Computational and Mathematical Methods in Medicine The latest articles from Hindawi Publishing Corporation © 2014 , Hindawi Publishing Corporation . All rights reserved. Craniofacial Reconstruction Evaluation by Geodesic Network Wed, 20 Aug 2014 10:48:57 +0000 Craniofacial reconstruction is to estimate an individual’s face model from its skull. It has a widespread application in forensic medicine, archeology, medical cosmetic surgery, and so forth. However, little attention is paid to the evaluation of craniofacial reconstruction. This paper proposes an objective method to evaluate globally and locally the reconstructed craniofacial faces based on the geodesic network. Firstly, the geodesic networks of the reconstructed craniofacial face and the original face are built, respectively, by geodesics and isogeodesics, whose intersections are network vertices. Then, the absolute value of the correlation coefficient of the features of all corresponding geodesic network vertices between two models is taken as the holistic similarity, where the weighted average of the shape index values in a neighborhood is defined as the feature of each network vertex. Moreover, the geodesic network vertices of each model are divided into six subareas, that is, forehead, eyes, nose, mouth, cheeks, and chin, and the local similarity is measured for each subarea. Experiments using 100 pairs of reconstructed craniofacial faces and their corresponding original faces show that the evaluation by our method is roughly consistent with the subjective evaluation derived from thirty-five persons in five groups. Junli Zhao, Cuiting Liu, Zhongke Wu, Fuqing Duan, Kang Wang, Taorui Jia, and Quansheng Liu Copyright © 2014 Junli Zhao et al. All rights reserved. A Patient-Specific Airway Branching Model for Mechanically Ventilated Patients Wed, 20 Aug 2014 09:16:29 +0000 Background. Respiratory mechanics models have the potential to guide mechanical ventilation. Airway branching models (ABMs) were developed from classical fluid mechanics models but do not provide accurate models of in vivo behaviour. Hence, the ABM was improved to include patient-specific parameters and better model observed behaviour (ABMps). Methods. The airway pressure drop of the ABMps was compared with the well-accepted dynostatic algorithm (DSA) in patients diagnosed with acute respiratory distress syndrome (ARDS). A scaling factor (α) was used to equate the area under the pressure curve (AUC) from the ABMps to the AUC of the DSA and was linked to patient state. Results. The ABMps recorded a median α value of 0.58 (IQR: 0.54–0.63; range: 0.45–0.66) for these ARDS patients. Significantly lower α values were found for individuals with chronic obstructive pulmonary disease (). Conclusion. The ABMps model allows the estimation of airway pressure drop at each bronchial generation with patient-specific physiological measurements and can be generated from data measured at the bedside. The distribution of patient-specific α values indicates that the overall ABM can be readily improved to better match observed data and capture patient condition. Nor Salwa Damanhuri, Paul D. Docherty, Yeong Shiong Chiew, Erwin J. van Drunen, Thomas Desaive, and J. Geoffrey Chase Copyright © 2014 Nor Salwa Damanhuri et al. All rights reserved. Biomedical Relation Extraction: From Binary to Complex Tue, 19 Aug 2014 12:05:53 +0000 Biomedical relation extraction aims to uncover high-quality relations from life science literature with high accuracy and efficiency. Early biomedical relation extraction tasks focused on capturing binary relations, such as protein-protein interactions, which are crucial for virtually every process in a living cell. Information about these interactions provides the foundations for new therapeutic approaches. In recent years, more interests have been shifted to the extraction of complex relations such as biomolecular events. While complex relations go beyond binary relations and involve more than two arguments, they might also take another relation as an argument. In the paper, we conduct a thorough survey on the research in biomedical relation extraction. We first present a general framework for biomedical relation extraction and then discuss the approaches proposed for binary and complex relation extraction with focus on the latter since it is a much more difficult task compared to binary relation extraction. Finally, we discuss challenges that we are facing with complex relation extraction and outline possible solutions and future directions. Deyu Zhou, Dayou Zhong, and Yulan He Copyright © 2014 Deyu Zhou et al. All rights reserved. Delay Differential Model for Tumour-Immune Response with Chemoimmunotherapy and Optimal Control Thu, 14 Aug 2014 00:00:00 +0000 We present a delay differential model with optimal control that describes the interactions of the tumour cells and immune response cells with external therapy. The intracellular delay is incorporated into the model to justify the time required to stimulate the effector cells. The optimal control variables are incorporated to identify the best treatment strategy with minimum side effects by blocking the production of new tumour cells and keeping the number of normal cells above 75% of its carrying capacity. Existence of the optimal control pair and optimality system are established. Pontryagin’s maximum principle is applicable to characterize the optimal controls. The model displays a tumour-free steady state and up to three coexisting steady states. The numerical results show that the optimal treatment strategies reduce the tumour cells load and increase the effector cells after a few days of therapy. The performance of combination therapy protocol of immunochemotherapy is better than the standard protocol of chemotherapy alone. F. A. Rihan, D. H. Abdelrahman, F. Al-Maskari, F. Ibrahim, and M. A. Abdeen Copyright © 2014 F. A. Rihan et al. All rights reserved. Predictions of the Length of Lumbar Puncture Needles Wed, 13 Aug 2014 12:23:32 +0000 Introduction. The lumbar puncture is a well-known neurological procedure. The purpose of this study is to build an accurate mathematical formula to estimate the appropriate depth for inserting a lumbar puncture needle for a beginner. Methods. This is a retrospective study of patients who underwent magnetic resonance imaging (MRI) of the L-spine. The depth from the skin to the posterior and anterior margin of the spinal canal at the level of L4-L5 and L3-L4 interspaces of the spine was estimated using MRI. Results. Three hundred sixty-eight patients aged between 20 and 89 years were studied. The optimal puncture depths of the lumbar puncture needle were moderately strongly related to weight and BMI. The most accurate models with the highest coefficient of determination were 1.27 + 0.18 × BMI and 1.68 + 0.067 × weight (kg) for man and woman, respectively. Conclusion. The best formula for men and women provides the most accurate estimates for adults based on the MRI of the L-spine. Hon-Ping Ma, Yun-Fei Hung, Shin-Han Tsai, and Ju-chi Ou Copyright © 2014 Hon-Ping Ma et al. All rights reserved. Pressure Dynamic Characteristics of Pressure Controlled Ventilation System of a Lung Simulator Wed, 13 Aug 2014 08:30:51 +0000 Mechanical ventilation is an important life support treatment of critically ill patients, and air pressure dynamics of human lung affect ventilation treatment effects. In this paper, in order to obtain the influences of seven key parameters of mechanical ventilation system on the pressure dynamics of human lung, firstly, mechanical ventilation system was considered as a pure pneumatic system, and then its mathematical model was set up. Furthermore, to verify the mathematical model, a prototype mechanical ventilation system of a lung simulator was proposed for experimental study. Last, simulation and experimental studies on the air flow dynamic of the mechanical ventilation system were done, and then the pressure dynamic characteristics of the mechanical system were obtained. The study can be referred to in the pulmonary diagnostics, treatment, and design of various medical devices or diagnostic systems. Yan Shi, Shuai Ren, Maolin Cai, Weiqing Xu, and Qiyou Deng Copyright © 2014 Yan Shi et al. All rights reserved. NIM: A Node Influence Based Method for Cancer Classification Mon, 11 Aug 2014 08:18:27 +0000 The classification of different cancer types owns great significance in the medical field. However, the great majority of existing cancer classification methods are clinical-based and have relatively weak diagnostic ability. With the rapid development of gene expression technology, it is able to classify different kinds of cancers using DNA microarray. Our main idea is to confront the problem of cancer classification using gene expression data from a graph-based view. Based on a new node influence model we proposed, this paper presents a novel high accuracy method for cancer classification, which is composed of four parts: the first is to calculate the similarity matrix of all samples, the second is to compute the node influence of training samples, the third is to obtain the similarity between every test sample and each class using weighted sum of node influence and similarity matrix, and the last is to classify each test sample based on its similarity between every class. The data sets used in our experiments are breast cancer, central nervous system, colon tumor, prostate cancer, acute lymphoblastic leukemia, and lung cancer. experimental results showed that our node influence based method (NIM) is more efficient and robust than the support vector machine, K-nearest neighbor, C4.5, naive Bayes, and CART. Yiwen Wang, Min Yao, and Jianhua Yang Copyright © 2014 Yiwen Wang et al. All rights reserved. A DAQ-Device-Based Continuous Wave Near-Infrared Spectroscopy System for Measuring Human Functional Brain Activity Sun, 10 Aug 2014 13:24:28 +0000 In the last two decades, functional near-infrared spectroscopy (fNIRS) is getting more and more popular as a neuroimaging technique. The fNIRS instrument can be used to measure local hemodynamic response, which indirectly reflects the functional neural activities in human brain. In this study, an easily implemented way to establish DAQ-device-based fNIRS system was proposed. Basic instrumentation components (light sources driving, signal conditioning, sensors, and optical fiber) of the fNIRS system were described. The digital in-phase and quadrature demodulation method was applied in LabVIEW software to distinguish light sources from different emitters. The effectiveness of the custom-made system was verified by simultaneous measurement with a commercial instrument ETG-4000 during Valsalva maneuver experiment. The light intensity data acquired from two systems were highly correlated for lower wavelength (Pearson’s correlation coefficient = 0.92, < 0.01) and higher wavelength ( = 0.84, < 0.01). Further, another mental arithmetic experiment was implemented to detect neural activation in the prefrontal cortex. For 9 participants, significant cerebral activation was detected in 6 subjects ( < 0.05) for oxyhemoglobin and in 8 subjects ( < 0.01) for deoxyhemoglobin. Gang Xu, Xiaoli Li, Duan Li, and Xiaomin Liu Copyright © 2014 Gang Xu et al. All rights reserved. Different Perception of Musical Stimuli in Patients with Monolateral and Bilateral Cochlear Implants Thu, 07 Aug 2014 07:53:09 +0000 The aim of the present study is to measure the perceived pleasantness during the observation of a musical video clip in a group of cochlear implanted adult patients when compared to a group of normal hearing subjects. This comparison was performed by using the imbalance of the EEG power spectra in alpha band over frontal areas as a metric for the perceived pleasantness. Subjects were asked to watch a musical video clip in three different experimental conditions: with the original audio included (Norm), with a distorted version of the audio (Dist), and without the audio (Mute). The frontal EEG imbalance between the estimated power spectra for the left and right prefrontal areas has been calculated to investigate the differences among the two populations. Results suggested that the perceived pleasantness of the musical video clip in the normal hearing population and in the bilateral cochlear implanted populations has similar range of variation across the different stimulations (Norm, Dist, and Mute), when compared to the range of variation of video clip’s pleasantness for the monolateral cochlear implanted population. A similarity exists in the trends of the perceived pleasantness across the different experimental conditions in the mono- and bilaterally cochlear implanted patients. Anton Giulio Maglione, Giovanni Vecchiato, Carlo Antonio Leone, Rosa Grassia, Franco Mosca, Alfredo Colosimo, Paolo Malerba, and Fabio Babiloni Copyright © 2014 Anton Giulio Maglione et al. All rights reserved. Application of Multivariate Modeling for Radiation Injury Assessment: A Proof of Concept Thu, 07 Aug 2014 00:00:00 +0000 Multivariate radiation injury estimation algorithms were formulated for estimating severe hematopoietic acute radiation syndrome (H-ARS) injury (i.e., response category three or RC3) in a rhesus monkey total-body irradiation (TBI) model. Classical CBC and serum chemistry blood parameters were examined prior to irradiation (d 0) and on d 7, 10, 14, 21, and 25 after irradiation involving 24 nonhuman primates (NHP) (Macaca mulatta) given 6.5-Gy 60Co Υ-rays (0.4 Gy min−1) TBI. A correlation matrix was formulated with the RC3 severity level designated as the “dependent variable” and independent variables down selected based on their radioresponsiveness and relatively low multicollinearity using stepwise-linear regression analyses. Final candidate independent variables included CBC counts (absolute number of neutrophils, lymphocytes, and platelets) in formulating the “CBC” RC3 estimation algorithm. Additionally, the formulation of a diagnostic CBC and serum chemistry “CBC-SCHEM” RC3 algorithm expanded upon the CBC algorithm model with the addition of hematocrit and the serum enzyme levels of aspartate aminotransferase, creatine kinase, and lactate dehydrogenase. Both algorithms estimated RC3 with over 90% predictive power. Only the CBC-SCHEM RC3 algorithm, however, met the critical three assumptions of linear least squares demonstrating slightly greater precision for radiation injury estimation, but with significantly decreased prediction error indicating increased statistical robustness. David L. Bolduc, Vilmar Villa, David J. Sandgren, G. David Ledney, William F. Blakely, and Rolf Bünger Copyright © 2014 David L. Bolduc et al. All rights reserved. Variational Principles for Buckling of Microtubules Modeled as Nonlocal Orthotropic Shells Tue, 05 Aug 2014 09:43:33 +0000 A variational principle for microtubules subject to a buckling load is derived by semi-inverse method. The microtubule is modeled as an orthotropic shell with the constitutive equations based on nonlocal elastic theory and the effect of filament network taken into account as an elastic surrounding. Microtubules can carry large compressive forces by virtue of the mechanical coupling between the microtubules and the surrounding elastic filament network. The equations governing the buckling of the microtubule are given by a system of three partial differential equations. The problem studied in the present work involves the derivation of the variational formulation for microtubule buckling. The Rayleigh quotient for the buckling load as well as the natural and geometric boundary conditions of the problem is obtained from this variational formulation. It is observed that the boundary conditions are coupled as a result of nonlocal formulation. It is noted that the analytic solution of the buckling problem for microtubules is usually a difficult task. The variational formulation of the problem provides the basis for a number of approximate and numerical methods of solutions and furthermore variational principles can provide physical insight into the problem. Sarp Adali Copyright © 2014 Sarp Adali. All rights reserved. Computer Implementation of a New Therapeutic Model for GBM Tumor Tue, 05 Aug 2014 00:00:00 +0000 Modeling the tumor behavior in the host organ as function of time and radiation dose has been a major study in the previous decades. Here the effort in estimation of cancerous and normal cell proliferation and growth in glioblastoma multiform (GBM) tumor is presented. This paper introduces a new mathematical model in the form of differential equation of tumor growth. The model contains dose delivery amount in the treatment scheme as an input term. It also can be utilized to optimize the treatment process in order to increase the patient survival period. Gene expression programming (GEP) as a new concept is used for estimating this model. The LQ model has also been applied to GEP as an initial value, causing acceleration and improvement of the algorithm estimation. The model shows the number of the tumor and normal brain cells during the treatment process using the status of normal and cancerous cells in the initiation of treatment, the timing and amount of dose delivery to the patient, and a coefficient that describes the brain condition. A critical level is defined for normal cell when the patient’s death occurs. In the end the model has been verified by clinical data obtained from previous accepted formulae and some of our experimental resources. The proposed model helps to predict tumor growth during treatment process in which further treatment processes can be controlled. Ali Jamali Nazari, Dariush Sardari, Ahmad Reza Vali, and Keivan Maghooli Copyright © 2014 Ali Jamali Nazari et al. All rights reserved. Comparison of Two Methods Forecasting Binding Rate of Plasma Protein Mon, 04 Aug 2014 06:12:33 +0000 By introducing the descriptors calculated from the molecular structure, the binding rates of plasma protein (BRPP) with seventy diverse drugs are modeled by a quantitative structure-activity relationship (QSAR) technique. Two algorithms, heuristic algorithm (HA) and support vector machine (SVM), are used to establish linear and nonlinear models to forecast BRPP. Empirical analysis shows that there are good performances for HA and SVM with cross-validation correlation coefficients of 0.80 and 0.83. Comparing HA with SVM, it was found that SVM has more stability and more robustness to forecast BRPP. Liu Hongjiu and Hu Yanrong Copyright © 2014 Liu Hongjiu and Hu Yanrong. All rights reserved. Advances and Computational Tools towards Predictable Design in Biological Engineering Sun, 03 Aug 2014 12:52:41 +0000 The design process of complex systems in all the fields of engineering requires a set of quantitatively characterized components and a method to predict the output of systems composed by such elements. This strategy relies on the modularity of the used components or the prediction of their context-dependent behaviour, when parts functioning depends on the specific context. Mathematical models usually support the whole process by guiding the selection of parts and by predicting the output of interconnected systems. Such bottom-up design process cannot be trivially adopted for biological systems engineering, since parts function is hard to predict when components are reused in different contexts. This issue and the intrinsic complexity of living systems limit the capability of synthetic biologists to predict the quantitative behaviour of biological systems. The high potential of synthetic biology strongly depends on the capability of mastering this issue. This review discusses the predictability issues of basic biological parts (promoters, ribosome binding sites, coding sequences, transcriptional terminators, and plasmids) when used to engineer simple and complex gene expression systems in Escherichia coli. A comparison between bottom-up and trial-and-error approaches is performed for all the discussed elements and mathematical models supporting the prediction of parts behaviour are illustrated. Lorenzo Pasotti and Susanna Zucca Copyright © 2014 Lorenzo Pasotti and Susanna Zucca. All rights reserved. Computerized Neuropsychological Assessment in Aging: Testing Efficacy and Clinical Ecology of Different Interfaces Thu, 24 Jul 2014 08:30:43 +0000 Digital technologies have opened new opportunities for psychological testing, allowing new computerized testing tools to be developed and/or paper and pencil testing tools to be translated to new computerized devices. The question that rises is whether these implementations may introduce some technology-specific effects to be considered in neuropsychological evaluations. Two core aspects have been investigated in this work: the efficacy of tests and the clinical ecology of their administration (the ability to measure real-world test performance), specifically (1) the testing efficacy of a computerized test when response to stimuli is measured using a touch-screen compared to a conventional mouse-control response device; (2) the testing efficacy of a computerized test with respect to different input modalities (visual versus verbal); and (3) the ecology of two computerized assessment modalities (touch-screen and mouse-control), including preference measurements of participants. Our results suggest that (1) touch-screen devices are suitable for administering experimental tasks requiring precise timings for detection, (2) intrinsic nature of neuropsychological tests should always be respected in terms of stimuli presentation when translated to new digitalized environment, and (3) touch-screen devices result in ecological instruments being proposed for the computerized administration of neuropsychological tests with a high level of preference from elderly people. Matteo Canini, Petronilla Battista, Pasquale Anthony Della Rosa, Eleonora Catricalà, Christian Salvatore, Maria Carla Gilardi, and Isabella Castiglioni Copyright © 2014 Matteo Canini et al. All rights reserved. PLI Cancellation in ECG Signal Based on Adaptive Filter by Using Wiener-Hopf Equation for Providing Initial Condition Wed, 23 Jul 2014 10:57:34 +0000 This paper presents a technique for finding the optimal initial weight for adaptive filter by using difference equation. The obtained analytical response of the system identifies the appropriate weights for the system and shows that the MSE depends on the initial weight. The proposed technique is applied to eliminate the known frequency power line interference (PLI) signal in the electrocardiogram (ECG) signal. The PLI signal is considered as a combination of cosine and sine signals. The adaptive filter, therefore, attempts to adjust the amplitude of cosine and sine signals to synthesize a reference signal very similar to the contaminated PLI signal. To compare the potential of the proposed technique to other techniques, the system is simulated by using the Matlab program and the TMS320C6713 digital board. The simulation results demonstrate that the proposed technique enables the system to eliminate the PLI signal with the fastest time and gains the superior results of the recovered ECG signal. Anchalee Manosueb, Jeerasuda Koseeyaporn, and Paramote Wardkein Copyright © 2014 Anchalee Manosueb et al. All rights reserved. Neurophysiological Tools to Investigate Consumer’s Gender Differences during the Observation of TV Commercials Wed, 23 Jul 2014 08:35:52 +0000 Neuromarketing is a multidisciplinary field of research whose aim is to investigate the consumers’ reaction to advertisements from a neuroscientific perspective. In particular, the neuroscience field is thought to be able to reveal information about consumer preferences which are unobtainable through conventional methods, including submitting questionnaires to large samples of consumers or performing psychological personal or group interviews. In this scenario, we performed an experiment in order to investigate cognitive and emotional changes of cerebral activity evaluated by neurophysiologic indices during the observation of TV commercials. In particular, we recorded the electroencephalographic (EEG), galvanic skin response (GSR), and heart rate (HR) in a group of 28 healthy subjects during the observation of a series of TV advertisements that have been grouped by commercial categories. Comparisons of cerebral indices have been performed to highlight gender differences between commercial categories and scenes of interest of two specific commercials. Findings show how EEG methodologies, along with the measurements of autonomic variables, could be used to obtain hidden information to marketers not obtainable otherwise. Most importantly, it was suggested how these tools could help to analyse the perception of TV advertisements and differentiate their production according to the consumer’s gender. Giovanni Vecchiato, Anton Giulio Maglione, Patrizia Cherubino, Barbara Wasikowska, Agata Wawrzyniak, Anna Latuszynska, Malgorzata Latuszynska, Kesra Nermend, Ilenia Graziani, Maria Rita Leucci, Arianna Trettel, and Fabio Babiloni Copyright © 2014 Giovanni Vecchiato et al. All rights reserved. Analysis of Epileptic Seizures with Complex Network Wed, 23 Jul 2014 07:25:05 +0000 Epilepsy is a disease of abnormal neural activities involving large area of brain networks. Until now the nature of functional brain network associated with epilepsy is still unclear. Recent researches indicate that the small world or scale-free attributes and the occurrence of highly clustered connection patterns could represent a general organizational principle in the human brain functional network. In this paper, we seek to find whether the small world or scale-free property of brain network is correlated with epilepsy seizure formation. A mass neural model was adopted to generate multiple channel EEG recordings based on regular, small world, random, and scale-free network models. Whether the connection patterns of cortical networks are directly associated with the epileptic seizures was investigated. The results showed that small world and scale-free cortical networks are highly correlated with the occurrence of epileptic seizures. In particular, the property of small world network is more significant during the epileptic seizures. Yan Ni, Yinghua Wang, Tao Yu, and Xiaoli Li Copyright © 2014 Yan Ni et al. All rights reserved. Optimal Treatment Strategy for a Tumor Model under Immune Suppression Wed, 23 Jul 2014 00:00:00 +0000 We propose a mathematical model describing tumor-immune interactions under immune suppression. These days evidences indicate that the immune suppression related to cancer contributes to its progression. The mathematical model for tumor-immune interactions would provide a new methodology for more sophisticated treatment options of cancer. To do this we have developed a system of 11 ordinary differential equations including the movement, interaction, and activation of NK cells, CD8+T-cells, CD4+T cells, regulatory T cells, and dendritic cells under the presence of tumor and cytokines and the immune interactions. In addition, we apply two control therapies, immunotherapy and chemotherapy to the model in order to control growth of tumor. Using optimal control theory and numerical simulations, we obtain appropriate treatment strategies according to the ratio of the cost for two therapies, which suggest an optimal timing of each administration for the two types of models, without and with immunosuppressive effects. These results mean that the immune suppression can have an influence on treatment strategies for cancer. Kwang Su Kim, Giphil Cho, and Il Hyo Jung Copyright © 2014 Kwang Su Kim et al. All rights reserved. A Biological Hierarchical Model Based Underwater Moving Object Detection Tue, 22 Jul 2014 09:59:09 +0000 Underwater moving object detection is the key for many underwater computer vision tasks, such as object recognizing, locating, and tracking. Considering the super ability in visual sensing of the underwater habitats, the visual mechanism of aquatic animals is generally regarded as the cue for establishing bionic models which are more adaptive to the underwater environments. However, the low accuracy rate and the absence of the prior knowledge learning limit their adaptation in underwater applications. Aiming to solve the problems originated from the inhomogeneous lumination and the unstable background, the mechanism of the visual information sensing and processing pattern from the eye of frogs are imitated to produce a hierarchical background model for detecting underwater objects. Firstly, the image is segmented into several subblocks. The intensity information is extracted for establishing background model which could roughly identify the object and the background regions. The texture feature of each pixel in the rough object region is further analyzed to generate the object contour precisely. Experimental results demonstrate that the proposed method gives a better performance. Compared to the traditional Gaussian background model, the completeness of the object detection is 97.92% with only 0.94% of the background region that is included in the detection results. Jie Shen, Tanghuai Fan, Min Tang, Qian Zhang, Zhen Sun, and Fengchen Huang Copyright © 2014 Jie Shen et al. All rights reserved. Effects of First-Time Overnight CPAP Therapy for Increasing the Complexity of the Patient’s Physiological System Mon, 21 Jul 2014 09:45:04 +0000 Studies regarding the effects of short-term continuous positive airway pressure (CPAP) therapy are not sufficient. A total of 35 patients with moderate to severe untreated OSA were divided into 2 groups. Group 1 comprised 22 patients who underwent polysomnography (PSG) for one night, and Group 2 comprised 13 patients who received PSG combined with CPAP therapy. To evaluate the influence of receiving CPAP therapy for one night, we measured 5 min wrist pulse signals before and after the experiment to assess heart rate variability, as well as novel short time multiscale entropy (sMSE) indicator that examines complexity in physiological signals. The results show that the participants in Group 1 exhibited significant changes in normalized low-frequency power/normalized high-frequency power (nLF/nHF) (0.72 ± 0.09 versus 1.11 ± 0.11, ) values before and after the PSG study. By contrast, the participants in Group 2 showed no significant changes in the 3 indicators. Regarding the sMSE indicator, Group 2 patients exhibited significant increases in the sMSE. CPAP therapy administered for one night can reduce the sympathovagal imbalance in patients with moderate to severe untreated OSA and increase the complexity of the patient’s physiological system, thereby reflecting their overall improved health. Hsien-Tsai Wu, Hong-Ruei Chen, Wen-Yao Pan, Cyuan-Cin Liu, Mao-Chang Su, and Meng-Chih Lin Copyright © 2014 Hsien-Tsai Wu et al. All rights reserved. Path-Counting Formulas for Generalized Kinship Coefficients and Condensed Identity Coefficients Mon, 21 Jul 2014 08:32:51 +0000 An important computation on pedigree data is the calculation of condensed identity coefficients, which provide a complete description of the degree of relatedness of two individuals. The applications of condensed identity coefficients range from genetic counseling to disease tracking. Condensed identity coefficients can be computed using linear combinations of generalized kinship coefficients for two, three, four individuals, and two pairs of individuals and there are recursive formulas for computing those generalized kinship coefficients (Karigl, 1981). Path-counting formulas have been proposed for the (generalized) kinship coefficients for two (three) individuals but there have been no path-counting formulas for the other generalized kinship coefficients. It has also been shown that the computation of the (generalized) kinship coefficients for two (three) individuals using path-counting formulas is efficient for large pedigrees, together with path encoding schemes tailored for pedigree graphs. In this paper, we propose a framework for deriving path-counting formulas for generalized kinship coefficients. Then, we present the path-counting formulas for all generalized kinship coefficients for which there are recursive formulas and which are sufficient for computing condensed identity coefficients. We also perform experiments to compare the efficiency of our method with the recursive method for computing condensed identity coefficients on large pedigrees. En Cheng and Z. Meral Ozsoyoglu Copyright © 2014 En Cheng and Z. Meral Ozsoyoglu. All rights reserved. Image Tracking for the High Similarity Drug Tablets Based on Light Intensity Reflective Energy and Artificial Neural Network Thu, 17 Jul 2014 11:55:44 +0000 It is obvious that tablet image tracking exerts a notable influence on the efficiency and reliability of high-speed drug mass production, and, simultaneously, it also emerges as a big difficult problem and targeted focus during production monitoring in recent years, due to the high similarity shape and random position distribution of those objectives to be searched for. For the purpose of tracking tablets accurately in random distribution, through using surface fitting approach and transitional vector determination, the calibrated surface of light intensity reflective energy can be established, describing the shape topology and topography details of objective tablet. On this basis, the mathematical properties of these established surfaces have been proposed, and thereafter artificial neural network (ANN) has been employed for classifying those moving targeted tablets by recognizing their different surface properties; therefore, the instantaneous coordinate positions of those drug tablets on one image frame can then be determined. By repeating identical pattern recognition on the next image frame, the real-time movements of objective tablet templates were successfully tracked in sequence. This paper provides reliable references and new research ideas for the real-time objective tracking in the case of drug production practices. Zhongwei Liang, Liang Zhou, Xiaochu Liu, and Xiaogang Wang Copyright © 2014 Zhongwei Liang et al. All rights reserved. Segmentation of Intensity Inhomogeneous Brain MR Images Using Active Contours Wed, 16 Jul 2014 09:13:11 +0000 Segmentation of intensity inhomogeneous regions is a well-known problem in image analysis applications. This paper presents a region-based active contour method for image segmentation, which properly works in the context of intensity inhomogeneity problem. The proposed region-based active contour method embeds both region and gradient information unlike traditional methods. It contains mainly two terms, area and length, in which the area term practices a new region-based signed pressure force (SPF) function, which utilizes mean values from a certain neighborhood using the local binary fitted (LBF) energy model. In turn, the length term uses gradient information. The novelty of our method is to locally compute new SPF function, which uses local mean values and is able to detect boundaries of the homogenous regions. Finally, a truncated Gaussian kernel is used to regularize the level set function, which not only regularizes it but also removes the need of computationally expensive reinitialization. The proposed method targets the segmentation problem of intensity inhomogeneous images and reduces the time complexity among locally computed active contour methods. The experimental results show that the proposed method yields better segmentation result as well as less time complexity compared with the state-of-the-art active contour methods. Farhan Akram, Jeong Heon Kim, Han Ul Lim, and Kwang Nam Choi Copyright © 2014 Farhan Akram et al. All rights reserved. Screening for Prediabetes Using Machine Learning Models Wed, 16 Jul 2014 00:00:00 +0000 The global prevalence of diabetes is rapidly increasing. Studies support the necessity of screening and interventions for prediabetes, which could result in serious complications and diabetes. This study aimed at developing an intelligence-based screening model for prediabetes. Data from the Korean National Health and Nutrition Examination Survey (KNHANES) were used, excluding subjects with diabetes. The KNHANES 2010 data were used for training and internal validation, while data from KNHANES 2011 were used for external validation. We developed two models to screen for prediabetes using an artificial neural network (ANN) and support vector machine (SVM) and performed a systematic evaluation of the models using internal and external validation. We compared the performance of our models with that of a screening score model based on logistic regression analysis for prediabetes that had been developed previously. The SVM model showed the areas under the curve of 0.731 in the external datasets, which is higher than those of the ANN model (0.729) and the screening score model (0.712), respectively. The prescreening methods developed in this study performed better than the screening score model that had been developed previously and may be more effective method for prediabetes screening. Soo Beom Choi, Won Jae Kim, Tae Keun Yoo, Jee Soo Park, Jai Won Chung, Yong-ho Lee, Eun Seok Kang, and Deok Won Kim Copyright © 2014 Soo Beom Choi et al. All rights reserved. A Note regarding Problems with Interaction and Varying Block Sizes in a Comparison of Endotracheal Tubes Tue, 15 Jul 2014 07:57:26 +0000 A randomized clinical experiment to compare two types of endotracheal tubes utilized a block design where each of the six participating anesthesiologists performed tube insertions for an equal number of patients for each type of tube. Five anesthesiologists intubated at least three patients with each tube type, but one anesthesiologist intubated only one patient per tube type. Overall, one type of tube outperformed the other on all three effectiveness measures. However, analysis of the data using an interaction model gave conflicting and misleading results, making the tube with the better performance appear to perform worse. This surprising result was caused by the undue influence of the data for the anesthesiologist who intubated only two patients. We therefore urge caution in interpreting results from interaction models with designs containing small blocks. Richard L. Einsporn and Zhenyu Jia Copyright © 2014 Richard L. Einsporn and Zhenyu Jia. All rights reserved. Automatic Blastomere Recognition from a Single Embryo Image Mon, 14 Jul 2014 14:23:12 +0000 The number of blastomeres of human day 3 embryos is one of the most important criteria for evaluating embryo viability. However, due to the transparency and overlap of blastomeres, it is a challenge to recognize blastomeres automatically using a single embryo image. This study proposes an approach based on least square curve fitting (LSCF) for automatic blastomere recognition from a single image. First, combining edge detection, deletion of multiple connected points, and dilation and erosion, an effective preprocessing method was designed to obtain part of blastomere edges that were singly connected. Next, an automatic recognition method for blastomeres was proposed using least square circle fitting. This algorithm was tested on 381 embryo microscopic images obtained from the eight-cell period, and the results were compared with those provided by experts. Embryos were recognized with a 0 error rate occupancy of 21.59%, and the ratio of embryos in which the false recognition number was less than or equal to 2 was 83.16%. This experiment demonstrated that our method could efficiently and rapidly recognize the number of blastomeres from a single embryo image without the need to reconstruct the three-dimensional model of the blastomeres first; this method is simple and efficient. Yun Tian, Ya-bo Yin, Fu-qing Duan, Wei-zhou Wang, Wei Wang, and Ming-quan Zhou Copyright © 2014 Yun Tian et al. All rights reserved. ProBLM Web Server: Protein and Membrane Placement and Orientation Package Mon, 14 Jul 2014 12:37:50 +0000 The 3D structures of membrane proteins are typically determined without the presence of a lipid bilayer. For the purpose of studying the role of membranes on the wild type characteristics of the corresponding protein, determining the position and orientation of transmembrane proteins within a membrane environment is highly desirable. Here we report a geometry-based approach to automatically insert a membrane protein with a known 3D structure into pregenerated lipid bilayer membranes with various dimensions and lipid compositions or into a pseudomembrane. The pseudomembrane is built using the Protein Nano-Object Integrator which generates a parallelepiped of user-specified dimensions made up of pseudoatoms. The pseudomembrane allows for modeling the desolvation effects while avoiding plausible errors associated with wrongly assigned protein-lipid contacts. The method is implemented into a web server, the ProBLM server, which is freely available to the biophysical community. The web server allows the user to upload a protein coordinate file and any missing residues or heavy atoms are regenerated. ProBLM then creates a combined protein-membrane complex from the given membrane protein and bilayer lipid membrane or pseudomembrane. The user is given an option to manually refine the model by manipulating the position and orientation of the protein with respect to the membrane. Taylor Kimmett, Nicholas Smith, Shawn Witham, Marharyta Petukh, Subhra Sarkar, and Emil Alexov Copyright © 2014 Taylor Kimmett et al. All rights reserved. Privacy-Preserving Self-Helped Medical Diagnosis Scheme Based on Secure Two-Party Computation in Wireless Sensor Networks Mon, 14 Jul 2014 09:54:38 +0000 With the continuing growth of wireless sensor networks in pervasive medical care, people pay more and more attention to privacy in medical monitoring, diagnosis, treatment, and patient care. On one hand, we expect the public health institutions to provide us with better service. On the other hand, we would not like to leak our personal health information to them. In order to balance this contradiction, in this paper we design a privacy-preserving self-helped medical diagnosis scheme based on secure two-party computation in wireless sensor networks so that patients can privately diagnose themselves by inputting a health card into a self-helped medical diagnosis ATM to obtain a diagnostic report just like drawing money from a bank ATM without revealing patients’ health information and doctors’ diagnostic skill. It makes secure self-helped disease diagnosis feasible and greatly benefits patients as well as relieving the heavy pressure of public health institutions. Yi Sun, Qiaoyan Wen, Yudong Zhang, and Wenmin Li Copyright © 2014 Yi Sun et al. All rights reserved. Computational and Control Methods in Rehabilitation Medicine Mon, 14 Jul 2014 00:00:00 +0000 Imre Cikajlo, Takashi Watanabe, and Strahinja Dosen Copyright © 2014 Imre Cikajlo et al. All rights reserved.