究中,用两种不同的PMMA(悬浮聚合制备的微球和磨碎和筛过的PMMA颗粒)制备骨水泥组合物。以羟基磷灰石(HA)为无机承载物质,硫酸钡(BaSO4)为混浊剂制备复合材料。为了提高骨水泥的生物相容性,添加了天然聚合物壳聚糖。观察到壳聚糖的加入对其力学性能有积极的影响。
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引用次数: 0
EEG and sLORETA: The Dichotic Listening test preliminary results EEG和sLORETA:二分性听力测试的初步结果
Pub Date : 2009-05-20 DOI: 10.1109/BIYOMUT.2009.5130386
M. Ozgoren, O. Bayazit, Ugras Erdogan, A. Oniz
Dichotic Listening (DL) paradigm which indicates the brain asymmetry behaviorally is a non-invasive neurocognitive method. Phonetic combinations are used in this method. During the DL paradigm, recently developed system is able to mark the time point on the continuous electroencephalography (EEG) at which the DL stimulus is applied to the person in real time. By applying this new method, DL paradigm, we can evaluate the event related potentials of each ear advantages. Also we can elucidate how auditory system processes the knowledge. In this preliminary study, the main aim was to apply the standardized “Low Resolution Electromagnetic Tomography“ (sLORETA) method to EEG data of DL paradigm. Secondly, sLORETA was applied to different ear advantage (heteronymous and homonymous) event related potentials (ERPs) as a new approach. The preliminary results indicate that for the heteronymous condition the activation found in the superior temporal gyrus in the early stages, moves to central frontal gyrus in the late stages. The differences between the conditions of heteronymous and homonymous arise in frontal activation in the late stages. These findings which indicate the spatial-temporal resolution of the brain's dynamic processing can be beneficial for the clinical applications.
二元聆听(DL)范式是一种非侵入性的神经认知方法,它揭示了大脑行为的不对称性。这种方法使用语音组合。在深度学习范式中,最近开发的系统能够在连续脑电图(EEG)上标记出深度学习刺激实时施加于人的时间点。利用这种新的方法,即深度学习范式,我们可以评估每个耳优势的事件相关电位。我们还可以阐明听觉系统是如何处理知识的。在本初步研究中,主要目的是将标准化的“低分辨率电磁断层扫描”(sLORETA)方法应用于深度学习范式的脑电数据。其次,将sLORETA作为一种新的方法应用于不同耳优势(异名和同名)事件相关电位(ERPs)。初步结果表明,在异位条件下,早期在颞上回发现的激活在晚期转移到额叶中央回。异名和同名条件的差异出现在后期的额叶激活上。这些发现表明,大脑动态处理的时空分辨率可用于临床应用。
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引用次数: 0
Estimation of quasi-linear viscoelastic material parameters using nonlinear optimization method 用非线性优化方法估计准线性粘弹性材料参数
Pub Date : 2009-05-20 DOI: 10.1109/BIYOMUT.2009.5130343
Firat Dogan, M. S. Çelebi
The soft tissues are considered as complex materials which are difficult to be modeled due to their nonlinear geometric and material properties, their multilayer structures, large displacements, anisotropic, nonhomogenous and viscoelastic material properties. This study focuses on the error minimization and converge problem in predicting the non-unique material parameters of quasi-linear (QLV) integral form by Fung [5] which is used in modeling viscoelastic material properties of soft tissues. The solution is improved by using refined nonlinear optimization method.
软组织是一种复杂的材料,由于其非线性的几何和材料特性、多层结构、大位移、各向异性、非均匀性和粘弹性等特性而难以建模。本研究主要针对Fung[5]在软组织粘弹性材料特性建模中所使用的准线性(QLV)积分形式的非唯一材料参数预测中的误差最小化和收敛问题。采用改进的非线性优化方法对求解结果进行了改进。
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引用次数: 3
期刊
2009 14th National Biomedical Engineering Meeting
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