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Issue 1, Volume 5,
January 2008
Title
of the Paper: Motor Control Information Extracted from Surface EMG as
Muscle Force Estimation
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Authors:
Rok Istenic, Ales Holobar, Marco Gazzoni, Damjan Zazula
Abstract: The aim of this paper is to introduce an extension to a force
estimation technique based on activity index and to compare it to two other
muscle force estimation techniques that also use the motor control
information on the same set of surface EMG signals. Our new method is called
motor unit twitch force technique and the compared methods include motor unit
action potential rate and activity index. The main difference of the three
compared methods lies in the extraction of the motor control information from
multi-channel surface EMG. Motor unit action potential rate and activity
index measure global muscle activity as they represent the summation of
innervation pulse trains of all active motor units, while twitch force
technique decomposes the surface EMG and obtains the activity of all active
individual motor units separately. This means a great improvement over
activity index and motor unit action potential rate methods as both force
regulation principles, i.e. motor unit recruitment and firing rate modulation
can be observed. Surface EMG signals used in the experiment were recorded
from biceps brachii muscle during elbow flexion on five subjects. Two-dimensional
matrix of surface electrodes (13 rows by 5 columns) was applied. Isometric
constant force contractions at three different force levels were performed,
i.e. at 5, 10 and 30 % of maximal voluntary contraction. Torque produced at
the elbow joint was measured simultaneously with surface EMG. The force
estimation error of the methods was measured by root mean square error
between the recorded and estimated force. Our new motor unit twitch force
technique reduced the muscle force estimation error significantly, for 13%
when compared to the motor unit action potential rate, and for 2% when
compared to the activity index method.
Keywords: surface electromyography, muscle force estimation, EMG force
relationship, MUAP rate, activity index, twitch force
Title
of the Paper: Agreement
between Multi-Layer Perceptron and a Compound
Neural Network on ECG Diagnosis of Aatrioventricular Blocks
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Authors:
Salama Meghriche, Mohammed Boulemden, Amer Draa
Abstract: Artificial Neural Networks (ANN) are computer-based expert systems
that have proved to be useful in pattern recognition tasks. ANN can be used
in different phases of the decision-making process, from classification to
diagnostic procedures. In this work, we develop two methods. The first one
based on a compound neural network (CNN) composed of three different
multilayer neural networks of the feed forward type, and the second one based
on only a multi-layer perceptron (MLP). Such both of them have the capability
to classify electrocardiograms (ECG) as normal or as carrying atrioventricular
blocks (AVB). These networks were fed with same measurements from one lead of
the ECG. A single output unit encodes the probability of AVB occurrences. The
difference in performance between the two neural networks classifiers was
measured as the difference in area under the receiver operating
characteristic curves (ROC). The results show that the CNN and MLP have a
good performance in detecting AVBs.
Keywords: Artificial neural networks, Biomedical data,
Electrocardiogram (ECG), Medical diagnosis, Pattern recognition, Signal
processing,
Issue 2, Volume 5,
February 2008
Title
of the Paper: Minimization of Tumor Volume and Endothelial Support for a
System Describing Tumor Anti-Angiogenesis
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Authors:
Urszula Ledzewicz, Heinz Schattler
Abstract: Anti-angiogenic therapy is a novel treatment approach for cancer
that aims at preventing a tumor from developing its own network of blood
vessels that it needs for its supply of nutrients and thus indirectly
inhibits the growth of the tumor. In this paper a mathematical model for
anti-angiogenic treatment is analyzed as a 3- dimensional optimal control
problem with the aim of minimizing a convex combination of tumor volume and
endothelial support. The latter represents a measure for the size of the
tumor’s vasculature. The results are compared with the solutions for the
problem when only the tumor volume is minimized.
Keywords: Optimal control, singular controls, cancer treatments, tumor
growth, anti-angiogenesis
Title
of the Paper: Random Modeling of Population Dynamics with Uncertainty
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Authors:
Gilberto Gonzalez, Lucas
Jodar, Rafael
Villanueva, Fransisco
Santonja
Abstract: Obesity is growing at an important rate in developed and developing
countries and it is becoming a serious disease not only from the individual
health point of view but also from the public socioeconomic one. In this
paper it is studied the effect of uncertainty in the dynamics behavior of the
overweight and obesity childhood populations. Since initial conditions and
parameters appearing in a deterministic mathematical model of obesity
population are subject to some degree of uncertainty, randomness in the
differential equations are introduced in the initial conditions and in the
most relevant parameter of the deterministic model. Additionally, in this
work stochastic and random ordinary differential equations were used to study
the randomness effect in the deterministic mathematical model of obesity
population. Monte Carlo
simulations are performed assuming different distributions for the initial
conditions and parameters of the model. Furthermore, confidence intervals and
expected solutions of the random models are also obtained. To verify the
consistence of the method, results are compared against numerical solutions
of the deterministic mathematical model.
Keywords: Random differential equation, Population dynamics, Numerical
simulation, Stochastic differential equation, Monte Carlo method.
Issue 3, Volume 5,
March 2008
Title
of the Paper: Minimizing the Set Up for ADL Monitoring through DTW
Hierarchical Classification on Accelerometer Data
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Authors:
Rossana Muscillo, Silvia Conforto, Maurizio Schmid, Tommaso D’Alessio
Abstract: Systems for remote monitoring of motor activities in the elderly
are becoming very popular in developed countries. In this context,
recognition and classification of Activities of Daily Living (ADL) is a very
important step that can open intriguing scenarios, especially if real-time
techniques become available. The present work proposes a hierarchical
classifier based on the Dynamic Time Warping (DTW) technique, applied on data
recorded from a tri-axial accelerometer placed on the shin, to classify among
different motor activities. The classifier was applied to the recognition of
walking, climbing and descending stairs of five different subjects. After the
calibration phase needed to extract the templates, the technique makes it
possible to recognize activities by determining the distance between the
signal input and a set of the previously defined templates. Signals coming
from the three different channels are used in a hierarchical way, with three
layers. The hierarchy has been set based on sorting channels by signal to
noise ratio in descending order. The results show a classification with
overall percentage of error less than 5%.
Keywords: Wearable sensors, Accelerometer, ADL , Dynamic Time Warping,
Template, Classification
Title
of the Paper: Comparison of Cluster Identification Methods for Selection
of GO Terms related to Gene Clusters
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Authors:
Yoichi Yamada, Yuki Miyata, Masanori Higashihara, Kenji Satou
Abstract: The hierarchical clustering algorithm has frequently been applied
to grouping genes sharing a certain characteristic from a microarray data
set. Identification of clusters from a hierarchical cluster tree is generally
conducted by cutting the tree at a certain level. In this method, the most
parental clusters are identified as mutually correlated gene groups and their
sibling clusters are ignored. However the sibling clusters have a possibility
to show more significant GO term annotation than their parental clusters. To
overcome this problem, Toronen developed a novel algorithm based on the
calculation of each GO annotation in all the clusters that satisfy a
threshold of correlation distance. However comparison of the algorithm and
the general method has not been done enough yet. Therefore we compared the
general method with Toronen‟s proposed algorithm for
identifying gene cluster-relevant GO terms. Moreover, we compared the
hierarchical clustering with fuzzy k-means clustering which can group a
object into more than one cluster and permit a object not to belong to any
clusters. Consequently, we confirmed that Toronen‟s
algorithm is more available for identification of gene clusters and their
relevant GO terms from a microarray data set than the other methods.
Keywords: Hierarchical clustering, Gene Ontology, Microarray data,
Yeast cell cycle
Issue 4, Volume 5,
April 2008
Title
of the Paper: Stabilizing Effect of Prey Competition for Predators
Exhibiting Switching Feeding Behavior
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Authors:
Valerio Ajraldi, Ezio Venturino
Abstract: The classical model by Tanksy on a two-level food web with a
predator feeding on two kinds of prey is revisited and extended. The
ecosystem with intraspecific and interspecific competition for resources
among the prey is analized. Two equilibria are found: a segment of
conditionally (neutrally) stable equilibrium points and the interior
coexistence equilibrium, which is proven to be inconditionally stable. The
predator population settles to a lower level than the one arising in the
original Tansky’s model. In addition, there is inverse proportionality
between the predators’ mortality and the equilibrium value. Predators’
recovery and the settling of the system toward coexistence are also allowed
by a large prey carrying capacity.
Keywords: Predator-prey, switching mechanism, Tansky model,
competition, stable equilibria
Title
of the Paper: Blood Glucose Data Processing for Automated Diagnosis
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Authors:
Eugen Iancu, Ionela Iancu, Maria Mota
Abstract: The actual protocols used in diagnosis and management of the
diabetes mellitus include the classical clinical trials and the physicians’
experience, but they do not account by the dynamics of the blood glucose and
insulin. So, it is natural to have many diabetes patients with poor control
of blood glucose values. The introduction in the medical practice of the
blood glucose continuous monitoring systems has made possible the automated
analyse of blood glucose dynamics. Along this paper the authors present
algorithms for automatic diagnosis in the diabetic patients monitoring with
applications, especially in the intensive care units and telemedicine. We
have focused on the statistical analysis methods in order to detect the
reliable characteristics, useful in the identification of standard aspects or
stable patterns for each type and stage of the complex and long-term
evolution of the disease that is diabetes mellitus. Examples of the frequency
range of blood glucose dynamics of normal subjects and subjects with diabetes
are presented with the help of Wigner-Ville distribution. The spectral
analysis reveals the frequency band edge and offers the basic information to
correct determination of Nyquist sample period. These findings may have
significant clinical implication in diagnosis of the diabetes mellitus, in
blood glucose monitoring and the management of the diabetes therapy.
Keywords: Statistical analysis, Diabetes mellitus, Continuous glucose
monitoring, Probability distribution function, Periodogram, Correlation
Issue 5, Volume 5,
May 2008
Title
of the Paper: Drug Resistants Impact on Tuberculosis Transmission
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Authors:
Silvia Martorano Raimundo, Ezio Venturino
Abstract: In epidemiology, measures for prophilaxis of infectious diseases
are taken often using mathematical methods and statistical tools to evaluate
possible future scenarios of the evolution of transmissible diseases. Here we
present two models for TB transitions among different stages of the disease. We
analyze them assuming to have a large basin of susceptible individuals
available. The models account for immigration and demographic effects. A flow
of infected members into the population is assumed. Part of it is made by a
specified fraction is drug-sensitive latent individuals, while the other part
consists of drug-resistant latent individuals. Our aim is the description and
analysis of all the possible ways the infected individuals move. In
particular, from the classes of latent to infectious, and possibly back upon
successful treatment, or toward acute stages of the disease for drug
resistant cases due to improper, incomplete or ineffective healing measures. Some
conditions for the eradication of the disease are extracted from analytical
considerations and simulation results and might be useful for epidemiological
implementations.
Keywords: Drug resistant, transmissible disease, tuberculosis.
Title
of the Paper: Application of a Feature Selection Method to Nucleosome
Data: Accuracy Improvement and Comparison with Other Methods
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Authors:
Masanori Higashihara, Jovan David Rebolledo-Mendez, Yoichi Yamada, Kenji
Satou
Abstract: In binary classification problem, data of feature vectors with
binary labels are prepared in general. However, today it is well known that
using all the features for discrimination does not always the best way to
achieve the highest accuracy in prediction. Feature selection is a technique
to find a subset of features with the highest accuracy by eliminating
features harmful in prediction. Among various methods proposed, in this study
we used a method which can be divided in two steps. Firstly, along the ranked
features f1,…,fn based on Gini index, the feature subsets
{f1},{f1,f2},...,{f1,…,fn} are tested by SVM with RBF kernel. Secondary,
variants of the best feature subset found in the first step are tested in the
same way. In the application to the prediction of nucleosome occupancy and
modification from genome subsequence, the method achieved a small but assured
improvement from the previous study. In addition, observed ranking of
features revealed some relationships between features and categories of
nucleosome datasets. Finally, the method was compared with other promising
methods and outperformed them.
Keywords: Epigenetics, Histone, Acetylation, Methylation, Feature
selection, Support vector machine, Gini-index, Random forest
Issue 6, Volume 5,
June 2008
Title
of the Paper: A Fractal Approach to Pattern Formation in Biological
Systems
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Authors:
Radu Dobrescu, Loretta Ichim, Stefan Mocanu, Stefan Popa
Abstract: The paper discusses the connection between pattern formation and
nonlinear dynamics, focusing on the similarity between discrete patterns and
fractal structures, and then describes different solutions to model
reaction-diffusion systems as representative processes in morphogenesis. The
option for a discrete model and the steps to design it as a fractal structure
is argued. Construction of appropriate generic model is an important step
towards understanding the bacteria. It is shown how a pattern with arbitrary
complexity like a fractal pattern can be realized by a reaction-diffusion
system. A specific example is the diffusion limited aggregation growth
process, illustrated by the simulation of the evolution of a bacterial colony
that shows the roles of instability and sensitivity in nonequilibrium pattern
formation.
Keywords: morphogenesis, pattern formation, reaction-diffusion
systems, fractal analysis, attractors, diffusion limited aggregation
Title of the Paper: Stationary Densities and Parameter
Estimation for Delayed Stochastic Logistic Growth Laws with Application in
Biomedical Studies
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Authors:
Petras Rupsys
Abstract: The study of nonlinear stochastic delayed process is significant
for understanding nature of complex system in reductionistic viewpoints. This
paper investigates the stochastic linear and logistic (Verhulst, Gompertz and
Richards) models, and simulates the growth process of Ehrilch ascities tumor
(EAT) in a mouse. In order to explain the oscillations of EAT growth we use a
system of stochastic differential equations with time delay. We derive the
exact and approximate stationary densities in the case of small time delays. For
the estimation of parameters we propose the L1 distance and maximum
likelihood procedures. As an illustrative experience we use a real data set
from repeated measurements on Ehrilch ascities tumor in a mouse. The results
are implemented in the symbolic computational language MAPLE.
Keywords: Ehrilch ascities tumor,
Stochastic differential equation, Density function, Fokker-Plank equation,
Numerical solution.
Issue 7, Volume
5, July 2008
Title of the Paper: Phenotypic Characteristics,
Antibiotic Susceptibility and Pathogenicity of Ornithobacterium
Rhinotracheale
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Authors: Zaini Mohd-Zain, Tan Lin Jee, Kamaruzaman
Jusoff
Abstract:- Ornithobacterium rhinotracheale (ORT) has been recently recognized
as one of the respiratory pathogen in poultry. This bacterium produces
clinical signs in chickens which are almost similar to the infection of
Avibacterium paragallinarum, thus making diagnosis difficult. A collection of
18 isolates of O. rhinotracheale obtained from diseased chickens in Malaysia were
characterized and their pathogenicity in embryonated eggs and chickens was
investigated and compared to a reference strain. Antimicrobial susceptibility
pattern of these isolates against seven antibiotics were determined using
Kirby-Bauer diffusion test while minimal inhibition concentration (MIC) of
tylosin and tilmicosin were performed using agar dilution method following
the guidelines of Clinical and Laboratory Standards Institute. Biochemical
and enzymatic tests results showed that the O. rhinotracheale isolates were
made up of two variants that differ from the reference strain in their
fermentation of arginine and glucose. Serotyping of these isolates revealed
that all of the isolates were serotype A. Antimicrobial susceptibility test
performed using antimicrobial disks showed that at least two of the isolates
were resistant to more than three of the antibiotics tested. High (>128 μg/ml)
minimal inhibition concentration (MIC) of tylosin and tilmicosin was observed
in the isolates. Two representatives from these isolates were tested for
their ability to cause mortality in egg embryos and their clinical
manifestations in specific-pathogen-free (SPF) chickens. When compared to uninoculated
embryos, these two isolates were found to cause significantly (P<0.01)
higher number of embryo mortality. Infection of these isolates in SPF
chickens caused growth retardation but no respiratory symptoms were observed.
The results obtained in this study have provided some basic information on
the properties of O. rhinotracheale that would be useful in diagnosing the
disease. The understanding of its role in poultry health provides some
information that could be useful in implementing preventive measures against
the disease.
Key-Words: - Ornithobacterium
rhinotracheale, embryo mortality, growth retardation, chickens, antibiotic
resistant, Malaysia.
Title of the Paper: Decomposition of Synthetic
Surface Electromyograms Using Sequential Convolution Kernel Compensation
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Authors:
V. Glaser, A. Holobar, D. Zazula
Abstract: - This paper reveals a sequential decomposition method based on
Convolution Kernel Compensation (CKC). It operates in real time and can
decompose linear mixtures of finite-length signals. Multiple-input
multiple-output (MIMO) signal model is used with finite channel responses and
trains of delta pulses as inputs. Our approach compensates the channel
responses and reconstructs the input pulse trains in real time, when samples
of the observed signals become available. Two versions of the sequential
decomposition were tested: sample-by-sample and multiple sample input. The
time complexity of the two approaches, is analytically evaluated and
supported by the experimental measurements. Performance tests on the
synthetic surface electromyograms (sEMG) provide estimations of average rate
and standard deviation of the reconstructed pulse trains for single motor
units (MU).
Key-Words: – Compound signal
decomposition, Surface electromyogram, Real-time signal processing,
Sherman-Morrison-Woodbury matrix inversion, Sequential convolution kernel
compensation, antibiotic resistant, Malaysia.
Title of the Paper: Prediction of Genomic
Methylation Status on CpG
Islands Using DNA
Sequence Features
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Authors:
Yoichi
Yamada, Kenji Satou
Abstract: -. In mammals, cytosines of most CpG dinucleotides in their genomes
except gene promoters are subject to modification by methyl group
(methylation). A number of genes in a mammal are regulated developmental-
specifically or tissue-specifically by the methylation. Mammalian DNA
methylation contributes to regulation of gene expression, repression of
parasitic sequences, inactivation of X chromosome in female, genomic
imprinting, etc. Aberrant methylation results in a part of cancers and
genetic diseases in human. Therefore it is required that methylation status
on human genome is comprehensively revealed in each kind of cells. However,
since comprehensive methylation analyses require a lot of times and large
labor, methylation status on only a part of genomic regions is revealed in
mammals. Because of this, machine learning using already known methylation
data and prediction of methylation status on other genomic regions are
important. Moreover, since sequence differences between DNA regions showing
different methylation status also remain unclear, those differences should be
also determined. Therefore we conducted machine learning by support vector
machine using our previously reported methylation data, and predicted
methylation status on DNA sequences using DNA sequence features. Furthermore
we explored different sequence features among four types of methylation using
random forest. Consequently high methylation prediction accuracies were
observed between two different methylation status pairs. Moreover it was
revealed that sequences containing CG, CT or CA were important for
discrimination between them.
Key-Words: - CpG island, DNA methylation,
Human chromosome 11, Human chromosome 21, Support vector.
Title of the Paper: Characterization and
Clustering of GO Terms by Feature Importance Vectors Obtained from Microarray
Data
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Authors:
Jovan David Rebolledo-Mendez, Masanori Higashihara, Yoichi Yamada, Kenji
Satou
Abstract: - In this paper it is explained a new approach for clustering Gene
Ontology (GO) terms by examining microarray data related to them. By
segmenting the entire ontology in a single specific level, and applying
techniques as discrimination and ranking of features to those GO terms that
are contained in that level, it is produced a characterization of the
contained terms, as feature importance vectors related to the gene expression
patterns that are included in the microarray dataset. By utilizing data
mining techniques to cluster the vectors, it is concluded that this new
approach may help to obtain relations that are normally hidden among GO
terms, not only the ones in the same contained ontology, but also getting a
trans-ontological relationship of them.
Key-Words: - Gene Ontology,
Microarray data, Random forest, Feature ranking, Hierarchical clustering,
Data mining, Machine learning, Ontology clustering.
Title
of the Paper: Performance Evaluation of Parallel Processing Environment for
Molecular Dynamics
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Authors: Kenji Satou, Kenri Konno, Osamu Ohta,
Kazunori Mikami, Keita Teranishi, Yoichi Yamada, Shin-Ya Ohki
Abstract: - Molecular dynamics (MD) is one of the popular applications in the
research field of high performance computing. Since it requires large amount
of CPU time basically proportional to the square of the number of atoms
simulated, acceleration of MD is essential to simulation of large biomolecules
like proteins. Therefore, parallelization of MD has been actively studied
long time. However, most of the studies of parallel MD report modified or
newly developed algorithms specialized to some computer architectures like
vector-parallel supercomputer, and an end-user of MD software cannot
implement them to popular MD software developed by other ones. In this study,
we evaluated performance of four kinds of computer architectures: 1)
vector-parallel supercomputer, 2) multi-processor machine with shared memory,
3) multi-processor machine with distributed memory, and 4) PC cluster. Various
compiler options for parallelization and optimization were tested.
Experimental results revealed that if MD software is not parallelized nor
vectorized in source level, use of normal PC cluster with maximum use of
optimization options in compilation is the best way.
Key-Words: - Molecular dynamics
software, Computer architecture, Parallel processing, Optimization.
Issue 8, Volume
5, August 2008
Title of the Paper: Cortical
Signal Recording using an Economical Microelectrode Fabricated on Printed
Circuit Board
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Authors:
Yao-Ming Yu, Rong-Chin Lo
Abstract: - This work presents a simple, flexible and economical microwire
array electrode for extracellular cortical recordings. The proposed procedure
is relatively simple, even for a novice worker to implement in-house. These
main steps include design and sculpturing PCB, straightening microwires,
connecting PCB pattern, arraying and soldering microwires and packaging the
microelectrode. A practiced researcher can assemble the microelectrode in
about two hours and implant it in approximately three. The mass of this
assembled microelectrode is 1.96g. The cost of the materials in the entire
array is less than US$1.5, and the array is suitable for implantation in the
cortex of rats for neurophysiology studies. In this study, electrochemical
impedance spectroscopy is also applied to measure the impedance and the phase
between the electrode and the electrolyte, and then to obtain an equivalent
circuit. The improved microwire array electrode is adopted to record the
extracellular cortical signal of cerebrum. The microwire array electrode can
be fabricated and used for multi-site, multiple single-unit recording
experiments.
Key-Words: - Microelectrode, Printed circuit board, Flexible flat
cable, Extracellular, Electrochemical impedance spectroscopy
Title of the Paper: Electronic Health Records and
Decision Support Local and Global Perspectives
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Authors:
Jose Neves, Manuel Santos, Jose Machado, Antonio Abelha, Sollari Allegro,
Maria Salazar
Abstract: Safer, less expensive, and higher-quality health care can be
achieved using clinical decision support (CDS), although the use of CDS often
leads to disappointing results. Various problems and limitations can be
pointed being the most frequently referred by the physicians the inadequate
implementation of the clinical workflow. Electronic Health Records (EHR) and
Patient Health Record Systems (PHRS) can play an important role in CDS
mitigating those limitations and enabling the effective use of the archived
information in the support of the clinical practice and generating the right
knowledge to make decisions. The availability of such knowledge is crucial
either, for the hospitals and for the government institutions. This brings new
requirements for the EHR and PHRS conception and for the use of the
information out of the boundaries of the hospitals and health centers.
Interoperation and open models constitute the greater challenges that EHR
enfaces in the very next future. This paper presents a survey on the design,
development and implementation of PHRS in terms of organizational, regional,
national and worldwide initiatives. Finally is presented the EHR
implementation in the Hospital Geral de Santo Antonio, EPE, one of the major
hospitals in the North Region of Portugal.
Key-Words: Electronic Health Records, Electronic Medical Records,
Electronic Patient Record System, Interoperation, Terminologies
Title of the Paper: Implementation of
Extracellular Neural Recording System and Study of Evoked Signal Preprocessing
Method
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Authors:
Yao-Ming Yu, Wen-Liang Tsai, Rong-Chin Lo
Abstract: A multichannel recording system of extracellular cortex is utilized
to acquire the neural signal of primary somatosensory cortex in rats. The
extracellular neural recording system includes mainly the acquisition
sub-system, the monitoring sub-system and the analyzing sub-system. We use the
microwire array electrode to record different signal of three types; those are
from on air, from S1HL without stimulation and from S1HL with stimulation by
scratching the claw of the left hind leg using a brush. A signal processing
system is applied to deal with the saved data. Through the method of spectral
subtraction, we can reduce the influence of noise. Beside, nonlinear energy
operator algorithm is employed to detect the timestamp of evoked potential by
external stimuli. The signals are according to the time interval between
preceding and following of timestamp to separate apart into every section.
Each section can proceed to extract the features from every small segment of
the signals and classify evoked potential segments that own similar features
to the same group in the future. Finally, the information of the monitor
system are apply to verify the accuracy of spike detection that the
information comprises the action of external stimulus, the waveform of neural
signal and the voice of speaker, simultaneously. Through the result of
experiments, the developed recording system is suitable for intracortical
signals recording; the proposed method is feasible and effective for noise
reduction and spike detection of extracellular evoked potentials.
Key-Words: Microwire array electrode, Extracellular recording,
Somatosensory evoked potential, Brain machine interface, Moving average,
Spectral subtraction, Nonlinear energy operator
Title of the Paper: Fast Parallelized Algorithm
for ECG Analysis
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Authors:
M. Rizzi, M. D'Aloia, B. Castagnolo
Abstract: A new approach based on the adoption of wavelet transforms is
presented for the R point localization in ECG signals. The conceived real time
signal processing technique, which uses a fast parallelized algorithm, has
been evaluated adopting the standard MIT-BIH Arrhythmia database which
includes specially selected holter recordings with anomalous but clinically
important phenomena. In the procedure a soft thresholding technique is applied
to dyadic scales in which the ECG signal is decomposed. Therefore, noise
contribution is reduced and then signal is easily reconstructed in the time
domain for further processing. Moreover, the tool analyzes the signal on
different level wavelet representation at the same time showing a great
parallelism degree and an enhancement in processing time. To evaluate the
algorithm noise immunity, the MIT-BIH Noise Stress Test Database has been
adopted containing baseline wander, muscle artifacts and electrode motion
artifacts as noise sources. The obtained performance shows the method validity
in terms of algorithm speed up and characteristic parameter values. In fact,
sensitivity and positive predictivity values of about 99.8% are obtained with
a detection error rate of about 0.4%. Moreover, the conceived procedure gives
satisfactory results also for ECG signals heavily corrupted by noise.
Key-Words: ECG, QRS, wavelet transform, parallel filter bank, signal
processing, parallel computing
Issue 9, Volume 5,
September 2008
Title of the Paper: RF-MW Non-Thermal Effect
Enhanced Beta-Galactosidase Expression through the Induction of Dnak Synthesis
in E.coli BL21 DE3
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Authors:
Imad Aoude, Sarah Saab, Nader Aoude, Mohamed Mortada, Fatima Jebai, Mohamed
Ezzeddine
Abstract: Like most of stressful environmental factors RF/MW radiation induce
a higher HSP activity in absence of any heating. A low level of RF radiation
exposure can also increase other enzyme activity by stimulating their
expression in cells in particular the ?-galactosidase activity. The aim of our
work is to study the rate of accumulation of Dnak (HSP70) and the rate of
accumulation of β-galactosidase at the level of RNA messenger. We demonstrate
that Dnak and the β-galactosidase synthesis changes at the level of DNAc
synthesis, using RT-PCR and detection on agarose gel by UV radiation. The
exposure conditions are performed with the nominal radio GSM emitter (Base
Transceiver).
Key-Words: GSM radiation, E-coli, low level exposure; Dnak synthesis,
β-galactosidase activity; β-galactosidase synthesis; non-thermal effect
Title of the Paper: Modular Adaptive Bionics
Structure
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Authors:
Nicu George Bizdoaca, Dan Tarnita, Daniela Tarnita, Anca Petrisor, Elvira
Bizdoaca
Abstract: Applications of biological methods and systems found in nature to
the study and design of engineering systems and modern technology are defined
as BIONICS. The present paper describes a bionics application of shape memory
alloy in construction of orthopedic implant. The main idea of this paper is
related to design modular adaptive implants for fractured bones. In order to
target the efficiency of medical treatment, the implant has to protect the
fractured bone, for the healing period, undertaking much as is possible from
the daily usual load of the healthy bones. After a particular stage of healing
period is passed, using implant modularity, the load is gradually transferred
to bone, assuring in this manner a gradually recover of bone function. The
adaptability of this design is related to medical possibility of the doctor to
made the implant to correspond to patient specifically anatomy. Using a CT
realistic numerical bone models, the mechanical simulation of different types
of loading of the fractured bones treated with conventional method are
presented. The results are commented and conclusions are formulated.
Key-Words: Bionics, modularity, implants, numerical simulation
Title of the Paper: Digestive Database Evidential
Clustering Based on Possibility Theory
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Authors:
Anas Dahabiah, John Puentes, Basel Solaiman
Abstract: A new method that aims to automatically classify a set of objects in
spite of the imperfection and the uncertainty of their
heterogeneously-assigned data is proposed in this paper. This method is based
essentially on possibility theory to estimate the similarity among the
objects, and on belief theory and multidimensional scaling methods to
construct the compatible evidential class partition. This method is applied to
a medical database and robust results have been obtained without knowing the
key attributes of the concerned pathologies and without taking into account
any a priori medical knowledge.
Key-Words: Possibility Theory, Evidence Theory, Similarity, Clustering,
Partition, Multi-Dimensional Scaling
Issue 10, Volume 5,
October 2008
Title of the Paper: A HHT-based Time Frequency
Analysis Scheme in Clinical Alcoholic EEG Signals
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Authors:
Chin-Feng Lin, Shan-Wen Yeh, Yu-Yi Chien, Tsung-Ii Peng, Jung-Hua Wang,
Shun-Hsyung Chang
Abstract: In this paper, a Hilbert-Huang Transformation (HHT)-based time
frequency scheme is applied to the analysis of clinical alcoholic and normal
control FP1 electroencephalogram (EEG) signals. The differences in the
responses of the EEG signals, the intrinsic mode function (IMF), instantaneous
frequency (IF), marginal frequency (MF), and the Hilbert spectrum between the
simulation results of the clinical EEG signals of the alcoholic and control
groups are discussed. When comparing the clinical EEG signals of the alcoholic
and control groups, the EEGs of the control group of picture observers did not
appear to indicate significantly larger voltage. The EEG signals of the
alcoholic group in the experiment suggested that when they were exposed to the
stimulus, brain cells were stimulated and emitted higher voltage. From these
discussion, we can recognize IMFs, IFs, Hilbert Marginal frequency, and
Hilbert spectrum of EEG signals of an alcoholic and a normal observers to
define an alcoholic illness.
Key-Words: Hilbert-Huang Transformation (HHT), time frequency analysis,
alcoholic EEG, clinical signals, intrinsic mode function, Hilbert spectrum
Title of the Paper: New Spectral Numerical
Characterization of DNA Sequences
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Authors:
Igor Pesek, Janez Zerovnik
Abstract: We present new numerical characterization of DNA sequences that is
based on the modified graphical representation proposed by Hamori. While
Hamori embeds the sequence into Euclidean space, we use analogous embedding
into the strong product of graphs, K4xPn , with weighted edges. Based on this
representation, a novel numerical characterization was proposed in [14] which
is based on the products of ten eigenvalues from the start and the end of the
descending ordered list of the eigenvalues of the L/L matrices associated with
DNA. In this paper we compare two further numerical characterizations of the
same type emphasizing the robustness of the approach.
Key-Words: Numerical characterization, graph representation, graph
invariant, DNA sequence
Title of the Paper: An Electronic Circuit Model on
Cone Cell Pathway
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Authors:
Hongjie Li
Abstract: In this article, an electronic circuit model on cone cell pathway is
presented when a light stimulus is given to at the center of receptive field.
The circuit model can simulate potential change characteristics of
corresponding classes of neurons in the retina when visual information is
transferred through the cone cell pathway. These characteristics include
photoelectric conversion and hyperpolarization characteristics of cone cell,
depolarization and hyperpolarization characteristics of bipolar cell, and
action potential generation characteristics of ganglion cell. The simulation
results of the circuit model qualitatively accord with potential change
characteristics of the real neurons.
Key-Words: Cone cell, bipolar cell, ganglion cell, potential, circuit
model, simulation waveform
Issue 11, Volume 5,
November 2008
Title of the Paper: Prognostic Factors in the
Evaluation of Metastatic Breast Cancer
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Authors:
Man Milena Adina, Cosmina Bondor, Ioana Neagoe, Monica Pop, Antigona Trofor,
Dana Alexandrescu, Ruxandra Rajnoveanu, Oana Arghir
Abstract: Breast cancer continues to be a major cause of morbidity and
mortality in women worldwide, one of the most frequent neoplasia in female.
The evaluation of prognostic factors and the follow-up of metastases are major
research areas that enable cancer patients to have maximum therapeutic
benefits, increased quality of life and survival. We conducted a survey from
January 2000 to December 2005 on 120 patients admitted in Cluj-Napoca Oncology
Institute and “Leon Daniello” Pneumology Clinical Hospital. We introduced in
the study patients diagnosed with breast carcinoma and pulmonary metastases,
we analyzed risk factor and evolution of the diseases with survival function
calculated since breast cancer diagnosis, and the other calculated since
pulmonary metastases. Age of the patients over 60 years (p=0.01), urban areas
(p=0.048), smoking (p=0.001), time between the first symptoms and the doctor’
presentation (more than 1 year) was significant statistic in both survival
(p=0.005 and p=0.003). Tumor localization (p=0,95), primary tumor size
(p=0,000), number of metastatic ipsilateral axillary lymph node (p=0,0212) as
prognostic factor in breast cancer. Good performance status (p=0.03), the
stage of the disease at presentation (p=0.004), type of metastasis, good risk
class (p=0.0004), response at the treatment (only 5% had complete response)
influence the survival calculated from the breast cancer diagnosis (69.15% at
1 year, 17.02% at 5 years, 4.26% at 10 years) and the survival calculated from
the moment of pulmonary metastases (32.53% at 1 year, 4.82% at 5 years, 2.41%
at 10 years). Since classical prognostic factors could not be predictive for
all the patients in our studied group, we aimed to identify other prognostic
factors . We examined the status of estrogen and progesterone receptors as
unfavorable predictive factors of treatment response and found that patients
with hormone receptors had a significantly higher survival than those without
the receptors (p=0.0409 for estrogen and p=0.0355 for progesteron). In order
to evaluate tumor aggressiveness we carried out immunohistochemical studies to
detect P53 protein(p=0,012), bcl-2 gene(p=o,678) and PDGF (p=0,637) in the
attempt to demonstrate that these could have been useful in assessing the
future development of breast tumors The identification of prognostic factors (
with mathematics methods) is valuable due to the following three reasons: 1.
Optimum treatment may be selected for each patient 2. Various therapeutic
strategies could be compared among groups of patients with similar recurrence
risks and treatments 3. The knowledge that allows the identification of
recurrence patterns may be improved and new treatment strategies established
Key-Words: Prognostic factor, survival, metastases, breast cancer,
metastases treatment, risk factors
Title of the Paper: An Effective Method for
Detecting Dental Diseases by using Fast Neural Networks
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Authors:
Hazem M. El-Bakry, Nikos Mastorakis
Abstract: In this paper, a new fast algorithm for dental diseases detection is
presented. Such algorithm relies on performing cross correlation in the
frequency domain between input image and the input weights of fast neural
networks (FNNs). It is proved mathematically and practically that the number
of computation steps required for the presented FNNs is less than that needed
by conventional neural networks (CNNs). Simulation results using MATLAB
confirm the theoretical computations. One of the limitations of Direct Digital
Radiography (DDR) is noise. Some recent publications have indicated that
Digital Subtraction Radiography (DSR) might significantly aid in the clinical
diagnosis of dental diseases, once various clinical logistic problems limiting
its widespread use have been over come. Noise in digital radiography may
result from sources other than variation in projection geometry during
exposure. Structure noise consists of all anatomic features other than those
of diagnostic interest. Limitations of plain radiographs in detecting early,
small bone lesions are also due to the presence of structure noise. This
research work has been under - taken in an attempt to minimize structure noise
in digital dental radiography by using digital subtraction radiography. By
minimizing the structure noise, the validity of the digitized image in
detecting diseases is enhanced.
Key-Words: Direct digital radiography, structure noise, dental bone
lesions, digital subtraction radiography, fast neural networks, cross
correlation
Issue 12, Volume 5,
December 2008
Title of the Paper: Multifunctional Health
Information System for the Comprehensive Management of a Sleep Clinics
Franchise Chain
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Authors:
Edgar Daniel Acosta, Francklin Rivas-Echeverria, Solange Gonzalez, Lizmar
Molina, Carlos Rivas-Echeverria
Abstract: In this paper it is presented the prototype of a multifunctional
Health Information System for the Comprehensive Management of a Sleep Clinics
Franchise Chain. This prototype should facilitate the process by which it
obtains, uses or displays a variety of basic resources to support the
objectives of a Sleep Clinic, should facilitate the decision-making process,
the control of the administrative and other day-to day workflow activities and
the clinical management for the diagnosis and treatment of sleep disorders and
related diseases. The rationale of the project is the creation of a system to
ensure the availability of highly skilled and well trained staff that takes
care of patients attending a specialised centre of this kind. The system has
three main sub-systems, these are: a system to manage all the administrative
and (or) day-to-day workflow activities aspects of the clinic. The second, is
a diagnostic and treatment (decision) support system and an electronic health
record, it suggests the physician a diagnostic–therapeutic plan (following
standard and updated guidelines) for each patient; this rulebased subsystem
has been developed following the method for building Expert Systems (ES). The
third subsystem supports an educational program and training tool for the
staff to ensure that they will manage appropriately all the activities of a
specialized centre for diagnosing and treating sleep disorders. The paper
describes the ideas supporting the design, some comments about the system
architecture, the methods that we follow to build it, some conclusions, and
further research.
Key-Words: Information Systems, Expert Systems, Sleep Disorders,
Medical Diagnosis, Artificial Intelligence
Title of the Paper: An Exploratory Research on the
NanoVectors for Drug Delivery and for Gene Therapy
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Authors:
Tang Shao-Pu
Abstract: The purpose of this study is to explore the application of
nanotechnology to prepare optimal vectors for drug delivery systems and for
gene therapy delivery. We first review various types of drug delivery systems
as vectors and then to explore nanovecotrs in gene therapy. By reviewing
relative literature, we found out that nano drug vectors can be administered
by all possible routes of administration and will revolutionize both gene
therapy and the in vivo delivery of drugs. Three relative cases, inclusive of
C Montemagno's study on a biomolecular motor in Cornell University, were
explored. The findings show that applying nanotechnology will provide
preparing nano vectors for both drug delivery and gene therapy another
promising implication.
Key-Words: Nanotechnology, Nanovectors, Biomolecular, Drug delivery,
Gene therapy
Title of the Paper: Applying Boltzmann Equation to
Starch Enzymatic Hydrolysis Modeling
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Authors:
A. Patsioura, E. Reppas, G. Maniatis, V. Gekas
Abstract: In certain enzymatic actions, such as the case of α-amylase
hydrolyzing the starch, the mode of splitting the molecule is random. Various
models, mostly non-deterministic, have been applied to account for this type
of action, as for example the Monte-Carlo procedure. In this paper a new
approach is applied based on the Boltzmann entropy equation where the
multiplicity, W, has the meaning of various possible products after a given
number of hydrolysis stages. Through this analysis the probability of
obtaining the desirable product, which is maltose, is estimated and compared
to experimental results.
Key-Words: Enzymes, enzymatic hydrolysis, starch, α-amylase, maltose,
Boltzmann equation, enzymatic modeling
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