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2009 14th National Biomedical Engineering Meeting最新文献

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Artificial single trial auditory evoked potential signal generator 人工单次试验听觉诱发电位信号发生器
Pub Date : 2009-05-20 DOI: 10.1109/BIYOMUT.2009.5130262
Yemen Alev Bahtiyar, Yasemin Erkan, Nurettin Acır
In this study, we introduce an artificial single trial auditory evoked potential signal generator which contributes to create the synthetic data set that are mostly used in biomedical engineering applications. The proposed system not only provides the comparison of the methods used in engineering applications but also it provides an objectivity in determining the performance of the novel systems to be designed in other studies. In this study, we have aimed to create synthetic data set by generating single trial auditory evoked potential at any arbitrary SNR level.
在这项研究中,我们介绍了一个人工的单次试验听觉诱发电位信号发生器,它有助于创建主要用于生物医学工程应用的合成数据集。所提出的系统不仅提供了工程应用中使用的方法的比较,而且为确定其他研究中要设计的新系统的性能提供了客观的依据。在本研究中,我们旨在通过在任意信噪比水平下产生单次听觉诱发电位来创建合成数据集。
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引用次数: 0
Adjusting decision threshold in Naive Bayes based IVF embryo selection 基于朴素贝叶斯的体外受精胚胎选择决策阈值调整
Pub Date : 2009-05-20 DOI: 10.1109/BIYOMUT.2009.5130302
A. Uyar, A. Bener, H. N. Ciray, M. Bahçeci
In this study, IVF embryo selection has been considered as a binary classification problem and predictibality of implantation outcome of individual embryos has been tested using Naive Bayes method. First, in order to perform classification experiments, an embryo based dataset has been constructed from database of Bahçeci IVF Centre. Since the class distribution of dataset is highly imbalanced (11% Pozitive and 89% Negative implantation outcomes) the decision threshold of Naive Bayes classifier has been optimized using the features of ROC analysis. Experimental results show that classification with optimized threshold performs better than classification with default threshold.
在本研究中,IVF胚胎选择被视为一个二元分类问题,并使用朴素贝叶斯方法对单个胚胎着床结果的可预测性进行了测试。首先,利用巴西试管婴儿中心(baheci IVF Centre)的数据库,构建了基于胚胎的分类实验数据集。由于数据集的类分布高度不平衡(11%正植入结果和89%负植入结果),利用ROC分析的特征对朴素贝叶斯分类器的决策阈值进行了优化。实验结果表明,优化阈值的分类效果优于默认阈值。
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引用次数: 2
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
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
A new wavelet transform method for processing Doppler signals 一种处理多普勒信号的小波变换新方法
Pub Date : 2009-05-20 DOI: 10.1109/BIYOMUT.2009.5130279
Gorkem Serbes, N. Aydin
Stroke, which is seen nowadays frequently, is the rapidly developing loss of brain functions due to a disturbance in the blood vessels supplying blood to the brain. The main reason for the stroke is the emboli which are particles bigger than red blood cells. Emboli can be detected by Doppler ultrasound. Embolic Doppler ultrasound signals are short duration transient like signals. These signals can be obtained from in-phase and quadrature-phase parts of the quadrature Doppler signals as forward and reverse signals by using the phase relationship between in-phase and quadrature-phase signals. Discrete wavelet transform is one of the methods used for analyzing these signals. A desired property in discrete wavelet transform is phase shift-invariance which can not be provided by ordinary discrete wavelet transform. To overcome this disadvantage dual-tree complex wavelet transform was introduced. But Doppler signals are dual channel signals and dual-tree complex wavelet transform must be applied twice. Therefore complexity of the transform increases. In this work, a new transform method reducing computational complexity is introduced.
中风,现在很常见,是由于向大脑供血的血管受到干扰而导致的大脑功能的迅速丧失。中风的主要原因是栓塞,这是一种比红细胞更大的颗粒。栓子可用多普勒超声检测。栓子多普勒超声信号是短时间的瞬态信号。这些信号可以利用正交多普勒信号的同相部分和正交相部分作为正向和反向信号,利用同相和正交相信号之间的相位关系。离散小波变换是分析这些信号的方法之一。离散小波变换所需要的一个特性是相移不变性,这是普通离散小波变换所不能提供的。为了克服这一缺点,引入了双树复小波变换。但多普勒信号是双通道信号,必须进行两次双树复小波变换。因此,变换的复杂性增加了。本文提出了一种新的降低计算复杂度的变换方法。
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引用次数: 3
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
Information and comunication technologies in the management of diabetes 信息和通信技术在糖尿病管理中的应用
Pub Date : 2009-05-20 DOI: 10.1109/BIYOMUT.2009.5130276
Süleyman Sevinç, Baris Tanir
Fast developing information and communication technologies based on internet and mobile networks have changed our daily lives in a very positive way. Take for an example Diyahat.net, an important development in health information technologies, which enables diabetics to collect, store and manage data about blood glucose measurements, medication and diet lists using mobile technologies as well as internet. Diabetics, at their own will, can schedule the system to send themselves reminder SMS messages for blood glucose measurements, doctors' visits and medication times. Doctors can monitor their patients daily, if they wish, and can update patients' files as appropriate. Therefore both doctors and patients are kept in an active two-way communication. Patients can ask questions using the system to their doctors and receive comprehensive and detailed response resulting in significant time saved both by doctors and patients. The system becomes a significant source for patient motivation and lays the ground for a very effective environment for management of diabetes. Doctors can formulate best treatments for their patients, personalized and tailored for each patient's medical needs. Research done in this area and specifically one in Korea, based on a similar approach have proven that systems like Diyahat.net can help better control of blood glucose levels and of diabetes in general.
以互联网和移动网络为基础的快速发展的信息通信技术给我们的日常生活带来了积极的变化。以Diyahat.net为例,这是卫生信息技术的一项重要发展,使糖尿病患者能够利用移动技术和互联网收集、存储和管理有关血糖测量、药物和饮食清单的数据。糖尿病患者可以根据自己的意愿,安排系统向自己发送提醒短信,提醒自己血糖测量、医生就诊和服药时间。如果医生愿意的话,他们可以每天监测病人,并适时更新病人的档案。因此,医生和病人都保持着积极的双向沟通。患者可以使用该系统向医生提出问题,并得到全面详细的答复,从而大大节省了医生和患者的时间。该系统成为患者动力的重要来源,并为糖尿病管理的非常有效的环境奠定了基础。医生可以为他们的病人制定最好的治疗方案,针对每个病人的医疗需求进行个性化定制。在这一领域的研究,特别是在韩国的研究,基于类似的方法已经证明,像Diyahat.net这样的系统可以帮助更好地控制血糖水平和糖尿病。
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引用次数: 0
FPGA based arrhythmia classifier 基于FPGA的心律失常分类器
Pub Date : 2009-05-20 DOI: 10.1109/BIYOMUT.2009.5130253
A. Ozdemir, K. Danisman, M. H. Asyali
Processing of ECG (Electro CardioGram) records by software- based systems was started in the beginning of the 1960s. Many studies on different techniques about this topic have been made in the last 20 years. ANN (Artificial Neural Network) is the tool that is mostly used in medical diagnosis systems because of the belief in its powerful prediction characteristics. However, the suggested ANN architectures in literature are very complex software-based architectures. Consequently, these models with high computational complexity can only be run on expensive processors. To enable the implementation of ANN models on mobile and cheap devices, the features of ECG signal, which are applied to ANN inputs, should be reduced. This approach enables the implementation of a simple ANN architecture. In this study, the features of ECG signal are reduced dramatically using PCA (Principle Component Analysis), while keeping the error of the ANN learning rate at an acceptable level such as 5%. As a result, a simple Matlab ANN model, which consists of eight inputs, a hidden layer with two neurons and one output neuron, is implemented on an FPGA (Field Programmable Gate Arrays) by using IEE 754 32 bits floating-point numerical representation.
20世纪60年代初,基于软件的系统开始处理心电图记录。在过去的20年里,人们对这一主题的不同技术进行了许多研究。人工神经网络(Artificial Neural Network,简称ANN)因其强大的预测特性而被广泛应用于医疗诊断系统。然而,文献中建议的人工神经网络架构是非常复杂的基于软件的架构。因此,这些具有高计算复杂度的模型只能在昂贵的处理器上运行。为了使人工神经网络模型能够在移动和廉价的设备上实现,应用于人工神经网络输入的心电信号的特征应该被减少。这种方法可以实现简单的人工神经网络体系结构。在本研究中,使用主成分分析(principal Component Analysis, PCA)对心电信号的特征进行了大幅度的还原,同时使人工神经网络学习率的误差保持在5%的可接受水平。最后,采用ieee 754 32位浮点数表示,在FPGA上实现了一个简单的Matlab人工神经网络模型,该模型由8个输入、2个神经元和1个输出神经元的隐藏层组成。
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引用次数: 7
Forward problem solution for contactless electrical conductivity imaging with realistic head model 基于真实头部模型的非接触式电导率成像正向问题求解
Pub Date : 2009-05-20 DOI: 10.1109/BIYOMUT.2009.5130295
Reyhan Zengin, N. G. Gencer
In this study, forward problem of contactless electrical conductivity imaging is solved by using realistic-head model. Realistic-head model is modelled by a single volume with the ANSYS software and divided into hexahedral elements. Conductivity information for each element is obtained from MR gray-scale images obtained as a result of segmentation.For realistic-head model, a coil of radius 1 cm, 1 cm above the scalp and carrying a sinusoidal (50 kHz) current of 1 A is used as a source. Realistic-head modelis composed of the scalp, skull, brain fluid and brain (gray matter and white matter) tissues. For each tissue magnetic flux densities and current densities have been obtained.
本研究采用现实头部模型解决了非接触式电导率成像的正向问题。实景水头模型采用ANSYS软件对单个体进行建模,并划分为六面体单元。每个元素的电导率信息从分割得到的MR灰度图像中获得。对于真实的头部模型,一个半径为1厘米的线圈,在头皮上方1厘米处,携带1 a的正弦电流(50 kHz)作为源。实景头部模型由头皮、颅骨、脑液和脑(灰质和白质)组织组成。得到了每个组织的磁通密度和电流密度。
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引用次数: 0
Human resources, vocational education and Vocational Standards in Turkish health industry: A self-evaluation of the sector 土耳其卫生行业的人力资源、职业教育和职业标准:该部门的自我评价
Pub Date : 2009-05-20 DOI: 10.1109/BIYOMUT.2009.5130353
Ilke Eren
Thi study aims at an evaluation of vocational standards and qualifications both on national and EU levels in health industry with special stres on Turkey. After mentioning the previous works on vocational qualifications realized in Turkey in the sector, the results of a survey which questioned the needs of the sector had been communicated. The study informs on the subsequent efforts to establish Vocational Standards reyling on this survey.
这项研究的目的是评估国家和欧盟卫生行业的职业标准和资格,特别强调土耳其。在提到土耳其以前在该部门开展的关于职业资格的工作之后,又通报了对该部门需求提出质疑的一项调查的结果。这项研究为根据这项调查制定职业标准的后续工作提供了信息。
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引用次数: 0
期刊
2009 14th National Biomedical Engineering Meeting
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